Viral Prevalence Among Social Bees in Different Landscapes Tugce Karacoban University of Nebraska - Lincoln

University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln

Dissertations and Student Research in Entomology Entomology, Department of

12-2018 Viral prevalence among social bees in different landscapes Tugce Karacoban University of Nebraska - Lincoln

Follow this and additional works at: http://digitalcommons.unl.edu/entomologydiss Part of the Entomology Commons, and the Immunology and Infectious Disease Commons

Karacoban, Tugce, "Viral prevalence among social bees in different landscapes" (2018). Dissertations and Student Research in Entomology. 56. http://digitalcommons.unl.edu/entomologydiss/56

This Article is brought to you for free and open access by the Entomology, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Dissertations and Student Research in Entomology by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. VIRAL PREVALENCE AMONG SOCIAL BEES IN DIFFERENT LANDSCAPES

Tugce Karacoban

A THESIS

Presented to the Faculty of Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science

Major: Entomology

Under the Supervision of Professor Judy Wu-Smart

Lincoln, Nebraska

December, 2018

VIRAL PREVALENCE AMONG SOCIAL BEES IN DIFFERENT LANDSCAPES

Tugce Karacoban, M.S.

University of Nebraska, 2018

Advisor: Judy Wu-Smart

Honey bees and wild bees provide important pollination services to numerous crops and native plants. In recent years, declines in bee populations have highlighted the importance of the ecological services they provide and the need for more research into the reasons for their decline. Currently, many conservation efforts to mitigate bee losses include increasing forage and habitat, however, there is growing concern over the role interspecific pathogen transmission plays in bee decline. Viruses commonly found in honey bees may be transmitted and pose a threat to other bee species when bees come together at foraging sites. To elucidate the impact of viruses in bee health decline, I examined the roles flowers, bee management, land type, and foraging activity play in viral prevalence. Bees, pollen (collected from foraging bees), in-hive pollen stores, flowers, and other insects on flowers were analyzed for the presence of four common honey bee viruses using RT-PCR sequencing techniques. To further examine the role bee management and life history traits, such as sociality, may play in the transmission and or persistence of viruses, we compared viral profiles from two species of managed social bees (Apis mellifera, Bombus impatiens) and two species of wild social bees (B. griseocollis, Halictus ligatus). Bees were also collected from different landscapes (urban, agricultural, roadsides and conservation parks) and from short, medium, or long blooming plants to determine how floral traits and land management practices may impact viral profiles among bees.

Acknowledgements

I have so many people to thank that it’s difficult to know where to start. Some contributed directly and some indirectly, but all helped to make this possible.

My path to graduate school may not have been as straightforward as it is for most people, but that is a topic for a whole other book. I did not know I wanted to become a

Researcher/Scientist. I like to work hard, to read and to learn new things. I was working in veterinary medicine at an Animal hospital (Veterinary Surgical Orthopedic Center). I have always loved animals so it was a big honor to make life better for animals in need. Even if

I was feeling that I was doing the best thing in my life, I could not help but feel that I needed to help animals and people at the same time. It is at this point, the importance of bees in the world captured my attention. So I applied for a grant offered by the Republic of Turkey Ministry to complete a graduate degree abroad for the Apiculture Research

Institute of Republic of Turkey Ministry of Food, Agriculture and Livestock. I decided to do my master’s degree in USA and approached Judy Wu-Smart to be one of her graduate students. Although I did not have prior knowledge about bees and beekeeping, I was provided opportunities to learn everything from my advisor and help maintain honey bee colonies. I am very honored and grateful to have had Judy Wu-Smart as my advisor and academic mentor. I cannot find enough words to thank her for all her support, advices, mentorship, friendship, and of course, patience. Judy believed on my potential when I did not even know I had any. And for that I will always thank her.

I want to thank the support from members of the Bee Lab. The list may be long, but I would be remiss if I did not mention all of them: Kayla Mollet, Katie Lamke, Surabhi Gupta

Vakil, Natalia Bjorklund, Dustin Scholl, Sheldon Brummel, Courtney Brummel, Jennifer

Mai Albrecht. I would like to express my special thanks to two of them. In every point of my struggle, Kayla Mollet helped and encouraged me. Thank you Kayla for all your help and good friendship. You are the BEST! Another special thank you to Katie Lamke, who always had time to help with identification of my bees and made time to answer all of my questions.

I would also like to extend my sincere gratitude to my committee members, Drs. Troy

Anderson and Sydney Everhart. I could not have had a better group of faculty. Thank you for all your support, invaluable advice and contributions to my research.

My family, a big thank you for the countless words of support. It wasn’t easy, but without them it would have been much harder. Thanks to Hayriye Karacoban, Orhan Karacoban,

Tolga Karacoban, Zeynep Karacoban and Sema Olgun, my family in Turkey. My partner, best friend, and confidant, Turugsan Olgun. He is my strong shoulder. There are not enough words for me to properly thank you. You made me feel like you were always near me even if we have thousands of miles between us. Thank you so much for your unconditional love.

And last, but never least, my mom and dad. I always felt their love just with a phone call or just a smile at the back of a computer screen. They taught me that there is no limitation to show your love and support. They will always be my angels who just want my favor.

iii

Table of Contents

Acknowledgements ...... i

List of Figures & Tables ...... vi

Chapter 1. Literature review

1.1 The importance of bees ...... 1

1.2 Status of bee decline and contributing stress factors ...... 3

1.3 Honey bee stressors ...... 3

1.4 Viruses in Apis bees, other Hymenopterans, and non-Hymenopteran arthropods ...... 5

1.5 Pathogen transmission ...... 7

1.6 Pathogen transmission in honey bees ...... 9

References cited ...... 15

Chapter 2. An examination of viruses in four different species of bees collected from agricultural, urban, and natural landscapes

2.1 Abstract ...... 19

2.2 Introduction ...... 20

2.3 Materials & Methods ...... 24

2.3.1 Target bee species and site selection ...... 24

2.3.2 Collection method of bees ...... 25

2.3.3 Honey bee colonies and apiaries ...... 26

2.3.4 Bee tissue dissection ...... 27

2.3.5 Sample collection of pollen ...... 27

2.3.6 Total RNA extraction from bees and pollen ...... 28

2.3.7 RT-PCR method ...... 29

2.3.8 Target virus selection and assessment ...... 29

2.3.9 Statistical analysis ...... 31

2.3.9.1 Proportion of infected bees across different landscapes ...... 31

2.3.9.2 Distance-based redundancy analysis of virus type ...... 31

2.3.9.3 Mixed virus infections in honey bee colonies ...... 32

2.4 Result ...... 32

2.4.1 Virus prevalence in foraging bees collected from different landscapes ...... 32

2.4.2 Dissimilarities among bee species, virus type, and season ...... 34

2.4.3 Mixed virus infections in honey bee colonies ...... 35

2.5 Discussion ...... 36

2.5.1 Did the occurrence of viruses differ among the four bee species? ...... 36

2.5.2 How did landscape types correlate with the likelihood of virus detection? ...... 38

2.5.3 Does pollen play a role in interspecific transmission of viruses among bees? ...... 39

2.6 Figures & Tables ...... 41

References cited ...... 52

Chapter 3. An examination of the potential roles foraging activity, flowers, and other insects play in the spread of common honey bee viruses

3.1 Abstract ...... 55

3.2 Introduction ...... 56

3.3 Materials & Methods ...... 60

3.3.1 Site and sample collection ...... 60

3.3.2 Honey bee collection ...... 61

3.3.3 Collection of wild bees and other insects ...... 61

3.3.4 Flower and pollen collection ...... 61

3.3.5 Total RNA extraction ...... 62

3.3.6 RT-PCR analysis ...... 63

3.3.7 Statistical analysis ...... 64

3.3.7.1 Distance-based redundancy analysis of virus types ...... 64

3.4 Result ...... 65

3.4.1 Detection of viruses in foraging insects collected on flowers ...... 65

3.4.2. Dissimilarities among species, virus types and seasons ...... 66

3.5 Discussion ...... 67

3.6 Figures & Tables ...... 70

References cited ...... 80

List of Figures and Tables

Figure 2.1. The percent of individual bees (Apis mellifera, Bombus impatiens, Bombus griseocollis, Halictus ligatus) with detectable levels of viruses (BQCV, DWV, IAPV, and SBV) across different landscape types (urban, agricultural, and open spaces). Statistical analyses were completed using Chi-Square and Fisher’s Exact tests. Significant differences in infected bee species are denoted by “*” at alpha = 0.05 ...... 41

Figure 2.2. The percent of managed (A, mellifera & B. impatiens) & unmanaged bees (B. griseocollis & H. ligatus) with detectable levels of viruses (BQCV, DWV, IAPV, and SBV) across different landscape types (urban, agricultural, and open spaces). Statistical analyses were completed using Chi-Square and Fisher’s Exact tests. Significant differences in infected bees are denoted by “*” at alpha = 0.05...... 42

Figure 2.3. Virus prevalence, or the number of positive detections of BQCV, DWV, IAPV, and or SBV, in pollen loads collected from the legs of foraging honey bees, in-hive pollen stores, and pollen from flower anthers in samples collected in early and late summer (2017– 2018) ...... 43

Figure 2.4. Results from the distance-based redundancy analysis (dbRDA) show the prevalence of viruses in each sample relative to all other samples. Data are visualized using canonical analysis of principal coordinates (CAP) with the “capscale” function performed in R (version 3.5.1). To assess the differences between species (dissimilarity matrix) and the species distribution communities (presence/absence matrix), Bray-Curtis dissimilarity were used. CAP1 and CAP2 are the first two axes from the constrained analysis of principal coordinates, with the respective amount of variation in the Bray-Curtis. Black arrows correspond with DWV, IAPV, BQCV, and SBV virus detections. Individual infections are denoted by solid circles. Samples with more similar virus compositions are closer in proximity to each other and size of points indicate frequency of positive detections. The mean number of infected bee species are represented by open triangles.** Significance from the ‘anova.cca’ test indicate differences among species with 1,000 permutations and denoted by p < 0.001 ...... 44

Figure 2.5. Results from the distance-based redundancy analysis (dbRDA) show the prevalence of viruses in samples collected in early and late summer. Data are visually represented using canonical analysis of principal coordinates (CAP) with the “capscale” function performed in R (version 3.5.1). To assess seasonal differences in viral prevalence and distribution of species communities (presence/absence matrix), Bray-Curtis dissimilarity matrices were used. CAP1 and CAP2 are the axes from the constrained analysis of principal coordinates, with the respective amount of variation in the Bray- Curtis analysis. Black arrows correspond with DWV, IAPV, BQCV, and SBV virus detections. Individual infections are denoted by solid circles. Samples with more similar virus compositions are closer in proximity and size of points indicate frequency of positive detections. Mean infected bees by season was denoted by open triangles. ** Significance

vii

from the ‘anova.cca’ test was used to indicate differences among season with 1,000 permutations and denoted by p < 0.001 ...... 45

Figure 3.1. Distance-based redundancy analysis (dbRDA) was performed. The virus prevalence of each sample relative to all other samples were visualized using canonical analysis of principal coordinates (CAP) with the “capscale” function performed in R (version 3.5.1). CAP1 and CAP2 are the first two axes from the constrained analysis of principal coordinates, with the respective amount of variation in the Bray-Curtis. Black arrows correspond with DWV, IAPV, BQCV, and SBV virus detections. Individual infections are denoted by solid circles (i.e. samples with more similar virus compositions are closer). Size of points indicate frequency of viral detections. Mean of infected species denoted by open triangles. ** Significance from the ‘anova.cca’ test to indicate differences among insect types with 1,000 permutations (p < 0.021) ...... 70

Figure 3.2. Distance-based redundancy analysis (dbRDA) was performed. The virus prevalence of each sample collected on early-, mid-, and late-summer were visualized using canonical analysis of principal coordinates (CAP) with the “capscale” function performed in R (version 3.5.1). CAP1 and CAP2 are the first two axes from the constrained analysis of principal coordinates, with the respective amount of variation in the Bray-Curtis. Black arrows correspond with DWV, IAPV, BQCV, and SBV virus detections. Individual infections are denoted by solid circles (i.e. samples with more similar virus compositions are closer). Size of points indicate frequency of viral detections. Mean of infected species denoted by open triangles. ** Significance from the ‘anova.cca’ test to indicate differences among season with 1,000 permutations (p < 0.021) ...... 71

Table 2.1. Primer sequences and size for each of the four target viruses used in multiplex RT-PCR ...... 46

Table 2.2. Descriptive statistics for positive detections of four common honey bee viruses in managed and wild bees collected from three landscapes types across the season in 2017– 2018. Significance was determined by Fisher’s Exact Test and denoted at alpha = 0.05. Managed and unmanaged bees are shown with upper cases. For Agriculture, Urban, and Open landscapes, the names of viruses were abbreviated as follows: Deformed wing virus (DWV), Black queen cell virus (BQCV), Israeli acute paralysis virus (IAPV), Sacbrood virus (SBV) ...... 47

Table 2.3. Summary statistics from the Bray-Curtis analysis of dissimilarity illustrating the variance and significance in virus prevalence across bee species, season, and year .. 48

Table 2.4. Observed frequency compared with expected frequency of viruses per honey bees and colonies collected from urban landscapes in 2017 and 2018. The number of viruses positively detected (n) and the percentage of infected individual bees and colonies are shown. The total detection of each virus are divided into whether they occurred by themselves (mono-infection) or concurrently with one or more other viruses (co-detection: dual-, triple- & tetra-infection). Expected frequency of co-detection were calculated as

viii

prevalence of first virus x prevalence of second virus. Magnitude (M) illustrates higher magnitude of change in observed co-infections than what is expected by chance ...... 49

Table 2.5. Observed frequency compared with expected frequency of viruses per honey bees and colonies collected from agricultural landscapes in 2017 and 2018. The number of viruses positively detected (n) and the percentage of infected bees and colonies are shown. The total detection of each virus are divided into whether they occurred by themselves (mono-infection) or concurrently with one or more other viruses (co-detection: dual-, triple- & tetra-infection). Expected frequency of co-detection were calculated as prevalence of first virus x prevalence of second virus. Magnitude (M) illustrates higher magnitude of change in observed co-infections than what is expected by chance ...... 50

Table 2.6. The mean number (± s.d.) of virus prevalence of bee species by landscape types, season, and year ...... 51

Table 3.1. Percentage of insects with positive detections of viruses collected from different flowers on early-summer (July-18-2018) from pollinator garden, UNL, Lincoln, NE .....72

Table 3.2. Percentage of insects with positive detections of viruses collected from different flowers on mid-summer (July-31-2018) from pollinator garden, UNL, Lincoln, NE ...... 73

Table 3.3. Percentage of insects with positive detections of viruses collected from different flowers on late-summer (Aug-21-2018) from pollinator garden, UNL, Lincoln, NE ...... 74

Table 3.4. Species identification, sample size, and percentage of DWV, BQCV, IAPV, and SBV infected bees and insects collected from the UNL pollinator garden and apiary on early-summer (July-18-2018) ...... 75

Table 3.5. Species identification, sample size, and percentage of DWV, BQCV, IAPV, and SBV infected bees and insects collected from the UNL pollinator garden and apiary on mid-summer (July-31-2018) ...... 76

Table 3.6. Species identification, sample size, and percentage of DWV, BQCV, IAPV, and SBV infected bees and insects collected from the UNL pollinator garden and apiary on late-summer (Aug-21-2018) ...... 77

Table 3.7. A list of the 12 targeted plant species with short (S), medium (M) and long (L) blooming times and their observed phenology during early, mid, and late summer in 2018. Bolded plant names indicate species that were attractive to foraging honey bees ...... 78

Table 3.8. The variation in virus prevalence on insect group, season times, and, blooming time of flowers from adonis analysis test ...... 79

Chapter 1

Introduction

1.1 The importance of bees

Wild and managed pollinators are essential to agriculture contributing pollination services to numerous crops worth $225 billion US dollars worldwide, annually (Gallai et al. 2009). Bees are the most important pollinators of flowering plants in agricultural and natural areas. Honey bees, Apis mellifera L., are eusocial insects that can form colonies of

40,000 individuals at peak population size and are uniquely adapted to forage across large agricultural fields. They may travel several miles in search of nectar and pollen resources and as generalists, their broad foraging activity assists with the pollination of a wide variety of plants. Managed honey bees contribute more than $15 billion US dollars in added crop value annually via pollination services (Morse & Calderone 2000; Calderon 2012). In contrast, bumble bees, Bombus spp, are primitively eusocial bees living in small annual colonies of 10-400 individuals (Otterstatter 2007). Although significantly smaller in population size compared to honey bee colonies, bumble bees are also valuable agricultural pollinators particularly of cooler climate crops (i.e., blueberries and cranberries) and greenhouse plants, such as tomatoes and peppers (Velthuis & van Doorn 2006). Halictids, or sweat bees, are another primitively eusocial species like bumble bees. They are also efficient pollinators because they exhibit similar foraging traits and appear to be better adapted to agricultural settings (Cameron 1988). Halictids are commonly reported in agricultural settings and can establish ground nests between crop rows [i.e., Lasioglossom

(Dialictus) can be found nesting at high rates between rows of coffee plants in Costa Rica;

Cane 2001].

Although managed bees (honey bees and some bumble bees) are reportedly the most important agricultural pollinators, other studies indicate that wild and unmanaged bees may enhance pollination services and are responsible for an estimated 62% of the flower visitation (Losey et al. 2006; Kremen & Chaplin-Kramer 2007; Winfree et al. 2008).

The value of services (est. $3.07 billion USD annually) provided by unmanaged wild bees to agricultural crops are considered complementary to services provided by manage bees, particularly for crops where honey bees were inefficient pollinators (i.e. alfalfa, blueberry, squash; Tuell et al. 2008). Large-bodied mining bees, Andrena spp. and bumble bees

Bombus spp., are more robust in size and better equipped to carry and deposit more apple pollen than honey bees (Mallinger et al. 2015). Bumble bees (Bombus spp.), orchard mason bees (Osmia spp.), and leaf cutting bees (Megachile spp.) are examples of alternative bee pollinators which may also be more efficient at pollinating some plants. In fact, alternative pollinators may be “managed” and preferred over honey bees for commercial pollination of specific crops. Bumble bees are excellent pollinators of greenhouse plants, such as tomatoes and pepper that require buzz pollination to dislodge pollen grains from the flower, and cooler climate crops (blueberries and cranberries) because they can forage at lower temperatures than honey bees (Potts et al. 2010). Wild bee communities are often overlooked in pollinator protection policies and discussions despite the fact that they are an integral component of sustaining pollinator-dependent crops and shaping natural landscapes.

1.2. Status of bee decline and contributing stress factors

Populations of insect pollinators, including bees and butterflies, have been declining worldwide over the last couple of decades (Potts et al. 2010). The loss of commercial honey bee colonies has averaged ~40% in the United States since 2006, ~25% in Europe since 1985, and ~45% in the United Kingdom since 2010 (Potts et al. 2010;

Allsopp et al. 2014; Traynor et al. 2016). Data on wild bee health is limited, however, bumble bee populations have decreased substantially around the world and their natural distribution range has dramatically decreased as well (Goulson et al. 2015). More specifically, reports have shown continued losses since the 1990s in Bombus occidentalis and B. terricola in North America, and losses of other bumble bee species in Europe (The

United Kingdom and Belgium), South America, China and Japan (Goulson et al. 2015).

1.3. Honey bee stressors

Honey bee declines are the result of several stressors such as poor nutrition, loss of natural habitat, pesticide exposure, pathogens (i.e., bacteria, fungi, protozoans, viruses) and parasites. The most severe stressor to honey bee colonies are the ectoparasitic mites,

Varroa destructor Anderson and Trueman (Arachnida: Acari: Varroidae). Varroa mites feed on the hemolymph and body fluids of adult and developing honey bees. High mite infestation during the pupal stage causes adverse physiological changes (lower hemolymph volume, lipids, and proteins) in infected bees making them ill-adapted for over-wintering

(Amdam et al. 2004). Varroa infection may also impair normal activities, such as poor navigation and foraging performance of infected bees due to alterations in GABA muscle signaling and impaired cognitive functions (Wolf et al. 2014; 2016, Klein et al. 2017).

Additionally, Varroa mites introduce viruses into their hosts when they break the bee’s protective cuticle with their piercing-sucking mouthparts.

Varroa destructor originated from Varroa jacobsoni Oudemans, a close relative native to Eastern Asia, that parasitizes the Asian honey bees, Apis ceranae Fabricius, but shifted hosts to the European honey bees, Apis mellifera (Graystock et al. 2016). After the host shift from A. ceranae to A. mellifera, Varroa destructor mites began to spread to Japan in 1957, Paraguay in 1971, and Brazil in 1972 (Graystock et al. 2016). Varroa destructor was introduced in the US in the late 1980’s but continues to be the most damaging and challenging pest to manage for beekeepers. Despite extensive research on Varroa mite infestation and management, there remains critical knowledge gaps in the capacity of mites to transmit viruses and the transmission of mite-vectored viruses among different bees and other insects.

Many stressors that affect honey bees may also impact wild bee populations causing concern for global bee decline and potential economic losses to insect-dependent agricultural crops. Managed social honey bees and bumble bees maintain close interactions among colony nestmates and are thus more susceptible to multiple suspected drivers as pests and infectious diseases. This includes a series of viral pathogens which are emerging as serious threats to bee health (Singh et al. 2010). Colony health inspection surveys from

2009 to 2015 show escalating bee health problems correlate with increased varroa- mediated viral infections (Traynor et al. 2016; Locke et al. 2014; vanEndgelsdorp et al.

2013; Le Conte et al. 2010). Recent studies document global declines of wild pollinators, such as bumble bees (Bombus spp.), and indicate a potential contributing factor to be

pathogen spillover from commercially managed pollinators (Furst et al. 2014). Honey bees do not live in isolation but mingle with other species of bees and flowering plants in the environment (Singh et al. 2010). Therefore, common viruses found in honey bees may be transmitted to other bees, such as acute bee paralysis virus (ABPV), black queen cell virus

(BQCV), Israeli acute bee paralysis virus (IAPV), Kashmir bee virus (KBV), deformed wing virus (DWV), sacbrood virus (SBV), and chronic bee paralysis virus (CBPV; Chen and Siede 2007; Runckel et al. 2011).

1.4. Viruses in Apis bees, other Hymenopterans, and non-Hymenopteran arthropods

Viruses are frequently found in honey bees, however, little is known about the epidemiology of viruses within colonies, apiaries, and pollinator communities. There also remain critical gaps in knowledge regarding the potential impact of viral infections either alone or in concert with others. More than 30 viruses have been described in the western honey bee (Apis mellifera) and most of these viruses belong to the Picornavirale group that includes Dicistroviruses and Iflaviruses (positive-sense single-stranded RNA viruses (+) ssRNA) and are exemplified by viruses such as: Deformed wing virus (DWV), Black queen cell virus (BQCV), Israeli acute bee paralysis virus (IAPV), Acute bee paralysis virus

(ABVP), Sacbrood virus (SBV), Kashmir bee virus (KBV), Slow bee paralysis virus

(SBPV), Varroa destructor virus1 (VDV-1) and Lake Sinai virus (LSV; Galbraith et al.

2018). Recently, new (+) ssRNA viruses have been identified, such as the Dicistro-like virus (Dicistroviridae), Seco-like virus (Secoviridae), Noda-like virus (Nodaviridae) and a

Tymo-like virus which has similar RNA sequence as other (+) ssRNA viruses within the

Tymoviridae family (Galbraith et al. 2018). Positive detections of (+) ssRNA viruses have

been found around the world and across several different species of bees (Dicistro-like virus in Apis florea from India and A. mellifera from New Zealand; Seco-like virus in A. mellifera from Georgia, Kenya, Panama, Nicaragua, Switzerland, and New Zealand, in

Megachile rotundata from the US and Nicaragua, and in Xylocopa spp. from Kenya; Noda- like virus in A. mellifera and B. impatiens from New Zealand and US; and Tymo-like virus in A. mellifera and B. impatiens from the US). Additionally, two new negative-sense strand viruses [(-) ssRNA], Apis rhabdovirus-1 (ARV-1) and Apis rahbdovirus-2 (ARV-2) first identified in A. mellifera (Remnant et al. 2017; Levin et al. 2017) confirmed that Apis rhabdovirus-1 was able to replicate in bees (A. mellifera, B. impatiens) and bee parasites

(V. destructor mites). ARV-1 and ARV-2 have been found in wild bees, Osmia cornuta, as well (Remnant et al. 2017). Furthermore, a Partiti-like double stranded RNA virus, and another Circo-like circular single stranded DNA (ssDNA) virus, were among the newly identified viruses detected in A. mellifera. The circular Circo-like virus is the first recorded in bees and is related to viruses previously found in dragonflies (Galbraith et al. 2018).

Moreover, other arthropod viruses, such as Nudivirus (Nudiviridae) Oryctes rhinoceros nudivirus and (-) ssRNA viruses, River bee virus (SRBV) and Ganda bee virus (GABV) have been found in Osmia cornuta (Li et al. 2015; Schoonvaere et al. 2016). Similarly, some plant-associated viruses such as Tobacco ringspot virus (TRSV) has been found in the pollen and nectar collected by bees and are capable of replicating in bee hosts, A. mellifera (Li et al. 2014; Galbraith et al. 2018).

While viruses specific to solitary wild bees are typically not found in honey bees, viruses common to honey bees can be found in bumble bees and other wild bees

(Schoonvaere et al. 2016). Viruses common in honey bee apiaries (DWV, BQCV, SBV,

KBV, IAPV) have also been detected in non-Hymenopteran species and other arthropods.

For instance, deformed wing virus (DWV; Iflaviridae) is the most prevalent honey bee virus and has been detected in symptomatic bumble bees with crippled wings (Genersch et al. 2006), mason bees (Osmia cornuta; Mazzei et al. 2014), and other arthropods, such as cockroaches, Blattella germanica, and earwigs, Forficula auricularia. Additionally, Acute bee paralysis virus (ABPV) and Kashmir bee virus (KBV) have been reported in bumble bees used for pollination of greenhouse tomatoes. Sacbrood bee virus (SBV) detections in wild bee samples are quite frequent as well (Dolezal et al. 2016). Chronic bee paralysis virus [CBPV; (-) ssRNA virus], was detected in other hymenopterans such as ants

(Camponotus spp.; Celle et al. 2008). While positive detections of viruses do not infer viral replication or infectivity, some viruses like DWV and IAPV, detected in A. mellifera, B. impatiens, and M. rotundata, are capable of replicating in alternative hosts (Levitt et al.

2013). Although the majority of viruses infecting bees were discovered in honey bees, the prevalence of viruses detected in other insects demonstrates broad host-ranges, and intra- and interspecies transmission routes not fully understood yet (McMenamin et al. 2018;

Dolezal et al. 2016; Mazzei et al. 2014; Levitt et al. 2013; Genersch et al. 2006; Singh et al. 2010; McMahon et al. 2015).

1.5. Pathogen transmission

Pathogens are life forms whose survival is reliant on its ability to replicate and persist on or within another species by effectively destroying a cellular or humoral host barrier which is important to protect themselves from foreign microorganisms (Casadevall

& Pirosfski 1999). Pathogen infections are capable of causing debilitating diseases and

pathogen spillover from reservoir hosts to novel hosts has been identified as a significant driver of bee declines in wild bee communities (Casadevall & Pirosfski 1999; 2001). The host-pathogen interaction is directed by the pathogen life cycle, infectivity, and pathogenicity. Infectivity relates to the ability of a microorganism to replicate in a host tissue while pathogenicity refers to the genetic capacity or dependence upon the relationship between virulence, the number of infective particles (McMahon et al. 2018), and transmission ability and/or route (Casadevall & Pirosfski 2001; Meeus 2018).

Virulence, or the severity of an infection, is dependent on the reproduction rate of the pathogen within the host. Selection pressures against highly virulent pathogens exist due to severe fitness costs and rapid decline in the health of infected hosts, which does not allow sufficient time and opportunity for disease transmission to occur before the host dies.

Pathogen transmission and virulence are highly correlated with one another and must be balanced to provide long-term pathogen survival within host so that both replication and transmission may occur (de Miranda et al. 2010). Therefore, it has been suggested that varroa-induced bee decline is the result of more virulent, fast killing viruses. In contrast, the most prevalent honey bee virus, DWV is considered less virulent, as it does not kill the host bee, but rather causes deformities in highly infected individuals. Asymptomatic bees with latent infections serve as carriers capable of transmitting viruses more widely (de

Miranda et al. 2010).

Pathogen richness and prevalence is shaped in part by differential host susceptibility to pathogens. For example, an optimal host acts as a reservoir for pathogens while alternative hosts may be less suitable for viral replication and or transmission, if hosts die too quickly. Changes to the environment or habitat may impact disease progression by

affecting host susceptibility and or density of potential hosts. Pesticides have been shown to suppress the immune system in exposed bees making them more susceptible to other pathogens (Goulson et al. 2015). Additionally, agricultural intensification and urban growth have reduced and fragmented natural landscapes diminishing floral resources such that remaining habitats concentrate insect visitors and shared resources (Meeus 2018;

Kruess 2000). Small floral patches in landscapes devoid of other resources may be visited by multiple pollinator species thus increasing the likelihood of direct contact with infected individuals or contaminated surfaces (Graystock et al. 2015). Although pathogen transmission through the shared use of flowers has been previously documented for parasites, the role flowers and foraging behavior play on viral transmission and persistence is poorly understood. Additionally, the role other environmental factors, such as warmer winter temperatures and changes in precipitation manifested by climate change, may play in the success and expansion of pathogens and is of growing concern and interest (Meeus

2018).

1.6. Pathogen transmission in honey bees

A major route of pathogen transmission in honey bees is from the ectoparasitic mite, Varroa destructor, which vectors several viruses, including Deformed Wing Virus

(DWV) and Israeli Acute Paralysis Virus (IAPV) (Roberts et al. 2017; Prisco et al. 2011).

Adverse effects of the Varroa-virus complex include a range of physiological, developmental, and behavioral impairments. For instance, deformed wing virus (DWV) has been shown to negatively impact olfactory learning as a result of viral replication of

DWV in the brain. Israeli acute paralysis virus (IAPV) has been shown to impair cognitive

homing and navigation behaviors of infected bees (Han et al. 2015; Klein 2017). And in

Japan, infections with the Kakugo virus is reportedly associated with highly aggressive behavior in infected honey bees (Fujiyuki et al. 2004, 2005).

Multiple viruses have been identified as Varroa-mediated pathogens but infectivity and virulence of viruses are relatively unknown for many, however, when mites are left unmanaged, colonies are expected to die within 1-2 years (Stankus 2008; Traynor et al.

2016).

The transmission of viruses and other pathogens, like Nosema spp., from infected bees to uninfected bees may occur in various ways (Chen et al. 2005). Pathogen transmission can be divided in eusocial bee systems by vertical transmission (between individuals of different generations) and horizontal transmission (between individuals of the same generation) either among bees within the same colony or different colonies (Fries

& Camazine 2001). Horizontal transmission may also occur either among the same bee species (intraspecific) or across different species (interspecific). For instance, intraspecific transmission of deformed wing virus (DWV) among nestmates in honey bees may occur when infected bees consume contaminated food stores or when the parasitic Varroa mite vectors DWV through host feeding. This is supported by the detection of DWV in all life stages of honey bees, as well as in glandular secretions which are used to make brood food and royal jelly that are fed to developing worker and queen bees (Chen et al. 2005; Yue &

Genersch 2005). However, interspecific transmission of DWV to bumble bees is suspected to occur via an oral route from robbing of honey from infected honey bee colonies or by physical contact through the shared use of common foraging sites since Varroa mites are not found in bumble bee colonies (Yue & Genersch 2006). This same situation, has also

been observed between honey bees and Argentine ants (Linepithema humile) that raid infected honey bee colonies (Sebastien et al. 2015).

Bees gather nectar and pollen from flowers to bring back to the colony or their nest.

Flowers are at the center of pollination and are therefore visited multiple times by different pollinators (Steen, & Blom 2010). Viruses and other pathogens can spread between social bees via trophallaxis, or food sharing, consuming contaminated food stores, grooming, or by physical contact of adult bees or pollen from bees’ hair and legs. In fact, DWV found in pollen loads collected directly from uninfected forager bees, suggests that the pollen- associated virus was transferred from infected bees via physical contact at common foraging sites and or possibly from contaminated floral sources (Singh et al. 2010).

Experimental evidence of interspecies transmission of IAPV has also been shown to occur from honey bees to bumble bees via shared use of flowers (Singh et al. 2010). Additionally, the frequent detection of other viruses, such as SBV and CBPV in pollen loads of honey bees and ABPV in pollen loads of both honey bees and bumble bees, further suggests pathogens are likely transmitted within insect communities broadly (Bailey & Gibbs 1964).

Pathogen spillover from managed honey bees to wild bees and other insects is fairly well-documented, however, the route of direct (bee to bee) or indirect (bee to flower/pollen to bee) transmission remains unclear (Mazzei et al. 2014; Galbraith et al. 2018; Levitt et al. 2013). The potential for flowers to serve as a common reservoir and hub for the spread and persistence of viruses among bee communities is also not well understood.

The main goal of my dissertation is to determine and compare viruses detected in managed and unmanaged wild bees then assess the role flowers, landscape, and foraging

activity play on the presence and persistence of viruses. Results will elucidate potential transmission routes, both direct and indirect, that may enable us to make recommendations that increase forage availability or reduce interspecific contact and thus limit viral transmission among pollinators.

My research objectives were to:

1. Examine the presence of viruses among bees from different landscapes (urban

gardens, agricultural fields, and open spaces);

2. Examine the role foraging activity of bees, flowers, and other insects play in viral

transportation and persistence.

In this chapter (Chapter 1), I reviewed the importance of bees and the role in agricultural crop production, report the status of honey bee and wild bee losses, and discuss contributing factors in bee decline. I also summarized the current literature on viruses found in honey bees, wild bees, and other insects and discussed intra- and interspecific transmission of viruses within honey bee colonies and among pollinator communities.

In Chapter 2, my aim was to examine the presence of viruses in managed (Apis mellifera and Bombus impatiens) and unmanaged (B. griseocollis and Halictus ligatus) bees collected from agricultural fields, urban gardens, and open spaces. I tested bees for four of the most commonly detected viruses in honey bee colonies: DWV, IAPV, BQCV, and SBV. Here we report our survey of the prevalence and seasonal variations of those viruses on managed and unmanaged bee species collected in different landscapes, covering a two-year period (2017–2018). Sample collections occurred three times per season, in

early, mid, and late summer from April to September. Presence of viruses in bees were analyzed using RT-PCR and compared across landscape type, season, and bee species. Our results indicate significant differences across bee species and season suggesting species- specific susceptibility to viruses and seasonal effects on infection rates but no differences by landscape type or year were observed.

In Chapter 3, I examined the role flowers and foraging activity of insects play in viral transmission among pollinators. This experiment was completed at the UNL

Pollinator Garden and Outdoor Classroom, Lincoln, NE, which is a large pollinator garden that attracts a variety of wild bees and other pollinators. The garden is adjacent to the UNL

Bee Lab Teaching Apiary, which houses 12–20 honey bee colonies throughout the year. I collected all insects visiting various flowers during their individual peak blooms from July through August, 2018. A total of 12 flowers spanning three different bloom periods (early, mid, and late summer) were used to examine for the presence of DWV, IAPV, BQCV, and

SBV viruses. Honey bees collected on garden flowers were paint-marked and followed back to their hive to assess colony viral loads in nestmates and in-hive pollen. All sample types (bees, flower pedals, pollen collected from flowers, corbicula pollen from foraging honey bees, and hive pollen collected from honey bee colonies) were tested for viruses to assess the viral environment from apiary to the garden. Our results indicate DWV was the most prevalent virus of the four target viruses and detectable in wild bees and other insects.

Prevalence of DWV increased in mid and late season samples and data suggests an association between DWV infection and the likelihood of co-infections with other virus types. Few viruses were detected in flowers and pollen suggesting that viral transmission occurs from direct interaction with infected bees rather than indirectly from contaminated

foods and surfaces. These results support pathogen spillover from honey bees (particularly

DWV and IAPV) into other bee species and insects, however, more research is needed to assess the impact of these viruses on the health of wild bees and other insects.

References cited

Allsopp, M., Tirado, R., Johnston, P., Santillo, D., & Lemmens, P. (2014). Plan bee— living without pesticides moving towards ecological farming. Greenpeace International, Amsterdam, 21–39. Amdam, G. V., Hartfelder, K., Norberg, K., Hagen, A., & Omholt, S. W. (2004). Altered physiology in worker honey bees (Hymenoptera: Apidae) infested with the mite Varroa destructor (Acari: Varroidae): a factor in colony loss during overwintering? Journal of economic entomology, 97(3), 741–747. Bailey, L., & Gibbs, J. (1964). Acute infection of bees with paralysis virus. Journal of insect pathology, 6(4), 395–407. Casadevall, A., & Pirofski, L. A. (2001). Host-pathogen interactions: the attributes of virulence. The Journal of infectious diseases, 184(3), 337–344. Casadevall, A., & Pirofski, L. A. (1999). Host-pathogen interactions: redefining the basic concepts of virulence and pathogenicity. Infection and immunity, 67(8), 3703–3713. Cane, J. H. (2001). Habitat fragmentation and native bees: a premature verdict? Conservation Ecology, 5(1). Cameron, D. G. (1988). Tropical and subtropical pasture legumes. 17. Lablab bean (Lablab purpureus): the major leguminous forage crop. Queensland Agricultural Journal, 114(2), 110–113. Chen, Y. P., & Siede, R. (2007). Honey bee viruses. Advances in virus research, 70, 33– 80. Chen, Y., Evans, J., & Feldlaufer, M. (2006). Horizontal and vertical transmission of viruses in the honey bee, Apis mellifera. Journal of invertebrate pathology, 92(3), 152–159. Celle, O., Blanchard, P., Olivier, V., Schurr, F., Cougoule, N., Faucon, J. P., & Ribière, M. (2008). Detection of Chronic bee paralysis virus (CBPV) genome and its replicative RNA form in various hosts and possible ways of spread. Virus Research, 133(2), 280–284. Dolezal, A. G., Hendrix, S. D., Scavo, N. A., Carrillo-Tripp, J., Harris, M. A., Wheelock, M. J., O’Neal, M. E., & Toth, A. J. (2016). Honey bee viruses in wild bees: viral prevalence, loads, and experimental inoculation. PloS one, 11(11), e0166190. De Miranda, J. R., & Genersch, E. (2010). Deformed wing virus. Journal of invertebrate pathology, 103, 48–61. Di Prisco, G., Pennacchio, F., Caprio, E., Boncristiani Jr, H. F., Evans, J. D., & Chen, Y. (2011). Varroa destructor is an effective vector of Israeli acute paralysis virus in the honeybee, Apis mellifera. Journal of General Virology, 92(1), 151–155. Fürst, M. A., McMahon, D. P., Osborne, J. L., Paxton, R. J., & Brown, M. J. F. (2014). Disease associations between honeybees and bumblebees as a threat to wild pollinators. Nature, 506(7488), 364. Fries, I., & Camazine, S. (2001). Implications of horizontal and vertical pathogen transmission for honey bee epidemiology. Apidologie, 32(3), 199–214.

Fujiyuki, T., Takeuchi, H., Ono, M., Ohka, S., Sasaki, T., Nomoto, A., & Kubo, T. (2004). Novel insect picorna-like virus identified in the brains of aggressive worker honeybees. Journal of virology, 78(3), 1093–1100. Fujiyuki, T., Takeuchi, H., Ono, M., Ohka, S., Sasaki, T., Nomoto, A., & Kubo, T. (2005). Kakugo virus from brains of aggressive worker honeybees. Advances in virus research, 65, 1–27. Goulson, D., Nicholls, E., Botías, C., & Rotheray, E. L. (2015). Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science, 347(6229), 1255957. Genersch, E., Yue, C., Fries, I., & de Miranda, J. R. (2006). Detection of deformed wing virus, a honey bee viral pathogen, in bumble bees (Bombus terrestris and Bombus pascuorum) with wing deformities. Journal of invertebrate pathology, 91(1), 61–63. Gallai, N., Salles, J. M., Settele, J., & Vaissière, B. E. (2009). Economic valuation of the vulnerability of world agriculture confronted with pollinator decline. Ecological economics, 68(3), 810–821. Graystock, P., Goulson, D., & Hughes, W. O. (2015). Parasites in bloom: flowers aid dispersal and transmission of pollinator parasites within and between bee species. Proc. R. Soc. B, 282(1813), 20151371. Goblirsch, M. (2018). Nosema ceranae disease of the honey bee (Apis mellifera). Apidologie, 49(1), 131–150. Han, Y., van Oers, M. M., van Houte, S., & Ros, V. I. (2015). Virus-induced behavioural changes in insects. In Host Manipulations by Parasites and Viruses, 149–174. Springer, Cham. Kremen, C., & Chaplin-Kramer, R. (2007). Insects as providers of ecosystem services: crop pollination and pest control. In Insect conservation biology: proceedings of the royal entomological society’s 23rd symposium, 349–382. CABI Publishing Wallingford, UK. Klein, S., Cabirol, A., Devaud, J. M., Barron, A. B., & Lihoreau, M. (2017). Why bees are so vulnerable to environmental stressors. Trends in Ecology & Evolution, 32(4), 268–278. Kruess, A., & Tscharntke, T. (2000). Species richness and parasitism in a fragmented landscape: experiments and field studies with insects on Vicia sepium. Oecologia, 122(1), 129–137. Losey, J. E., & Vaughan M. (2006). The economic value of ecological services provided by insects. AIBS Bulletin, 56(4), 311–323. Le Conte, Y., Ellis, M., & Ritter, W. 2010. Varroa mites and honey bee health: can Varroa explain part of the colony losses? Apidologie 41(3), 353–363. Levitt, A. L., Singh, R., Cox-Foster, D. L., Rajotte, E., Hoover, K., Ostiguy, N., & Holmes, E. C. (2013). Cross-species transmission of honey bee viruses in associated arthropods. Virus research, 176(1–2), 232–240. Locke, B., Forsgren, E., & de Miranda, J. R. (2014). Increased tolerance and resistance to virus infections: a possible factor in the survival of Varroa destructor- resistant honey bees (Apis mellifera). PloS one, 9(6), e99998.

Levin, S., Galbraith, D., Sela, N., Erez, T., Grozinger, C. M., & Chejanovsky, N. (2017). Presence of Apis rhabdovirus-1 in populations of pollinators and their parasites from two continents. Frontiers in Microbiology, 8, 2482. Li, C. X., Shi, M., Tian, J. H., Lin, X. D., Kang, Y. J., Chen, L. J., Qin, X. C., Xu, J., Holmes, E. C., & Zhang, Y. Z. (2015). Unprecedented genomic diversity of RNA viruses in arthropods reveals the ancestry of negative-sense RNA viruses. elife, 4, e05378. Li, J. L., Cornman, R. S., Evans, J. D., Pettis, J. S., Zhao, Y., Murphy, C., Peng, W. J., Wu, J., Hamilton, M., Boncristiani, H. F., Zhou, L., Hammond, J., & Chen, Y. P. (2014). Systemic Spread and Propagation of a Plant-Pathogenic Virus in European Honeybees, Apis mellifera. MBio, 5(1), e00898–13. McMahon, D. P., Wilfert, L., Paxton, R. J., & Brown, M. J. (2018). Emerging viruses in bees: from molecules to ecology. Advances in virus research, 101, 251–291. Meeus, I., Pisman, M., Smagghe, G., & Piot, N. (2018). Interaction effects of different drivers of wild bee decline and their influence on host-pathogen dynamics. Current opinion in insect science, 26, 136-141. Mallinger, R. E., & Gratton, C. (2015). Species richness of wild bees, but not the use of managed honeybees, increases fruit set of a pollinator-dependent crop. Journal of Applied Ecology, 52(2), 323–330. McMenamin, A. J., & Flenniken, M. L. (2018). Recently identified bee viruses and their impact on bee pollinators. Current opinion in insect science. 26, 120–129. Morse, R. A. & Calderone, N. W. (2000). The value of honey bee pollination in the United States. Bee Culture, 128(18), 1–15. Mazzei, M., Carrozza, M. L., Luisi, E., Forzan, M., Giusti, M., Sagona, S., Tolari, F., & Felicioli, A. (2014). Infectivity of DWV associated to flower pollen: experimental evidence of a horizontal transmission route. PloS one, 9(11), e113448. McMahon, D. P., Fürst, M. A., Caspar, J., Theodorou, P., Brown, M. J., & Paxton, R. J. (2015). A sting in the spit: widespread cross-infection of multiple RNA viruses across wild and managed bees. Journal of Animal Ecology, 84(3), 615–624. Otterstatter, M. C., & Thomson, J. D. (2007). Contact networks and transmission of an intestinal pathogen in bumble bee (Bombus impatiens) colonies. Oecologia, 154(2), 411–421. Potts, S. G., Biesmeijer, J. C., Kremen, C., Neumann, P., Schweiger, O., & Kunin, W. E. (2010). Global pollinator declines: trends, impacts and drivers. Trends in ecology & evolution, 25(6), 345–353. Roberts, J. M., Anderson, D. L., & Durr, P. A. (2017). Absence of deformed wing virus and Varroa destructor in Australia provides unique perspectives on honeybee viral landscapes and colony losses. Scientific Reports, 7(1), 6925. Runckel, C., Flenniken, M. L., Engel, J. C., Ruby, J. G., Ganem, D., Andino, R., & DeRisi, J. L. (2011). Temporal analysis of the honey bee microbiome reveals four novel viruses and seasonal prevalence of known viruses, Nosema, and Crithidia. PloS one, 6(6): e20656. Remnant, E. J., Shi, M., Buchmann, G., Blacquière, T., Holmes, E. C., Beekman, M., & Ashe, A. (2017). A diverse range of novel RNA viruses in geographically distinct honey bee populations. Journal of virology, JVI-00158.

Singh, R., Levitt, A. L., Rajotte, E. G., Holmes, E. C., Ostiguy, N., vanEngelsdorp, D., lan Lipkin, W., dePamphilis, C. W., Toth, A. L., & Cox-Foster, D. L. (2010). RNA viruses in hymenopteran pollinators: evidence of inter-taxa virus transmission via pollen and potential impact on non-Apis hymenopteran species. PloS one, 5(12), e14357. Stankus, T. (2008). A review and bibliography of the literature of honey bee Colony Collapse Disorder: a poorly understood epidemic that clearly threatens the successful pollination of billions of dollars of crops in America. Journal of Agricultural & Food Information, 9(2), 115–143. Schoonvaere, K., De Smet, L., Smagghe, G., Vierstraete, A., Braeckman, B. P., & de Graaf, D. C. (2016). Unbiased RNA shotgun metagenomics in social and solitary wild bees detects associations with eukaryote parasites and new viruses. PloS one, 11(12), e0168456. Sebastien, A., Lester, P. J., Hall, R. J., Wang, J., Moore, N. E., & Gruber, M. A. M. (2015). Invasive ants carry novel viruses in their new range and form reservoirs for a honeybee pathogen. Biology letters, 11(9), 20150610. Steen, J. J. M. VAN DER, & Blom, M. P. K. (2010). Pathogen transmission in insect pollinators 6, 395–407. Traynor, K. S., Rennich, K., Forsgren, E., Rose, R., Pettis, J., Kunkel, G., Madella, S., Evans J., Lopez, D., & vanEngelsdorp, D. (2016). Multiyear survey targeting disease incidence in US honey bees. Apidologie, 47(3), 325–347. Tuell, J. K., Fiedler, A. K., Landis, D., & Isaacs, R. (2008). Visitation by wild and managed bees (Hymenoptera: Apoidea) to eastern US native plants for use in conservation programs. Environmental entomology, 37(3), 707–718. Velthuis, H. H. & Van Doorn, A. (2006). A century of advances in bumblebee domestication and the economic and environmental aspects of its commercialization for pollination. Apidologie, 37(4), 421–451. Van der Sluijs, J. P., Simon-Delso, N., Goulson, D., Maxim, L., Bonmatin, J. M., & Belzunces, L. P. (2013). Neonicotinoids, bee disorders and the sustainability of pollinator services. Current opinion in environmental sustainability, 5(3–4), 293– 305. Winfree, R., Williams, N. M., Gaines, H., Ascher, J. S., & Kremen, C. (2008). Wild bee pollinators provide the majority of crop visitation across land-use gradients in New Jersey and Pennsylvania, USA. Journal of Applied Ecology, 45(3), 793–802. Wolf, S., McMahon, D. P., Lim, K. S., Pull, C. D., Clark, S. J., Paxton, R. J., & Osborne, J. L. (2014). So near and yet so far: harmonic radar reveals reduced homing ability of Nosema infected honeybees. PloS one, 9(8), e103989. Wolf, S., Nicholls, E., Reynolds, A. M., Wells, P., Lim, K. S., Paxton, R. J., & Osborne, J. L. (2016). Optimal search patterns in honeybee orientation flights are robust against emerging infectious diseases. Scientific reports, 6, 32612. Yue, C., & Genersch, E. (2005). RT-PCR analysis of Deformed wing virus in honeybees (Apis mellifera) and mites (Varroa destructor). Journal of General Virology, 86(12), 3419–3424.

Chapter 2

An examination of viruses in four different species of bees collected from agricultural, urban, and natural landscapes

2.1. Abstract

Managed honey bees and wild bees provide critical ecological services that shape and sustain natural, agricultural, and urban landscapes. In recent years, declines in bee populations have highlighted the importance of the pollination services they provide and the need for more research into the reasons for global bee losses. Several stressors cause declining populations of managed and wild bee species such as habitat degradation, pesticide exposure, and pathogens. Viruses, which have been implicated as a key stressor, are able to infect a wide range of species and can be transmitted both intra-and inter- specifically from infected bee species to uninfected bee species via vertical (among individuals of different generations) and/or horizontal (among individuals from the same generation) transmission. To explore how viruses spread both intra- and inter-specifically within a community, we examined the impact of management, landscape type, and bee species on the transmission of four common viruses (DWV, IAPV, BQCV, and SBV) in

Nebraska. Our results indicate that the prevalence of viruses is affected by bee species, virus type, and season but not by landscape and year. The high prevalence of DWV detected across bee species and seasons indicate higher risk of interspecific transmission of DWV. However, IAPV was predominately detected in Halictus ligatus and in late season collections which may suggest species-specific susceptibility and seasonal trends in infection rates associated with different virus types.

2.2. Introduction

There are roughly 20,000 extant species of bees worldwide and approximately

3,600 species of bees in North American that aid in the pollination of our agricultural crops and native flora (Waldbauer 2017; McMenamin et al. 2018). Domesticated honey bees

(Apis mellifera L.) play vital roles as the principal providers of food crop pollination, contributing over $15 billion USD in added value (Waldbauer 2017). In addition to the services provided by commercially managed honey bees, other species of social and solitary bees are critical for the pollination of ecologically important plants in natural, agricultural, and urban landscapes (McMenamin et al. 2018; Waldbauer 2017). Many of these wild, unmanaged bees, however, are increasingly being utilized commercially as alternative pollinators for certain crops and/or under more specific environmental conditions. For example, Bombus impatiens Cresson, is often used for the pollination of greenhouse crops [tomatoes (Lycopersicon esculentum Mill.; Palma et al. 2008), and sweet peppers (Capsicum annuum L. var. grossum cv. Superset; Meisels et al. 1997)] because bumble bee colonies are smaller, annual, and adapt to indoor settings far better than honey bees. Bumble bees are also used to pollinate cooler climate crops [blueberries (Vaccinium corymbosum L.; Macfarlane 1992), cranberries (Vaccinium macrocarpon Ait; Mackenzie

1994)] due to their ability to forage under lower temperatures. Bumble bees pollinate some plants more efficiently through “buzz” pollination, or the ability to sonicate flowers by vibrating thoracic muscles while grasping onto flowers. Sonication causes pollen grains

secured in plant anthers to dehisce and attach to bee hairs, which more effectively collects pollen than active pollen collection by honey bees (Velthuis & van Doorn 2006).

Recent studies indicate declining populations of managed and wild bee species over the past century (Youngsteadt et al. 2015; Hatfield et al. 2012). Common factors identified as contributors to both managed and wild bee declines include habitat degradation, pesticide exposure, and pathogens (Potts et al. 2010). Agricultural intensification and urban growth has dramatically reduced the amount of natural landscapes and diminished floral abundance and diversity, which are critical for the long-term establishment of healthy pollinator communities. With increased crop production and urbanization comes increased risk of pesticide exposure on bees, when growers and homeowners treat for unwanted pests, pathogens, and weeds. Pesticide exposure can have lethal consequences or cause various adverse sub-lethal effects on bees including: impaired cognitive behaviors, disrupted foraging activity, suppression of the immune system, and increased susceptibility to other pests and diseases (Klein et al. 2017). While there exists extensive literature on pests and pathogens that affect honey bees, there are knowledge gaps in our understanding of pathogen transmission within honey bee colonies and across other species of bees.

Viruses have a broad host range and a number of viruses can exist in their host in a latent form or be asymptomatic making monitoring efforts difficult. More than 30 distinct viruses have been identified in honey bees thus far, but this is an evolving area of science that continues to discover new strains (McMenamin et al. 2018). It is well-documented that honey bee diseases can be transmitted to individual nestmates and within colonies as well as across different bee species, and other insects (Evans & Spivak 2010). Vertical

transmission (from adults to offspring) and horizontal transmission (between nestmates) routes occur either directly through contact with infected individuals or indirectly through contaminated foods, which allows viruses to persist in colonies. Horizontal transmission may occur among nest mates of honey bees having interaction with contaminated foods

(intraspecific transmission) or/and may occur by physical contact between different bee species during foraging at common site (interspecific transmission; Manley et al. 2015;

Evans & Schwarz 2011). Long-term persistence of viruses increases the risk of pathogen spread from infected to uninfected individuals or colonies. The most commonly detected honey bee virus, deformed wing virus (DWV), is vectored by a major ectoparasitic mite

(Varroa destructor) of honey bees, however, DWV is found in both managed bumble bees and other wild bees (Osmia spp., Augochlora spp., and Xylocopa spp.), despite the absence of Varroa mites (Tehel et al. 2016). Bumble bees and wasps are common robbers of weak honey bee colonies and may serve as alternative hosts for DWV as they come into direct contact with infected honey bees or indirectly through contaminated foods. (McMenamin

& Flenniken 2018; Singh et al. 2010). While many bee viruses can only replicate in suitable hosts, some bee viruses, such as Sacbrood virus (SBV) and Black queen cell virus (BQCV), are also capable of replicating in mite vectors (Varroa spp. and Tropilaelaps spp.; de

Miranda et al. 2013).

Nebraska is an important agricultural state particularly for the production of corn and soybeans. In fact, crop coverage in Nebraska has increased from 8.5 to 9.4 million acres in the last ten years. The growth of agricultural production in Nebraska and across the nation has led to decreasing availability of habitat and increasing agrochemical exposure for pollinators (e.g., birds, bees and butterflies) (NRCC 2007; Mineau &

Whiteside 2013; Sauer et al. 2000; vanEngelsdorp et al. 2009). However, studies showed that crop field margins may be utilized to provide important habitat and promote increased insect diversity (including natural predators of crop pests) and food sources for wildlife

(Pierce et al. 2008). Some crops (i.e. alfalfa, vetch, sweet clover, sunflower) grown in

Nebraska depend on bees for pollination but this is minor in comparison to the number of wind-pollinated crops (corn, soybeans, sorghum, wheat) grown in the state. And while

97.2% of Nebraska is privately-owned, there are a number of biologically unique landscapes protected to conserve species identified by the Nebraska Game and Parks

Service as “at-risk” or “threatened” which includes several insects and bees (Schneider et al. 2005). Therefore, research on drivers of bee loss are critically important for identifying potential bee and land management practices that may promote bee communities and mitigate further bee declines. Greater insight into which viruses are present and how they are transmitted both intra- and inter-specifically within the pollinator community will help elucidate the impact of management, landscape type, and bee species on the transmission of viruses. Here we present a descriptive survey of honey bee viruses (DWV, BQCV,

IAPV, and SBV) found in managed (A. mellifera and B. impatiens) and unmanaged (B. griseocollis and H. ligatus) bee species collected from different landscapes (agricultural, urban, and natural or open spaces) across the season. We hypothesized that managed bees would have more frequent positive detections of viruses due to greater densities of bees in managed apiaries. Likewise, we hypothesized landscapes with more limited floral resources would lead to more concentrated foraging sites and co-mingling across species thus driving higher rates of interspecific transmission of viruses. Results of this study will be used to improve our understanding of interspecific transmission of viruses from honey

bees, which may inform bee and landscape management recommendations to mitigate direct contact of infected bees with wild populations to reduce pathogen spread and infectivity.

2.3. Materials & Methods

2.3.1. Target bee species and site selection

Four generalist species of bees were selected for this study because of the relative ease of finding them in all landscapes across the season. Targeted bee species included, honey bees [Apis mellifera (Apidae)), bumble bees (Bombus impatiens and B. griseocollis

(Apidae)), and sweat bees (Halictus ligatus (Halictidae)]. Collections of bees occurred at

10 sites located in agricultural, urban, and natural landscapes from April through

September over two years (2017 and 2018). Agricultural field sites consisted of two privately-owned farms (Dixi Farm located in Waverly and Goat Farm located in Lincoln,

NE) that house University of Nebraska-Lincoln (UNL) honey bee colonies and pollinator habitat plots (i.e. cover crops such as clover and alfalfa) established in field margins of research corn and soybean fields at the UNL Eastern Nebraska Research and Extension

Center (ENREC) in Mead, NE. Foraging honey bees and wild bees were collected at each site either within pollinator habitats or in field margins absent pollinator plantings.

Urban sites included four public gardens within two major cities. The UNL

Pollinator Garden and Outdoor Classroom located on East Campus, the Rose Garden, and the Sunken Garden are all located within the city of Lincoln, while Lauritzen Gardens is located in Omaha, NE. These sites all contain pollinator-friendly plantings of both native and cultivar species and ranged in size from <1 acre to 100+ acres. Different garden spaces

provided varying resources and habitats for wildlife. The carry capacity for pollinator establishment in gardens is dependent on the plant types, phenology of flowers, and management of gardens. The Rose Garden, for example, is less suitable for pollinators due to the perennial ornamental roses that are highly cultivated for ornate petals but offer few floral nectar or pollen for bees.

The natural area or open sites include public parks/conservation areas such as the

Lincoln Prairie Corridor which spans from Pioneers Park (tallgrass prairie ecosystem), to the Spring Creek Audubon Center (shortgrass prairie ecosystem) and public roadsides

(Union City, NE). Open spaces also vary greatly in the quality of pollinator habitat they provide. Some sites were newly-seeded (roadside plots) and recently restored (prairie), while other areas have remained relatively undisturbed include areas with older (5+ years) conservation reserve program (CRP) plots and unmanaged prairie.

2.3.2. Collection method of bees

Apis mellifera, B. impatiens, B. griseocollis, and H. ligatus were collected using nets and hand vial trapping. Ten individual bees of each species were collected from each landscape type from May through September in 2017 and 2018. Collections occurred between 8am–12pm in early, mid and late summer. In nets, it is possible that physical contact among bees may result in some surface-level cross contamination, although internal cross-contamination is unlikely (Dolezal & Hendrix et al. 2016). To reduce potential for cross contamination, target bees were separated immediately after collection in individual vials and stored on ice (< 3 hours) in the field until samples could be returned to the laboratory. Bees were stored in a -20 ̊C freezer prior to identification and processing.

Identification of bees were confirmed using three identification guides (Ascher & Pickering

2011; Arduser 2018; Williams et al. 2014). After identification, bees were put into 1.5 ml centrifuged tube and stored at -80 ̊C until they are processed for virus identification using

RT-PCR.

2.3.3. Honey bee colonies and apiaries

Twenty-six honey bee (Apis mellifera) colonies were set up at the UNL Pollinator

Garden between May–June 2017 (Early Spring). Seven of the twenty-six honey bee colonies were moved to the UNL ENREC agricultural field site location in July 2017 (mid- summer). Four additional colonies, were moved to two privately-owned agricultural farms in spring of 2017. The Dixi Farm located in Waverly, NE was a property growing roughly

5-acres of alfalfa and was surrounded by adjacent corn and soy fields. The second property

(Goat Farm) was a 30-acre vegetable and goat farm located in Lincoln, NE. Ten individual honey bees were collected from the hive entrance at each of the four apiary sites (UNL

Pollinator Garden, ENREC, Dixi Farm, and Goat Farm) in early spring, mid-summer, and late summer. Due to colony losses and potential pesticide kills, honey bees were not collected from ENREC and the Goat Farm in late summer of 2017.

In 2018, colonies that successfully over-wintered in UNL Pollinator Garden and

Dixi Farm were resampled. Colonies from the Goat Farm did not survive and were replaced with newly established colonies. Colonies that died at ENREC were not replace due to concerns over the previous year’s pesticide kill. Therefore, in 2018, only three of the four apiaries were resampled.

2.3.4. Bee tissue dissection

Ten adult bees of each target species (A. mellifera, B. impatiens, B. griseocollis, H. ligatus) were individually divided into three body regions (head, thorax, and abdomen).

The wings, legs, head, and abdomen of bees were removed with scissors and forceps to prevent a false negative PCR result for viruses due to the inhibitory substances in the compound eyes and guts of honey bees and insects (Boncristiani et al. 2011). The thoracic region of each bee was individually placed into sterile microcentrifuge tubes (1.5 ml) while the heads and abdomens were placed together into different microcentrifuge tubes. All samples were stored at -80 ̊C until they were processed for RNA extraction.

2.3.5. Sample collection of pollen

To examine the role of pollen plays in interspecific transmission of viruses, pollen loads collected by foraging honey bees were tested for the presence of viruses. Honey bee- collected pollen loads (50–100 mg) were obtained using pollen traps which require returning bees to squeeze through a mesh screen that dislodges pollen off their pollen basket or corbicula (Aparicio et al. 1999). Pollen traps were placed on three hives (located at the UNL Pollinator Garden) and activated for 1-2 days per hives in early spring, mid- summer, and late-summer. Fresh pollen collected from flowers visited by bees and the pollen on the legs and hairs of actively foraging bees were collected using paint brushes and analyzed for viruses.

2.3.6. Total RNA extraction from bees and pollen

Dissected bee thoraces and pollen samples were process to extract total RNA and assess for the presence of viral RNA. Bees were individually processed to improve detection of viruses in homogenate samples. Each sample was transferred to nuclease-free centrifuge tubes (1.5 ml). Resistant 316 stainless steel ball (6.35 mm diameter) and TRI

Reagent (Invitrogen; ml per 50–100 mg of tissue) were put into sample tubes to homogenize using the SPEX SamplePrep 2010 Geno/Grinder® at 1300 strokes for 1 min.

The liquid was removed into a fresh centrifuge tube and allowed to settle for 5 min at room temperature. After settling, chloroform (0.2 ml per ml of TRIzol Reagent) was added and the tube was vigorously vortexed for 15 secs to mix. Samples were then left at room temperature for 15 min and centrifuged at 12,000 x g for 15 min. At this point, samples separated into three layers and the aqueous phase was transferred into a fresh tube.

Isopropanol (0.5 ml per ml of TRIzol Reagent used) was added and gently mixed to the aqueous phase. Sample tubes were stored over night at -20 °C and then centrifuged at

12,000 x g for 10 min. After this process, a small barely visible pellet containing RNA would form at base of each tube. RNA pellets were washed by adding 1 ml 75% ethanol and then centrifuging the tube at 7,500 x g for 5 min. The ethanol was poured off without touching the pellet at base of tubes and the pellet was allowed to air-dry. RNA samples were further dissolved in DEPC-treated water in the presence of Ribonuclease Inhibitor

(Invitrogen, Carlsbad, CA) and stored at -80 °C for further analysis (Chen 2004). The concentration of extracted RNA was estimated by measuring the absorbance of aliquots at

260nm of an aliquot of the final preparation at a Nanodrop 2000c (Thermo Scientific).

Then, RT-PCR was used to detect the presence of target viruses.

2.3.7. RT-PCR method

RT-PCR analysis were applied to screen for the presence of DWV, IABPV, BQCV, and SBV in the samples. Specific publicly available primer pairs were used for viruses which were as follows: DWV-F: 5’-atcagcgcttagtggaggaa-3’, DWV-R: 5’- tcgacaattttcggacatca-3’, IABPV-F: 5′-ttatgtgtccagagactgtatcca-3’, IABPV-R: 5′- gctcctattgctcggtttttcggt-3′, BQCV-F: 5’-tggtcagctcccactaccttaaac-3’, BQCV-R: 5’- gcaacaagaagaaacgtaaaccac-3’, and SBV-F: 5’-gctgaggtaggatctttgcgt-3’, SBV-R: 5’- tcatcatcttcaccatccga-3’ (Chen 2005; Table 1).

2.3.8. Target virus selection and assessment

Honey bees collected from colonies in 2016 were tested for the presence of IAPV,

BQCV, DWV, KBV, SBV-1 and SBV-2 separately by the uniplex RT-PCR technique

(Chen 2004). The Access Quick RT-PCR system (Promega, Madison, WI) was used according to the manufacturer’s instructions. The reaction mixture contained: 25 µl of

Access Quick TM Master Mix, 0.5 µl of Upstream Primer, 0.5 µl of Downstream Primer,

2.5 µl of RNA Template, 1l of AMV Reverse Transcriptase, and 500 ng total RNA in a total volume of 25 µl. The thermal cycling profiles were as follows: one cycle at 48 °C for

45 minutes for reverse transcription followed by 95°C for 2min; up to 40 cycles at 95°C for 30 sec., 55 °C for 1 min, and 68 °C for 2 min; 68 °C for 7 min. Negative and positive control samples (previously identified) were included in each RT-PCR trial (Chen 2004).

Amplification products were analyzed together with 100 bp ladder for size determination of PCR products through electrophoresis (1% agarose gel and 0.5 ug/ml ethidium bromide)

and UV trans illumination (Chen 2004) was used for visualization.

Four out of six viruses were confirmed in 2016 honey bee samples and became the target viruses (DWV, IAPV, BQCV, SBV) screened for in 2017–2018 samples. Although these viruses are common in honey bees, they may be detected in another species. One or more viruses may be detected within a sample and may be defined as a mono-, dual-, triple, or tetra-infection. To develop an assay that allows simultaneous detection of different viruses in a single reaction, multiplex RT-PCR were used on samples of adult bee identified with infections of four viruses using uni plex RT-PCR.

The multiplex Reverse Transcription-PCR (RT-PCR) protocols adapted from Chen et al. (2004) were performed to determine whether bee and pollen samples contained the presence of DWV, IAPV, BQCV, and or SBV viral RNA by using a one-step RT-PCR kit

(Promega, Madison, WI). The RT-PCR kit contained 1 x AMV/Tfl reaction buffer, 4 mM

MgSO4, 0.6 mM dNTP, 0.4 unit AMV reverse transcriptase, 0.4 unit Tfl DNA polymerase,

2 µg total RNA, 0.6 µM of each specific primer for DWV, IAPV, BQCV, and SBV for a total volume of 50 µl. The cycling conditions consisted of one cycle at 48 °C for 45 min for reverse transcription followed by one cycle at 94 °C for 2 min, 20 cycles of 94 °C for

30 s, 58 °C for 1 min, and 68 °C for 1 min, and 20 cycles of 94 °C for 30 s, 52 °C for 1 min and 68 °C for 1 min followed by final elongation step at 68 °C for 10 min. PCR products were separated by electrophoresis in 1.8% agarose gel and visualized under UV light.

2.3.9. Statistical analysis

2.3.9.1. Proportion of infected bees across different landscapes

The proportion of individual bees (A, mellifera, B. impatiens, B. griseocollis, H. ligatus) with detectable levels of viruses (BQCV, DWV, IAPV, and SBV) were compared across different landscape types (urban, agricultural, and open spaces) using Chi-Square test and

Fisher’s Exact test with significance denoted at alpha = 0.05. Fisher’s Exact test utilized to analyze contingency tables that account for small sample sizes and zero inflated responses in observed data. Fisher’s Exact significance tests were performed using SAS or R version

3.5.1 (Urbanek 2018).

2.3.9.2. Distance-based redundancy analysis of virus type

To assess the relationship between virus types, bee host species, and season, a distance- based redundancy analysis (dbRDA) was performed (Pavoine et al. 2004). Differences among species (dissimilarity matrix) and the species distribution communities

(presence/absence matrix) with a zero-adjusted Bray-Curtis dissimilarity metric were analyzed (Clarke et al. 2006). The vegan package in R (version 3.5.1) was used for the analysis of dissimilarity (Oksanen et al. 2011). The constrained analysis of principal coordinates (‘capscale’) was performed to assess dissimilarities among virus types and other variables (landscape, host, season, and year) (Anderson and Willis 2003). The model for constrained ordination methods (capscale) was built by applying ‘ordistep’ function which allows forward, backward, and stepwise model selection using permutation tests

(Blanchet et al. 2008). Negative eigenvalues were transformed to positive eigenvalues

because capscale discards the imaginary dimensions where negative eigenvalues exist and only base models positive eigenvalues in real dimensional space (Oksanen et al. 2011).

Lastly, the ‘adonis’ function was applied to analyze the variance in distance matrices

(Dixon 2003).

2.3.9.3. Mixed virus infections in honey bee colonies

To assess the co-infection in different landscapes at honey bee apiaries, the expected frequency of co-detection of viruses were calculated to be compare with the observed frequency of co-detection of viruses per honey bees and colonies collected from agricultural and urban landscapes in 2017 and 2018. The total detections of each virus were divided into whether they occurred by themselves (mono-infection) or concurrently with one or more other viruses (co-detection: dual-, triple- & tetra-infection). The expected frequencies of co-detection were calculated as prevalence of first virus x prevalence of second virus. Magnitude (M) was calculated as observed frequency of co-detection / expected frequency of co-detection. Magnitude (M) illustrates higher magnitude of fold change in observed co-infections than what is expected by chance.

2.4. Result

2.4.1. Virus prevalence in foraging bees collected from different landscapes

A total of 1,643 bees (1180 A. mellifera, 154 B. impatiens, 161 B. griseocollis, and

148 H. ligatus) were collected from agriculture, urban, and open sites during the summers of 2017 and 2018. Bees were analyzed for the presence of DWV, IAPV, BQCV, and SBV

and compared across landscape types and season. All four viruses were detected in honey bees (A. mellifera) collected from agriculture sites, particularly from late summer collections. However, DWV and IAPV were detected mostly in sweat bees (H. ligatus) collected from urban and open sites in both early and late season collections (Figure 2.1).

The frequency of positive detections among the four target bee species were separately analyzed by landscape type and across season and year.

Results for bees collected in agricultural sites indicate no effect by year but a significant correlation between the prevalence of DWV- and SBV-infected foragers and late season collections for both years (Fisher Exact test; p = 0.02 and p = 0.04, respectively)

(Table 2.2). Bees collected from urban sites had more detections of DWV and IAPV in both early and late summer samples particularly in 2018 (p = <0.0001) (Figure 2.1, Table

2.2).

Within natural or open sites, DWV detections were significantly different across wild bees (no honey bees caught), but only in early season samples in 2018 [DWV p =

0.0003 (early) and p = 0.0183 (late)]. IAPV detections were also significantly different among wild bees in 2018 but differences were observed for early and late season samples

(p = 0.0183 and p = 0.0012, respectively) (Table 2.2). BQCV and SBV detections were low and showed little differences among bee species, season, or landscape type. Positive detections of viruses from bees collected in natural landscapes or open spaces were similar to detection rates in bees from urban sites, and yielded more positive detections of DWV and IAPV and few detections of BQCV and SBV. Higher detections of DWV and IAPV in sweat bees, H. ligatus, accounted for the significant differences observed across bee

species but only in 2018 (p = 0.0012) (Figure 2.1).

To assess the potential role of bee management, bee species were further grouped by whether they were actively “managed” or are “unmanaged” wild species. Honey bees

(A. mellifera) and one bumble bee species (B. impatiens) are commercially managed for pollination and or honey production. Managed bee colonies are typically stocked at higher densities then natural densities of wild species (B. griseocollis and H. ligatus) and thus may play a greater role of viral persistence and transmission. Comparisons between managed and unmanaged bee groups collected from three different landscapes, indicate significant differences in the number of positive detections of DWV in managed compared to unmanaged bees but only from urban sites in 2018 (early and late season) (p = <0.001)

(Figure 2.2, Table 2.2). Differences were also observed among managed and unmanaged bees with positive IAPV detections in early (open and urban) and late season (urban) samples collected in 2018 (p = 0.0012, p < 0.0001 for early and late season, respectively)

(Figure 2.2, Table 2.2). No significant differences were found between managed and unmanaged bees collected in agriculture sites (p = 0.05) (Figure 2.2) and for BQCV and

SBV detections.

2.4.2. Dissimilarities among bee species, virus type, and season

The occurrence of viruses in each sample relative to all other samples was visualized (Figure 2.3). Results indicated that bee species (R2= 0.089, p < 0.001) and season

(R2= 0.036, p < 0.001) were significant main factors that accounted for the variance observed (Figures 2.3, 2.4 and Table 2.3). Landscape type and year, however, were not factors in viral prevalence (Table 2.3, p =0.145 and p = 0.1, respectively).

Relationships between virus types showed DWV was the most prevalent and commonly detected virus across all bee species, landscape types, and seasons. The high prevalence of DWV in bees positively correlated with IAPV, but not with BQCV and SBV

(Figures 2.4, 2.5). Few viruses were detected in pollen samples collected from the legs of foraging honey bees (corbiculae pollen), in-hive pollen stores, and pollen from the anthers of flowers (Fig 2.3). And in general, the viral prevalence in bees increased from early to late season collections in one or both years (Figures 2.1, 2.2, 2.4) that the viral prevalence were 0.08 ± 0.27, 0.02 ± 0.15, 0.004 ± 0.06, and 0.007 ± 0.08 in early season and 0.13 ±

0.33, 0.06 ± 0.24, 0.01 ± 0.12, and 0.04 ± 0.20 in late season for DWV, IAPV, BQCV and

SBV, respectively (average of viral prevalence in bees ± standard deviation; Table 2.6).

2.4.3. Mixed virus infections in honey bee colonies

From the urban apiary, 440 individual honey bees were collected from 44 different colonies in early and late summer of 2017 and 2018 (Table 2.3). The percent of colonies that had detectable viruses increased in late season samples for both years. In 2017, the percent of colonies with one target virus present (mono-infection of DWV, IAPV, BQCV, or SBV) ranged between 5.2–18.1% and 5–42.9% in early and late summer collections, respectively. In 2018, the percent range of infected colonies dropped slightly to 5.5-30% and 7-40%, respectively. Less than 10% of colonies had two or more viruses present (dual-

, triple, tetra-infections) in both years (Table 2.4).

Within the agricultural sites, 30–150 honey bees were collected from 4 apiaries containing 3–15 colonies each. High rates of mono-, dual, -triple, and tetra-infections were found in colonies from agricultural sites. The infection rate of bees increased in late season

samples, which was consistent with temporal variation in rates from urban sites (Table 2.5).

No apiaries were in close proximity to open space sites, therefore no honey bees were collected.

DWV was the most prevalent virus detected among colonies, throughout the season, and in different landscapes with 5.2% and 5.5% at early summer of 2017 and 2018,

5%, and 7% at late summer of 2017 and 2018 in urban and 0.7% and 18.7% at early summer of 2017 and 2018, 73.3%, and 10% at late summer of 2017 and 2018 in agriculture (Table

2.4, 2.5). Co-infections were observed at higher rates than what we would expect by chance and indicates an association between virus types. Calculations of expected frequency of co-detections suggest a relationship between the presence of DWV and increased likelihood of co-infection by other viruses with the higher observed dual- and triple- infection of DWV. For example, from table 2.4, dual-infection of DWV with IAPV,

BQCV, and SBV resulted in 18, 10, and 3-fold and triple-infection of DWV with three viruses resulted in 20-fold higher magnitude than expected infection base on frequency at early summer of 2017 in urban, respectively.

2.5. Discussion

2.5.1. Did the occurrence of viruses differ among the four bee species?

In this study, foraging bees collected from different landscapes were analyzed for the presence of common honey bee viruses (DWV, IAPV, BQCV, SBV) to understand the distribution of viruses in agricultural, urban, and natural open landscapes in eastern

Nebraska. DWV was the most frequently detected virus in all bee species, landscapes,

seasons, and years. IAPV was the second most common virus found but was not found in all bees, seasons, or years. BQCV and SBV were less commonly found but were detected in honey bees and bumble bees (B. griseocollis) from agricultural and open sites.

Detections of common honey bee viruses on alternative hosts supports the hypothesis of inter-species transmission within pollinator communities and has been reported in several previous studies (Levit et al. 2013; Li 2012; Mazzei et al. 2014; Singh et al. 2010; Dolezal et al. 2016). Surprisingly, the significant differences among bee species for both DWV and

IAPV appear to be driven by higher positive detections in wild sweat bees, H. ligatus, (41% and 88.9% infected with DWV, and 36.4% and 88.9% infected with IAPV) that were collected from urban site in early and late summer of 2018, respectively (Figure 2.1). DWV and IAPV are varroa mite-mediated viruses and would be expected to appear at higher rates in honey bees, the only known host of varroa mites (Ryabov et al. 2014; de Miranda et al.

2010; Locke et al. 2014; Brutscher et al. 2016).

Less virulent viruses may be persistent and slowly spread within colonies when infected brood are able to survive through adulthood, thus providing mite-vectors with hosts capable of transporting mites and their associated viruses to uninfected bees and colonies (Lanzi et al. 2006). High varroa mite populations in honey bee colonies increases the potential of viral transmission within and across colonies (Nordstrom et al. 1999;

Nordstrom 2000). High prevalence of DWV and IAPV in honey bees, bumble bees, and sweat bees, reaffirms that honey bee pathogens spill over into wild bee communities, however, little is known about the impact of these viruses on wild bees (Tehel et al. 2016).

Differences in tongue length and foraging behavior may be another explanation why prevalence was higher in sweat bees than other wild bees (i.e. Bombus impatiens and B.

griseocollis), wherein sweat bees have short tongues (2–6 mm in length; Krischik2018) and bumble bees have long tongues (4–16 mm in length; Krischik2018). A foraging bee’s handling time on each flower is positively correlated with the depth of flower heads and the corresponding length of bee tongues required to reach flower nectaries (Harder 1982;

Harder 1983; William et al. 2014). Therefore, the short-tongued sweat bees, may be faster foragers and able to visit more flowers, thereby increasing the likelihood of contact with infected bees and contaminated flowers (Singh et al. 2010). More research is needed to determine infectivity of DWV and IAPV in sweat bees, which would clarify whether sweat bees act as asymptomatic carriers of viruses capable of infecting others.

2.5.2. How did landscape types correlate with the likelihood of virus detection?

Our data showed no significant difference between landscape types; however, our sites were either in or near city limits and not completely isolated. Floral availability measures would have allowed for better distinctions to be made across landscape types, but were not taken in this study. In agricultural landscapes, the rate of virus-infected honey bees increased from early to late season samples. Low sample sizes in wild bees caught during late summer may have contributed to observed differences in the frequency of virus- infected honey and wild bees. Managed bees can be placed in any habitat and moved from one location to another, particularly when floral resources are limited. Wild bees, in contrast, depend on the pockets of natural or semi-natural areas scattered around agricultural and urban areas to provide nesting habitats (Garibaldi et al. 2011). Therefore, plant-pollinator community richness and pollination to crop plants by wild bees depends on the proximity of crop fields to natural areas (Garibaldi et al. 2011). Diminishing natural

habitat and greater pesticide exposure in largely agricultural areas may explain the low number of wild bees found in agricultural sites. In contrast, no honey bees were collected in open space sites. Both honey bees and wild bees were collected from urban sites but more viruses were detected in wild bees compared to honey bees. Human-made urban gardens typically pack high volumes of diverse plants in concentrated areas. The higher density of common foraging sites may increase the number of bee visitations per flower or the likelihood of bee—bee interactions which could increase the risk of interspecific virus transmission. Planting flowers in larger and less dense areas may reduce bee—bee interactions and lower the chance of coming into contact with infected bees or contaminated flowers.

2.5.3. Does pollen play a role in interspecific transmission of viruses among bees?

We hypothesized that if honey bee viruses were being transmitted indirectly to different species of bees though the shared use of contaminated flowers than viruses would be easily detected in flowers and floral resources. Pollen collected from corbicula of honey bees, from in-hive pollen, and from flowers showed low rates of DWV and BQCV only.

The low frequency of detections yielded results not sufficient to assess the persistence and association of viruses with pollen and would require further testing. Chapter 3 of this thesis addresses this question and further examined the role flowers play in interspecific transmission routes.

In conclusion, our results indicate that the prevalence of viruses is affected by bee species, virus type, and season, but not by landscape and year. Low sample sizes of wild bees and low frequency of virus detections made results difficult to interrupt, whereas clear

differences were observed in DWV rates across bee species and seasons, while IAPV was predominately detected in sweat bees and in late season collections. Our data provides greater insight into the prevalence of viruses among bee communities, yet more research is needed to elucidate potential changes in bee and land management practices that could mitigate disease transmission and spread among pollinator communities.

2.6 Figures & Tables

Figure 2. 1. The percent of individual bees (Apis mellifera, Bombus impatiens, Bombus griseocollis, Halictus ligatus) with detectable levels of viruses (BQCV, DWV, IAPV, and SBV) across different landscape types (urban, agricultural, and open spaces). Statistical analyses were completed using Chi- Square and Fisher’s Exact tests. Significant differences in infected bee species are denoted by “*” at alpha = 0.05.

Figure 2. 2. The percent of managed (Apis mellifera & Bombus impatiens) & unmanaged bees (Bombus. griseocollis & Halictus ligatus) with detectable levels of viruses (BQCV, DWV, IAPV, and SBV) across different landscape types (urban, agricultural, and open spaces). Statistical analyses were completed using Chi-Square and Fisher’s Exact tests. Significant differences in infected bees are denoted by “*” at alpha = 0.05.

Figure 2. 3. Virus prevalence, or the number of positive detections of BQCV, DWV, IAPV, and or SBV, in pollen loads collected from the legs of foraging honey bees, in-hive pollen stores, and pollen from flower anthers in samples collected in early and late summer (2017–2018).

Canonical Analysis of Principal Coordinates 4 44 IAPV Canonical Analysis of Principal Coordinates 4

IAPV

Species 2 A.MelliferaA. mellifera Species B.griseocollisB. griseocollis 2 A.Mellifera B.impatiensB. impatiens B.griseocollis B.impatiensH.ligatusH. ligatus H.ligatusPollenPollen Pollen CAP1

CAP1 DWV DWV sizesize

2 2 0 0 4 4 6 6 SBV 8 BQCV SBV 8 BQCV

−2

−2 −2.5 0.0 2.5 5.0 7.5 CAP2

Figure 2. 4. Results from the distance-based redundancy analysis (dbRDA) show the prevalence−2.5 of viruses0.0 in each sample2.5 relative to all5.0 other samples.7.5 Data are visualized using canonical analysis of principalCAP2 coordinates (CAP) with the “capscale” function performed in R (verion 3.5.1). To assess the differences between species (dissimilarity matrix) and the species distribution communities (presence/absence matrix), Bray-Curtis dissimilarity were used. CAP1 and CAP2 are the first two axes from the constrained analysis of principal coordinates, with the respective amount of variation in the Bray–Curtis. Black arrows correspond with DWV, IAPV, BQCV, and SBV virus detections. Individual infections are denoted by solid circles. Samples with more similar virus compositions are closer in proximity to each other and size of points indicate frequency of positive detections. The mean number of infected bee species are represented by open triangles. ** Significance from the’anova.cca’ test indicate differences among species with 1,000 permutations and denoted by p < 0.001.

Canonical Analysis of Principal Coordinates 45

Canonical Analysis of Principal Coordinates IAPV 4

IAPV

2 2 size size2 4 2 6 8 4 CAP1 6 DWV Seasontime 8 Early 0 CAP1 Late DWV SBV Seasontime BQCV Early 0 Late

−2 SBV BQCV

−2.5 0.0 2.5 5.0 7.5 CAP2

Figure 2. 5. Results from the distance-based redundancy analysis (dbRDA) show the prevalence of viruses in samples collected in early and late summer. Data are visually represented using canonical analysis of principal coordinates (CAP) with the “capscale” function performed in R (version 3.5.1). To assess seasonal differences in viral prevalence and distribution of species communities (presence/absence matrix), Bray-Curtis −2 dissimilarity matrices were used. CAP1 and CAP2 are the axes from the constrained analysis of principal coordinates, with the respective amount of variation in the Bray– Curtis analysis. Black arrows correspond with DWV, IAPV, BQCV, and SBV virus −2.5 detections.0.0 Individual infections2.5 are denoted by5.0 solid circles. Samples7.5 with more similar virus compositions are closerCAP2 in proximity and size of points indicate frequency of positive detections. Mean infected bees by season was denoted by open triangles. ** Significance from the’anova.cca’ test was used to indicate differences among season with 1,000 permutations and denoted by p < 0.001.

Table 2.1: Primer sequences and size for each of the four target viruses used in multiplex RT-PCR.

Virus Primers Product size(bp) References

BQCV BQCV-F: (5’ -tggtcagctcccactaccttaaac-3’) 700 Benjeddou et al. (2001)

BQCV-R: (5’ -gcaacaagaagaaacgtaaaccac-3’)

DWV DWV-F: (5’ -atcagcgcttagtggaggaa-3’) 194 Chen et al. (2004b)

DWV-R: (5’ -tcgacaattttcggacatca-3’)

SBV SBV-F: (5’ -gctgaggtaggatctttgcgt-3’) 824 Chen et al. (2004c)

SBV-R: (5’ -tcatcatcttcaccatccga-3’)

IAPV IABPV-F: (5′- ttatgtgtccagagactgtatcca-3) 586 Chen et al. (2014)

IABPV-R: (5′-gctcctattgctcggtttttcggt-3′)

(UM)

Sacbrood virus. Sacbrood

, and and unmanaged (M) (M) SBV Managed Managed at alpha = 0.05. at ” * Israeli acute paralysis Israeli virus; acute paralysis

“ , IAPV

2018. – Agriculture, Urban, and Open landscapes, the names of viruses are the ofabbreviated names follow: as landscapes, viruses Urban, and Open Agriculture, a Black queen cell virus; queen Black

, For For

BQCV Descriptive statistics for positive detections of four common honey bee viruses infor of detections managed and honey Descriptive statistics wild four bee viruses collected common positive bees 2 Deformed wing Deformed virus;

Table Table 2. in the 2017 season across types from landscapes three Significance was determined by Fisher’s Exact Test and Significance denoted determinedby Fisher’s Test was Exact by are with bees showed upper cases. DWV

Table 2. 3 Summary statistics from the Bray-Curtis analysis of dissimilarity illustrating the variance and significance in virus prevalence across bee species, season, and year.

Bray-Curtis R2 P-value Species 0.08988 0.001

Season times 0.03699 0.001

Year 0.01154 0.065 Bold P-values indicate significant comparisons from adonis test (P = 0.05). The variances (r2) and P- values were calculated using analysis of dissimilarity (adonis)

Table 2. 4. Observed frequency compared with expected frequency of viruses per honey bees and colonies collected from urban landscapes in 2017 and 2018.

% of colonies % of bees Type of infected Expected Season Viruses detected infected M Infection (n/total per bee % (n/total bees) colonies) DWV 5.2% (23/440) 18.1% (8/44) IAPV 1.1% (5/440) 4.5% (2/44) Mono-infection SBV 1.1% (5/440) 9% (4/44) BQPV 1% (4/440) 6.9% (3/44) early DWV/IAPV 1.1% (5/440) 4.5% (2/44) 0.06 18X summer DWV/BQCV 0.5% (2/440) 4.5% (2/44) 0.05 10X 2017 Dual-infection DWV/SBV 0.2% (1/440) 2.3% (1/44) 0.06 3X IAPV/SBV 0.2% (1/440) 2.3% (1/44) 0.01 20X IAPV/BQCV 0.2% (1/440) 2.3% (1/44) 0.01 20X DWV/IAPV/SBV 0.2% (1/440) 2.3% (1/44) 0.01 20X Triple-infection DWV/IAPV/BQCV 0.2% (1/440) 2.3% (1/44) 0.01 20X DWV 5% (7/140) 42.9% (6/14) late Mono-infection summer IAPV 1.4% (2/140) 14.3% (2/14) 2017 Dual-infection DWV/IAPV 1.4% (1/140) 7.1% (1/14) 0.07 20X

DWV 5.5% (11/200) 30% (6/20) IAPV 0.5% (1/200) 5% (1/20) Mono-infection SBV 0.5% (1/200) 5% (1/20) early DWV/IAPV 0.5% (1/200) 5% (1/20) 0.03 17X summer DWV/SBV 0.5% (1/200) 5% (1/20) 0.03 17X 2018 Dual-infection IAPV/SBV 0.5% (1/200) 5% (1/20) 0.002 250X

Triple-infection DWV/SBV/ IAPV 0.5% (1/200) 5% (1/20) 0.0001 5,000X DWV 7% (7/100) 40% (4/10)

IAPV 3% (3/100) 20% (2/10) late summer Mono-infection SBV 5% (5/100) 30% (3/10) 2018 BQPV 1% (1/100) 10% (1/10)

Dual-infection DWV/BQCV 1% (1/100) 10% (1/10) 0.07 14X

The number of viruses positively detected (n) and the percentage of infected bees and colonies are shown. The total detection of each virus are divided into whether they occurred by themselves (mono-infection) or concurrently with one or more other viruses (co-detection: dual-, triple- & tetra-infection). Expected frequency of co-detection were calculated as prevalence of first virus x prevalence of second virus. Magnitude (M) illustrates higher magnitude of fold change in observed co-infections than what is expected by chance.

Table 2. 5. Observed frequency compared with expected frequency of viruses per honey bees and colonies collected from agricultural landscapes in 2017 and 2018.

% of colonies % of bees Type of Viruses infected Expected infected (n/total M Season Infection detected (n/total per bee % bees colonies) Early Mono- summer DWV 0.7%(1/150) 6.6% (1/15) 2017 infection DWV 73.3% (22/30) 100% (3/3) Mono- IAPV 23.3% (7/30) 66.6% (2/3) infection SBV 23.3% (7/30) 66.6% (2/3) BQPV 16.6% (5/30) 33.3% (1/3) DWV/IAPV 23.3% (7/30) 66.6% (2/3) 17.1 1X DWV/BQCV 16.6% (5/30) 33.3% (1/3) 12.2 1X

DWV/SBV 23.3% (7/30) 66.6% (2/3) 17.1 1X

BQCV/IAPV 16.6% (5/30) 33.3% (1/3) 3.9 4X

Dual-infection BQCV/SBV 16.6% (5/30) 33.3% (1/3) 3.9 4X

late IAPV/SBV 20% (6/30) 33.3% (1/3) 5.4 4X summer DWV/BQCV/ 16.6% (5/30) 33.3% (1/3) 2.8 6X 2017 IAPV DWV/IAPV/ 20% (6/30) 33.3% (1/3) 4 5X Triple- SBV infection IAPV/SBV/ 16.6% (5/30) 33.3% (1/3) 0.9 18X BQCV DWV/BQCV/ 16.6% (5/30) 33.3% (1/3) 2.8 6X SBV Tetra- DWV/BQCV/ 16.6% (5/30) 33.3% (1/3) 0.7 23X infection SBV/IAPV DWV 18.7%(15/80) 25% (2/8) early IAPV 1.2% (1/80) 25% (2/8) summer Mono- 1.2% (1/80) 12.5%(1/8) SBV 2018 infection Dual-infection DWV/IAPV 1.2% (1/80) 12.5%(1/8) 0.2 6X DWV 10% (4/40) 50% (2/4) late IAPV 10% (4/40) 50% (2/4) summer Mono- SBV 7.5% (3/40) 25% (1/4) 2018 infection Dual-infection IAPV/SBV 5% (2/40) 25% (1/4) 0.7 7X

The number of viruses positively detected (n) and the percentage of infected bees and colonies are shown. The total detection of each virus are divided into whether they occurred by themselves (mono-infection) or concurrently with one or more other viruses (co-detection: dual- , triple- & tetra-infection). Expected frequency of co-detection were calculated as prevalence of first virus x prevalence of second virus. Magnitude (M) illustrates higher magnitude of fold change in observed co-infections than what is expected by chance.

Table 2. 6. The mean number (± s.d.) of virus prevalence of bee species by landscape types, season, and year.

by landscapes DWV IAPV BQCV SBV Urban 0.070 ± 0.256 0.025 ± 0.158 0.005 ± 0.072 0.011 ± 0.106 Agriculture 0.143 ± 0.350 0.039 ± 0.194 0.013 ± 0.113 0.036 ± 0.187 Open 0.182 ± 0.387 0.091 ± 0.288 0.091 ± 0.081 0.006 ± 0.081 by season Early-mid 0.084 ± 0.278 0.023 ± 0.151 0.004 ± 0.064 0.007 ± 0.081 Late 0.130 ± 0.336 0.063 ± 0.243 0.015 ± 0.120 0.042 ± 0.200 by year 2017 0.070 ± 0.255 0.017 ± 0.129 0.011 ± 0.102 0.013 ± 0.112 2018 0.133 ± 0.339 0.133 ± 0.233 0.003 ± 0.052 0.022 ± 0.146 Mean number of virus prevalence in bee species ± standard deviation

References cited

Ascher, J. S. & Pickering, J. (2011). Bee species guide. Retrieved from https://www.discoverlife.org/. Arduser, M. (2018). Bees of the tallgrass prairie region and greater Midwest. Anderson, M. J. & Willis, T. (2003). Canonical analysis of principal coordinates: a useful method of constrained ordination for ecology. Ecology, 84(2), 511–525. Blanchet, F. G., Legendre, P. & Borcard, D. (2008). Forward selection of explanatory variables. Ecology 89(9), 2623–2632. Brutscher, L. M., McMenamin, A. J., & Flenniken, M. L. (2016). The buzz about honey bee viruses. PLoS pathogens, 12(8), e1005757. Clarke, K. R., Somerfield, P. J., & Chapman, M. G. (2006). On resemblance measures for ecological studies, including taxonomic dissimilarities and a zero-adjusted Bray– Curtis coefficient for denuded assemblages. Journal of Experimental Marine Biology and Ecology, 330(1), 55–80. Dixon, P. (2003). VEGAN, a package of R functions for community ecology. Journal of Vegetation Science, 14(6), 927–930. De Miranda, J. R., & Genersch, E. (2010). Deformed wing virus. Journal of invertebrate pathology, 103, 48–61. De Miranda, J. R., & Fries, I. (2008). Venereal and vertical transmission of deformed wing virus in honeybees (Apis mellifera L.). Journal of invertebrate pathology, 98(2), 184–189. Dolezal, A. G., Hendrix, S. D., Scavo, N. A., Carrillo-Tripp, J., Harris, M. A., Wheelock, M. J., O’Neal, M. E., & Toth A. L. (2016). Honey bee viruses in wild bees: viral prevalence, loads, and experimental inoculation. PloS one, 11(11), e0166190. Evans, J. D., & Spivak, M. (2010). Socialized medicine: individual and communal disease barriers in honey bees. Journal of invertebrate pathology, 103, 62–72. Garibaldi, L. A., Steffan-Dewenter, I., Kremen, C., Morales, J. M., Bommarco, R., Cunningham, S. A., Carvalheiro, L. G., Chacoff, N. P., Dudenhoffer, J. H., Greenleaf, S. S., Holzschuh, A., Isaacs, R. Krewenka, K., Mandelik, Y., Mayfield, M. M., Morandin, L. A., Potts, S. G., Ricketts, T. H., Szentgyorgyi, H., Viana, B. F., Westphal, C., Winfree, R., Klein, A. M. & Holzschuh, A. (2011). Stability of pollination services decreases with isolation from natural areas despite honey bee visits. Ecology letters, 14(10), 1062–1072. Hatfield, R., Jepsen, S., Mader, E., Black, S. H. & Shepherd, M. (2012). Conserving bumble bees: guidelines for creating and managing habitat for America's declining pollinators. Xerces Society for Invertebrate Conservation. Harder, L. D. (1983). Flower handling efficiency of bumble bees: morphological aspects of probing time. Oecologia, 57(1–2), 274–280. Harder, L. D. (1982). Measurement and estimation of functional proboscis length in bumblebees (Hymenoptera: Apidae). Canadian Journal of Zoology, 60(5), 1073– 1079.

Klein, S., Cabirol, A., Devaud, J. M., Barron, A. B., & Lihoreau, M. (2017). Why bees are so vulnerable to environmental stressors. Trends in Ecology & Evolution, 32(4), 268–278. Krischik, V. 2018. USDA NCIPM Consumer horticulture working group 2008-2015. The University of Minnesota. Retrieved from http://ncipmhort.cfans.umn.edu/id-native- bees-scroll-down-see-pictures-and-information-6-families-native-bees. Locke, B., Forsgren, E., & de Miranda, J. R. (2014). Increased tolerance and resistance to virus infections: a possible factor in the survival of Varroa destructor-resistant honey bees (Apis mellifera). PloS one, 9(6), e99998. Levitt, A. L., Singh, R., Cox-Foster, D. L., Rajotte, E., Hoover, K., Ostiguy, N., & Holmes, E. C. (2013). Cross-species transmission of honey bee viruses in associated arthropods. Virus research, 176(1–2), 232–240. MacKenzie, K. E. (1994). The foraging behavior of honey bees (Apis mellifera L) and bumble bees (Bombus spp.) on cranberry (Vaccinium macrocarpon Ait). Apidologie, 25(4), 375–383. Macfarlane, R. P. (1992). An initial assessment of blueberry pollinators in New Zealand. New Zealand Journal of Crop and Horticultural Science, 20(1), 91–95. McMenamin, A., Daughenbaugh, K., Parekh, F., Pizzorno, M., & Flenniken, M. (2018). Honey bee and bumble bee antiviral defense. Viruses, 10(8), 395. Mazzei, M., Carrozza, M. L., Luisi, E., Forzan, M., Giusti, M., Sagona, S., Tolari, F., & Felicioli, A. (2014). Infectivity of DWV associated to flower pollen: experimental evidence of a horizontal transmission route. PloS one, 9(11), e113448. Meisels, S., & Chiasson, H. (1996). Effectiveness of Bombus impatiens Cr. as pollinators of greenhouse sweet peppers (Capsicum annuum L.). In VII International Symposium on Pollination, 437, 425–430. McMenamin, A. J., & Flenniken, M. L. (2018). Recently identified bee viruses and their impact on bee pollinators. Current opinion in insect science, 26, 120–129. Manley, R., Boots, M., & Wilfert, L. (2015). Emerging viral disease risk to pollinating insects: ecological, evolutionary and anthropogenic factors. Journal of Applied Ecology, 52(2), 331–340. Mineau, P. & Whiteside, M. (2013). Pesticide acute toxicity is a better correlate of US grassland bird declines than agricultural intensification. PloS one, 8(2), e57457. National Research Council Committee (NRCC) on Status of Pollinators in North America (2007). Status of pollinators in North America. Washington, D. C., The National Academies Press. Nordström, S., Fries, I., Aarhus, A., Hansen, H., & Korpela, S. (1999). Virus infections in Nordic honey bee colonies with no, low or severe Varroa jacobsoni infestations. Apidologie, 30(6), 475–484. Nordström, S. (2000). Virus infections and varroa mite infestations in honey bee colonies. Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., Minchin, P. R., O’hara, R. B., Simpsom G. L., Solymos P., Stevens M. H. H., Szoecs, E. & Wagner, H. (2011). vegan: Community ecology package. R package version, 117–118.

Pavoine, S., Dufour, A. B., & Chessel, D. (2004). From dissimilarities among species to dissimilarities among communities: a double principal coordinate analysis. Journal of theoretical biology, 228(4), 523–537. Potts, S. G., Biesmeijer, J. C., Kremen, C., Neumann, P., Schweiger, O., & Kunin, W. E. (2010). Global pollinator declines: trends, impacts and drivers. Trends in ecology & evolution, 25(6), 345–353. Palma, G., Quezada-Euán, J. J. G., Reyes-Oregel, V., Meléndez, V., & Moo-Valle, H. (2008). Production of greenhouse tomatoes (Lycopersicon esculentum) using Nannotrigona perilampoides, Bombus impatiens and mechanical vibration (Hym.: Apoidea). Journal of Applied Entomology, 132(1), 79–85. Pierce, R. A., White, B., Jones-Farrand, D. T., Dailey, T. V., & Carpenter, B. (2008). Field borders for agronomic, economic and wildlife benefits. Ryabov, E. V., Wood, G. R., Fannon, J. M., Moore, J. D., Bull, J. C., Chandler, D., Mead, A., Burroughs, N., & Evans, D. J. (2014). A virulent strain of deformed wing virus (DWV) of honeybees (Apis mellifera) prevails after Varroa destructor- mediated, or in vitro, transmission. PLoS pathogens, 10(6), e1004230. Sauer, J. R., Hines, J. E., Thomas, I., Fallon, J., & Gough, G. (2000). The North American breeding bird survey. Results, and analysis, 1966–1999. Patuxent Wildl. Res. Cent., Laurel, Md. Singh, R., Levitt, A. L., Rajotte, E. G., Holmes, E. C., Ostiguy, N., vanEngelsdorp, D., lan Lipkin, W., dePamphilis, C. W., Toth, A. L., & Cox-Foster, D. L. (2010). RNA viruses in hymenopteran pollinators: evidence of inter-taxa virus transmission via pollen and potential impact on non-Apis hymenopteran species. PloS one, 5(12), e14357. Schneider, R., Humpert, M., Stoner, K., & Steinauer, G. (2005). The Nebraska natural legacy project. Tehel, A., Brown, M. J., & Paxton, R. J. (2016). Impact of managed honey bee viruses on wild bees. Current opinion in virology, 19, 16–22. Urbanek, S. (2018). R 3.5.1 binary for Mac OS X 10.11. Retrieved from https://cran.r- project.org/bin/macosx/. Velthuis, H. H. & Van Doorn, A. (2006). A century of advances in bumblebee domestication and the economic and environmental aspects of its commercialization for pollination. Apidologie, 37(4), 421–451. vanEngelsdorp, D., Evans, J., Saegerman, C., Mullin, C., Haubruge, E., Nyguyen, B. K., Frazier, M., Frazier, J., Cox-Foster, D., Chen, Y., Underwood, R., Tarpy, D. R. & Pettis, J. S. (2009). Colony collapse disorder: a descriptive study. PloS one, 4(8), e6481. Williams, P. H., Thorp, R. W., Richardson, L. L., & Colla, S. R. (2014). Bumble bees of North America: an identification guide. Princeton University Press. Waldbauer, G. (2017). Insects are not all bad: Beneficial aspects of insect-human interactions. Insect, 52, 66–67. Williams, P. H., Thorp, R.W., Richardson, L. L., & Colla, S.R. (2014). Bumble bees of North America: an identification guide. Princeton University Press.

Chapter 3

An examination of the potential roles foraging activity, flowers, and other insects

play in the spread of common honey bee viruses

3.1 Abstract

Bees are vital pollinators for an array of agricultural crops, wildflowers, and ornamental garden plants. In recent years, high losses in honey bee colonies and population declines in wild bees have been reported worldwide. Bee health declines have been attributed to several factors such as pathogens, parasites, agrochemical exposure, and the decrease of nutritional resources. Varroa destructor mites are ecto-parasites that feed on the hemolymph and bodily fluids of their honey bee hosts. The feeding action by mites causes the introduction of several different viruses. Together, the mites and their associated viruses are primary drivers in honey bee losses. The spread of viruses from infected honey bees into wild bee populations has been widely documented, however there remains little known about the prevalence of honey bee viruses and viral infectivity in wild bees.

Interspecific transmission of viruses among foraging bees may occur through direct contact with infected individuals or indirectly through contact with contaminated flowers and resources (nectar/pollen).

We examined the potential roles foraging activity, flowers, and other insects in the spread of common honey bee viruses. To do this, the presence of honey bee viruses (DWV,

IAPV, BQCV, and SBV) were tested for in honey bees foraging on flowers, flowers visited by bees, other insects foraging on shared flowers, and pollen from the flower anthers and

foraging bees. I also followed foraging honey bees (paint marked) back to their hive and tested hive mates and in-hive pollen for the same viruses. Twelve target plant species were selected for their varying phenology of blooms (early, mid, late summer) and bloom durations (short, medium, long). The results showed that two of the four honey bee viruses are more frequently detected in wild bees and other insects (DWV, IAPV) while the other two had few positive detections (BQCV, SBV) in all samples. Few detections of viruses on flower pedals and all pollen samples indicates that interspecific transmission of viruses is likely driven by direct bee-to-bee interaction rather than through contaminated foods and surfaces. While flowers are likely not a route of viral transmission, they still play a role.

Our data showed a higher incidence of viruses from bees associated with long blooming flowers, which suggests bloom duration may influence rate of viral transmission. Our results may provide insight into plant selection and landscape design considerations that would minimize the number of shared flowers bees visit, reduce opportunities for direct contact with other individuals, and mitigate interspecific transmission of viruses within pollinator communities.

3.2. Introduction

Commercially managed bees and wild bees are highly regarded as important pollinators of crop plants and native floral. Bees provide critical pollination services that support food production to meet the needs of increasing global populations. High losses of commercially managed honey bee colonies and declines in wild bee populations have been reported worldwide over the last decade (McMenamin & Genersch 2015). Bee health declines have been attributed to multiple factors such as pathogens, agrochemical exposure,

and the decrease of nutritional resources due to agricultural intensification and urban development (McMenamin & Flenniken 2018; Graystock et al. 2015).

Viruses can become serious pathogens affecting individuals and colonies of bees.

While many viruses remain in their host in latent or asymptomatic forms, some viruses manifest to impair brood development and or lead to higher mortality rates in honey bee colonies and wild bees (Tehel 2016; McMenamin & Flenniken 2018). Shared use of flowers and floral resources, increases the chance of interacting with infected bees or contaminated surfaces, thereby mediating interspecific transmission of viruses within insect communities (McMenamin et al. 2018). Previous studies have shown that honey bees are not the only host of viruses found in honey bee colonies (Singh et al. 2010). Honey bee viruses can be transmitted from managed bees (A. mellifera and B. impatiens) to wild bees and other insects. For example, the most prevalent virus found in honey bees, deformed wing virus (DWV), positive-sense single stranded RNA (+ssRNA) virus in the family Iflaviridae, has also been detected in both wild bees [Bombus impatiens (Li et al.

2011), B. terrestris, and B. pascuorum (Singh et al. 2010)] Mason bees (Osmia bicornis, and O. cornuta (Tehel 2016)) and other insects, like ants (Linepithema humile; Sébastien et al. 2015). Several other viruses common to honey bees have also been found in another bee species. Sacbrood virus (SBV) (family Iflaviridae), has been detected in commercially managed bumble bee colonies (B. impatiens) (Singh et al. 2010) and in other wild bumble bees (B. atratus, B. terrestris (Tehel 2016)) and mason bees (Megachilids (Dolezal et al.

2016)). Acute bee paralysis virus (ABPV) and Kashmir bee virus (KBV) in the family

Dicistroviridae has been detected in B. terrestris (Meeus et al. 2014).

Extensive literature supports the theory of pathogen spillover from honey bees into novel host populations, however there remain knowledge gaps regarding the impact and infectivity of honey bee viruses in wild bee hosts. Some honey bee viruses, such as Israeli acute paralysis virus (IAPV), were more prevalent in mining bees (Andrenidae) than compared to honey bees and other wild bees (Dolezal et al. 2016). Another study demonstrated that unclassified RNA viruses, Lake Sinai virus (LSV) can replicate in the bumble bees (B. pascuorum), mason bees and mining bees (Andrena vaga and A. ventralis)

(McMenamin & Flenniken 2018; Daughenbaugh et al. 2015).

In addition, honey bee viruses have been detected in other hymenopteran insects;

KBV found in yellow jacket wasps (Vespula germanica), (Levitt et al. 2013), IAPV in wasps (Vespula vulgaris and V. velutina), CBPV (Chronic bee paralysis virus) and DWV in ants (Formica rufa and Campunotus vagus) (Yanez et al. 2012; Celle et al. 2008; Bigot et al. 2017). Moreover, studies found that plant viruses can replicate in both plant tissues and honey bees. Li et al. (2014) demonstrated that tobacco ring spot virus (TRSV) has multiple hosts including plants (crops, weeds, and ornamentals) and insects (aphids, thrips, grasshoppers, and tobacco flea beetle; Flenniken 2018; Li et al. 2014). TRSV can also replicate inside honey bees and is suspected to be a mite-mediated virus since TRSV has been detected on both the bodies of honey bees and Varroa destructor mites, an ectoparasite of honey bees and known vector of several honey bee specific viruses

(Flenniken 2018; Li et al. 2014).

Varroa mite infestation in bee colonies is commonly associated with mite-mediated viruses (DWV, IAPV, ABPV, CBPV, SPV, BQCV, and SBV) and can lead to increased

viral loads, virulence, and prevalence of viruses in within colonies and across apiaries

(Santamaria et al. 2018; Martin et al. 2012).

Flowers that provide nectar and pollen rewards may attract a variety of foraging insects. The flowering plant species and pollinators depend on each other. With this positive relationship, flowers provide habitat which is the necessary food resources of native pollinators while pollinators are a cornerstone of pollination. The shared use of flowers and common foraging sites can play critical roles in the transmission of pathogens i.e. viruses) within insect communities. Therefore, the alarming declines in pollinator populations highlights the need to provide pathogen and pesticide-free habitats for maintaining healthy pollinator communities. Floral traits, such as flower structure and bloom period may affect the number of visitations, handling time or time spent foraging, and duration of foraging activity. To further investigate the role foraging activity and flowers play in interspecific viral transmission, foraging bees and other insects

(Hymenoptera, Lepidoptera, Hemiptera, and Coleoptera) were collected from short, medium, and long blooming flowers and assessed for the presence of four common honey bee viruses (DWV, IAPV, BQCV, SBV). Additionally, we tested flower pedals and pollen to examine whether honey bee viruses were detectable on flowers visited by honey bees and in other insects foraging on the same flowers as honey bees. We hypothesized that honey bee viruses are present in different bees and insects and infection occurs through direct contact with infected individuals as well as indirectly through the use of shared flowers and resources.

3.3. Materials and Methods

3.3.1. Site and sample collection

The University of Nebraska-Lincoln Pollinator Garden and Outdoor Classroom located on East Campus (established in 2015) is a small garden space with 40+ different species of pollinator-friendly plants. Adjacent to the garden is the UNL research apiary which houses approximately 10-20 honey bee colonies and roughly 10 bumble bee (B. impatiens) research colonies throughout the year. This site allowed for the collection of honey bees, wild bees, other foraging insects and pollen or pedals from flowers found in the garden as well as bee-collected pollen from the legs of foraging honey bees and were directly collected from forager bees and using in-hive pollen traps on colonies in the adjacent apiary (Table 3.4, 3.5, 3.6). Collections were taken three times from July through the end of August. A total of 12 forbes selected for the experiment were chosen according to their blooming period [short: buttombush (Cephalanthus occidentalis), joe pye weed

(Eupatorium purpureum), and blazing star (Liatris spp.); medium: wild bergamot

(Monarda fistulosa), rattlesnake master (Eryngium yuccifolium), brown eyed susan

(Rudbeckia spp.), and sneezeweed (Helenium autumnale); long bloom: blue mist spirea

(Caryopteris clandonensis), green-head coneflower (Rudbeckia laciniata), blue Russian sage (Perovskia atriplicifolia), purple coneflower (Echinacea purpurea), and catmint

(Nepeta cataria)] and phenology (early, mid, and late summer) (Table 3.7). Observations of foraging activity on target flowers, allowed us to further specify if flowers were attractive or unattractive to honey bees based on observed visitations.

3.3.2. Honey bee collection

Foraging honey bees (Apis mellifera) in the pollinator garden were directly collected on flowers using vial trapping and kept on ice in the field for <5 min. Chilled honey bees were marked on their thoraces with non-toxic green paint and allowed to return to their colonies. Honey bee colonies were then inspected for paint-marked bees so that bees captured at specific flowers could be followed back to the hive and the colony could be assessed for viruses. Viral loads in colonies were determined by screening in-hive pollen

(collected from pollen traps that dislodge corbicula pollen from returning foragers) and foragers caught at the hive entrance for the presence of DWV, IAPV, BQCV, and SBV.

Virus detections from colonies were then compared to the viral profiles of the flowers from which the paint-marked bee was originally captured and any other insects foraging on the same flower.

3.3.3. Collection of wild bees and other insects

Twelve target plants were observed during bloom to assess foraging activity and collect foraging insects, flower pedals, and pollen from anthers to analyze for the presence of DWV, IAPV, BQCV, and SBV viruses (Table 3.7). Wild bees and other insects on target flowers during bloom were collected. Other insects included wasps (Hymenoptera), beetles

(Coleopteran), true bugs (Hemipteran), and butterflies (Lepidoptera) (Table3.4., 3.5., 3.6.)

3.3.4. Flower and pollen collection

Flower pedals and pollen from anthers of each target flower were collected during peak bloom and tested for the presence of DWV, IAPV, BQCV, and SBV. Bee-collected

pollen was collected two ways from the foraging site and at the colony. Corbicula pollen or pollen loads packed onto the hind tibia of foraging honey bees were sampled when bees were caught on target flowers. Collected honey bees were paint-marked and released so that we could locate their colony. Pollen traps were placed on the colonies that housed paint marked bees previously caught in the garden. Pollen traps set at the entrance of the hive forces returning foragers to walk through a mesh screen that dislodges pollen loads off their hind legs as they pass through to enter the hive. Pollen traps were active on colonies for 1-

2 days during each of the three collection periods.

Insects, flowers, and pollen samples were kept on ice in the field and later stored in individual vials at -20 ̊C until insects could be identified. Identification of bees and insects were confirmed using three identification guides (Ascher & Pickering 2011; Arduser 2018;

Williams et al. 2014; Ascher et al. 2008).

Insect, flower, and pollen samples were maintained at -80 ̊C until ready to process for viral

RNA extraction. Bees and other insects were prepared for extraction using the same tissue dissection procedure as outlined in Chapter 2.

3.3.5. Total RNA extraction

Dissected bee and insect thoraces and pollen samples were process to extract total

RNA and assess for the presence of viral RNA. Bees were individually processed to improve detection of viruses in homogenate samples. Each sample was transferred to nuclease-free centrifuge tubes (1.5 ml). Resistant 316 stainless steel ball (6.35 mm diameter) and TRI Reagent (Invitrogen) (1 ml per 50–100 mg of tissue) were put into

sample tubes to homogenize using the SPEX SamplePrep 2010 Geno/Grinder® at 1300 strokes for 1 min. The liquid was removed into a fresh centrifuge tube and allowed to settle for 5 min at room temperature. After settling, chloroform (0.2 ml per ml of TRIzol Reagent used) was added and the tube was vigorously vortexed for 15 secs to mix. Samples were then left at room temperature for 15 min and centrifuged at 12,000 x g for 15 min. At this point, samples separated into three layers and the aqueous phase was transferred into a fresh tube. Isopropanol (0.5 ml per ml of TRIzol Reagent used) was added and gently mixed to the aqueous phase. Sample tubes were stored over night at -20 °C and then centrifuged at 12,000 x g for 10 min. After this process, a small barely visible pellet containing RNA would form at base of each tube. RNA pellets were washed by adding 1 ml 75% ethanol and then centrifuging the tube at 7,500 x g for 5 min. The ethanol was poured off without touching the pellet at base of tubes and the pellet was allowed to air- dry. RNA samples were further dissolved in DEPC-treated water in the presence of

Ribonuclease Inhibitor (Invitrogen, Carlsbad, CA) and stored at -80 °C for further analysis

(Chen 2004). The concentration of extracted RNA was estimated by measuring the absorbance of aliquots at 260 nm of an aliquot of the final preparation at a Nanodrop 2000c

(Thermo Scientific). Then, RT-PCR was used to detect the presence of target viruses.

3.3.6. RT-PCR analysis

The multiplex Reverse Transcription-PCR (RT-PCR) protocols adapted from Chen et al. (2004) were performed to determine whether samples contained deformed wing virus

(DWV), Black Queen Cell Virus (BQCV), Sacbrood Virus (SBV), and Israeli Acute

Paralysis Virus(IAPV) by using a one-step RT-PCR kit (Promega, Madison, WI). RT-PCR

reaction contained 1 x AMV/Tfl reaction buffer, 4 mM MgSO4, 0.6 mM dNTP, 0.4 unit

AMV reverse transcriptase, 0.4 unit Tfl DNA polymerase, 2 µg total RNA, 0.6 µM of each specific primer for DWV, BQCV, SBV, and IAPV in a total volume of 50 µl. The cycling conditions consisted of one cycle at 48 °C for 45 min for reverse transcription followed by one cycle at 94 °C for 2 min, 20 cycles of 94 °C for 30 s, 58 °C for 1 min, and 68 °C for 1 min, and 20 cycles of 94 °C for 30 s, 52 °C for 1 min and 68 °C for 1 min followed by final elongation step at 68 °C for 10 min. PCR products were separated by electrophoresis in

1.8% agarose gel and visualized under UV light.

3.3.7. Statistical analysis

3.3.7.1 Distance-based redundancy analysis of virus types

To assess the relationship between virus types, insects with detectable viruses, and season (early-, mid- and late summer), a distance-based redundancy analysis (dbRDA) was performed (Pavoine et al. 2004). The differences among species (dissimilarity matrix) and the species distribution communities (presence/absence matrix) with a zero-adjusted Bray-

Curtis dissimilarity metric were analyzed (Clarke et al. 2006). The vegan package in R

(version 3.5.1) was used for the analysis of dissimilarity and a constrained analysis of principal coordinates (‘capscale’) was performed from matrix distances or dissimilarities among virus types and insect species (Anderson & Willis 2003). The model for constrained ordination methods (capscale) was built by applying ‘ordistep’ function that allows forward, backward, and stepwise model selection using permutation tests (Blanchet et al.

2008). Negative eigenvalues were transformed to positive eigenvalues because capscale discards the imaginary dimensions with negative eigenvalues and only uses positive

eigenvalues (Oksanen et al. 2013). The ‘adonis’ function was applied to analyze the variance in distance matrices (Dixon 2003).

3.4. Results

3.4.1. Detection of viruses in foraging insects collected on flowers

Of the twelve flowering plants surveyed (Table 3.7), nine had observed visitations by foraging honey bees and were categorized as attractive to honey bees. A total of 217 samples of honey bees, bumble bees, wild bees, and other insects were collected during early (n = 82), mid (n = 83), and late summer (n = 52) and assessed for the presence of

DWV, IAPV, BQCV, and SBV. In early summer samples, DWV was the only virus detected (2.4% (2/82) of all samples) and was found in “other insects” collected on catmint

(Nepeta cataria) ((1/3) Formica pellidefulva samples had positive detections) and purple coneflower (Echinacea purpurea) ((1/6) Sphex pensylvanicus) (Table 3.4). In mid- summer, 3.6% (3/83) of all samples had DWV and 4.8% (4/83) had BQCV. DWV was detected in 6.7% of honey bees collected from colonies with paint-marked bees and 7.1% of honey bees caught foraging on blue Russian sage (Perovskia atriplicifolia). On catmint

12.5% (1/8) of wild bees caught had detectable levels of DWV [(1/3) Melissoides bimaculatus] and BQCV [(1/3) Melissoides bimaculatus] while 22.2 % of wild bees [(1/7)

M. menuachus and (1/1) Nomada spp.] caught on blazing star (Liatris spp.) had BQCV.

Other insects did not test positive for DWV but 25% of insects [(1/3) Acalymma vittatum] found on brown-eye susan (Rudbeckia spp.) had BQCV (Tables. 3.2, 3.5). In late summer, all four viruses [DWV (13.5% positive detections), BQCV (1.9%), IAPV (5.8%), and SBV

(1.9%)] were detected in samples. DWV was the most prevalent virus found in foraging honey bees [on blue mist spirea (Caryopteris clandonensis) and green-headed coneflower

(Rudbeckia laciniata; 3/5), honey bees in colonies (2/10) and wild bees [Bombus griseocollis (1/5) on blue mist spirea (Caryopteris clandonensis) and (1/2) Halictus ligatus on sneezeweed (Helenium autumnale)] but not in other insects. BQCV and IAPV were found in one bumble bee (B. impatiens) foraging on blue mist spirea (Caryopteris clandonensis; 1/7). BQCV was not found in any other sample but IAPV was found in H. ligatus on sneezeweed (Helenium autumnale; 1/2), and in honey bees collected in colonies containing paint-marked bee (1/10). SBV is only found in honey bees collected in colonies

(1/10). There were no detectable viruses found in “other insects” (0/15) collected during late summer (Table 3.3., 3.6).

3.4.2. Dissimilarities among species, virus types, and seasons

Differences in virus prevalence between insect species collected from pollinator garden were assessed using Bray-Curtis dissimilarity matrix (Glenny et al. 2017). Positive detections of viruses in each sample relative to all other samples were visualized using canonical analysis of principal coordinates (CAP) with capscale function (Figure 3.1. and

3.2.). Results from adonis analysis indicated that different insect species explained the most variation in virus prevalence (Figure 3.1. and Table 3.8, R2= 0.32, p = 0.025), followed by season time of sampled insect species (Figure 3.1. and Table 3.8., R2= 0.25, p = 0.031).

Surprisingly, viral prevalence in collected insect samples did not differ between flowers with short, medium or long blooming times (Table 3.8., Ordistep function, p =0.145).

The presence of viruses in bee samples across three seasonal periods was examined.

DWV was detected in bee and insect samples (except Bombus impatiens) and through all seasons. BQCV appeared mid-summer in wild bee and insect samples but then could only be found in B. impatiens samples by late summer. IAPV and SBV were only detected in late season samples and not at high rates (Figure 3.1. and 3.2.).

3.5. Discussion

To understand the potential roles foraging activity, flowers, and other insects play in the transportation and or spread of viruses, we sampled foraging honey bees, the pollen on their legs, and the flowers they visited, then followed them back to their hives and sampled in-hive bees and pollen to captured a snap shot of the viral environment from the apiary to the garden. Pathogen spill over from honey bees to other insects have previously been shown but critical gaps remain in our knowledge of the drivers and mechanisms by which interspecific transmission of viruses occurs. Here, we showed that honey bee viruses may be present in wild bees and other insects at possibly species-specific occurrence rates and varying across season. Bombus impatiens bumble bees were separately grouped from

“wild bees” because we wanted to prevent inflation of numbers potential due to the B. impatiens research colonies housed near the garden. There were few positive detections of viruses in B. impatiens, however, the number of collected bees was low throughout the season (2, 7 and, 7 bees collected in early, mid, and late summer). Interestingly, the rate of observed positive virus detections in wild bees were higher than compared to honey bees.

In addition, insects (Coleopterans and Hymenopterans) exhibited higher detections of viruses despite low detections on flowers and pollen. This may suggest that multiple viruses may infect one or more hosts and insects may be asymptomatic carriers. Carriers

exhibit no signs of disease yet are capable of infecting others that come into indirect contact by sharing microenvironments and resources. Given fewer positive detections of viruses in plant materials, it is likely that interspecific transmission of viruses occurs through direct contact with infected individuals rather than indirect transmission through contaminated floral resources and surfaces.

There were no significant differences found in positive viral detections from flowers with short, medium, or long bloom periods. However, viruses in foraging bees and insects were detected more commonly on long blooming flowers. The longer bloom period may provide more opportunities for visitations by foraging insects and higher traffic increases the chance of contact with infected individuals. The role flowers play in viral transmission is not clear. The deposition of feces from infected insects on flowers may be a major source of contamination that infects other visiting insects (Singh et al. 2010).

Positive detections of viruses (DWV, IAPV, BQCV, SBV, and KBV) found in the digestive tracts and feces of honey bees were at higher viral titers then the viral loads in other honey bee tissues indicating feces is likely a source of viral infection (Chen et al. 2006; Hung

2000; Singh et al. 2010). Low detections of viruses on flower pedals and all pollen samples, in our study, indicates that interspecific transmission of viruses is likely driven by direct bee-to-bee interaction rather than through contaminated foods and surfaces. While flowers may not play a direct role in viral transmission, floral traits may influence the likelihood for infected bees to come into contact with uninfected individuals at common forging sites.

Our data showed bees collected from longer blooming flowers [blue mist spirea

(Caryopteris clandonensis), blue Russian sage (Perovskia atriplicifolia), catmint (Nepeta cataria)] had more frequent detections of viruses which suggests bloom duration may

influence rate of viral transmission. Our results may provide insight into plant selection and landscape design considerations that minimizes the number of shared flowers bees visit, reduces opportunities for direct contact with other individuals, and mitigates interspecific transmission of viruses within pollinator communities.

Canonical3.6. Figures CanonicalAnalysis & Tables Analysisof Principal of Principal Coordinates Coordinates

BQCV BQCV 2 2

size 1 size 1 1 1 2 2 3 3 4 IAPV 4 IAPV 5 0 5

0 CAP1

CAP1 Insect_Group

Insect_GroupB.impatiens SBV Honey_beeB.impatiensB. impatiens SBV InsectHoney_bee -1 Wild_beeInsect -1 Wild_bee

-2 DWV -2 -1DWV 0 1 2 3 CAP2 -1 0 1 2 3 CAP2 Figure 3. 1. Distance-based redundancy analysis (dbRDA) was performed. The virus prevalence of each sample relative to all other samples were visualized using canonical analysis of principal coordinates (CAP) with capscale function. CAP1 and CAP2 are the first two axes from the constrained analysis of principal coordinates, with the respective amount of variation in the Bray–Curtis. Black arrows correspond with DWV, IAPV, BQCV, and SBV virus detections. Individual infections are denoted by solid circles (i.e. samples with more similar virus compositions are closer). Size of points indicate frequency of viral detections. Mean of infected species denoted by open triangles. ** Significance from the’anova.cca’ test to indicate differences among insect types with 1,000 permutations (p < 0.021)

Canonical Analysis of Principal Coordinates

BQCV 2

1 size 1 2 3 IAPV 4 5 0 CAP1

Experiments

Early-summer SBV Late-summer Mid-summer -1

-2 DWV

-1 0 1 2 CAP2

Figure 3. 2. Distance-based redundancy analysis (dbRDA) was performed. The virus prevalence of each sample collected on early- mid- and late-summer were visualized using canonical analysis of principal coordinates (CAP) with capscale function. CAP1 and CAP2 are the first two axes from the constrained analysis of principal coordinates, with the respective amount of variation in the Bray–Curtis. Black arrows correspond with DWV, IAPV, BQCV, and SBV virus detections. Individual infections are denoted by solid circles (i.e. samples with more similar virus compositions are closer). Size of points indicate frequency of viral detections. Mean of infected species denoted by open triangles. ** Significance from the’anova.cca’ test to indicate differences among season with 1,000 permutations (p < 0.021)

Table 3. 1. Percentage of insects with positive detections of viruses collected from different flowers on early-summer (July-182018) from pollinator garden, UNL, Lincoln, NE.

aPollen collected from flowers, bee’s corbicula, and hives by trap.

Table 3. 2. Percentage of insects with positive detections of viruses collected from different flowers on mid-summer (July-31-2018) from pollinator garden, UNL, Lincoln, NE.

aPollen collected from flowers, bee’s corbicula, and hives by trap.

Table 3. 3. Percentage of insects with positive detections of viruses collected from different flowers on late-summer (Aug-21-2018) from pollinator garden, UNL, Lincoln, NE.

aPollen collected from flowers, bee’s corbicula, and hives by trap.

0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) SBV(%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) IAPV (%) IAPV 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) BQCV(%)

. Number (percent) of of positive Numbersamples(percent) 33.3%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) (16.7%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 2018) 2(2.4%) DWV (%)DWV - 1 ( 1 1 18 - n 2 8 1 2 3 2 1 1 2 1 7 1 3 3 6 2 1 2 1 1 15 17 82 entrance from summer (July summer - Collected Collected Hive Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower early centage of DWV, BQCV, IAPV, and SBV infected bees and insects and insects bees of centage SBV BQCV, infected IAPV, DWV, and on Species mellifera mellifera impatiens griseocollis virginica communis desponsus bimaculatus comptoides rotundata ligatus confusus verticalis annulatus pallidefulva jamaicensis pensylvanicus pennsylvanicus trifurcata japonica Genus 2018) - 18 - Apis Apis Bombus Bombus Xylocopa Melissoides Melissoides Melissoides Melissoides Megachile Halictus Halictus Hylaeus Hylaeus Formica Sphex Sphex Chauliognathus Cerotoma Popillia Family Apidae Apidae Apidae Apidae Apidae Apidae Apidae Apidae Apidae Megachilidae Halictidae Halictidae Colletidae Colletidae Formicidae Sphecidae Sphecidae Cantharidae Chysomelidae Scarabaeidae Rhopalidae Blissidae r collections (July collections r Species identification, sample size, and per size, sample and identification, Species . 4

summe insects sampledinsects - Order To ta l Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Coleoptera Coleoptera Coleoptera Hemiptera Hemiptera Early Table Table 3. collected from apiary the pollinator garden UNL and

0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) SBV(%) es and insects and es insects 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) IAPV (%) IAPV 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 4(4.9%) 1(100%) 1(33.3%) 1(14.3%) 1(33.3%) BQCV(%)

Number (percent) of of positive Numbersamples(percent) 2018). - 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 1(6.7%) 1(7.1%) 3(3.6%) DWV (%)DWV 1(33.3%) 31 - n 5 1 3 7 1 1 1 1 1 2 1 2 1 4 3 6 1 1 15 14 12 83 summer (July summer from - Collected Collected mid Hive entranceHive Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Species mellifera mellifera impatiens griseocollis pennsylvanicus bimaculatus menuachus moesta mendica texanus angelicus splendens ligatus pallidefulva jamaicensis cervinus vittatum Genus 2018) - inator garden and apiary garden inator on and 31 Apis Apis Bombus Bombus Bombus Melissoides Melissoides Nomada Coelioxys Megachile Agapostemon Agapostemon Agapostemon Halictus Formica Sphex Pinalitus Acalymma - Family Apidae Apidae Apidae Apidae Apidae Apidae Apidae Apidae Megachilidae Megachilidae Halictidae Halictidae Halictidae Halictidae Formicidae Sphecidae Miridae Chysomelidae Hesperiidae Sphingidae Pieridae Species identification, sample size, and percentage of DWV, BQCV, IAPV, and SBV infected be ofpercentage SBV BQCV, infected size, IAPV, sample and DWV, and identification, Species

. 5

summer collections (July collections summer - Order Mid Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Coleopteran Coleopteran Lepidoptera Lepidoptera Lepidoptera sampledinsects Total Table Table 3. collected from the poll UNL

0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 1(10%) 1(1.9%) SBV(%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 1(10%) 1(50%) 3(5.8%) IAPV (%) IAPV 1(14.3%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 1(1.9%) 1(14.3%) BQCV(%) Number (percent) of of positive Numbersamples(percent) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 2(20%) 3(60%) 1(20%) 1(50%) DWV (%)DWV 7(13.5%) n 5 7 5 1 1 1 1 4 2 7 1 7 52 10

). entrance from 2018 - Collected Collected 21 Hive Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower Flower - (Aug Species summer - mellifera mellifera impatiens griseocollis affinis mendica brevis pruina splendens ligatus pennsylvanicus lintneriana late on on Genus 2018) Bombus Bombus Bombus Megachile Megachile Megachile Halictus Chauliognathus Cosmopepla - Apis Apis Agapostemon 21 - (Aug Family Megachilidae Megachilidae Megachilidae Halictidae Halictidae Cantharidae Pentatomidae Hesperiidae Apidae Apidae Apidae Apidae Apidae collections collections Species identification, sample size, and percentage of DWV, BQCV, IAPV, and SBV infected bees and insects collected and insects bees ofpercentage SBV BQCV, infected size, IAPV, sample and DWV, and identification, Species

. Order summer summer sampledinsects - otal otal able 3. 6 Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Hymenoptera Coleoptera Hemiptera Lepidoptera Late T T from pollinator garden UNL and apiary the

Table 3. 7. A list of the 12 targeted plant species with short (S), medium (M) and long (L) blooming times and their observed phenology during early, mid, and late summer in 2018.

Plant Bloom Period Bloom Early summer Middle summer Late summer Common name Specific name time June mid-July mid-July mid-Aug mid-Aug Sep Buttonbush Cephalanthus occidentalis S Joe Pye weed Eupatorium purpureum S Blazing Star Liatris spp. S Wild bergamot Monarda fistulosa M Rattlesnake Master Eryngium yuccifolium M Brown Eyed Susan Rudbeckia spp. M Sneezeweed Helenium autumnale M Blue Mist Spirea Caryopteris clandonensis L Green-head Coneflower Rudbeckia laciniata L Blue Russian Sage Perovskia atriplicifolia L Purple Coneflower Echinacea purpurea L Catmint Nepeta cataria L Bolded plant names indicate species that were attractive to foraging honey bees.

Table 3. 8. The variation in virus prevalence on insect group, season times, and, blooming time of flowers from adonis analysis test.

Bray-Curtis R2 P-value Insect group 0.32659 0.025 Season times (Experiments) 0.25494 0.031 Blooming time of flower 0.18513 0.131 Bold P-values indicate significant comparisons from adonis test (P < 0.05). The variances (r2) and P- values were calculated using analysis of dissimilarity (adonis)

References cited

Anderson, M. J., & Willis, T. (2003). Canonical analysis of principal coordinates: a useful method of constrained ordination for ecology. Ecology, 84(2), 511–525. Aparicio, F., Sánchez-Pina, M. A., Sánchez-Navarro, J. A., & Pallás, V. (1999). Location of prunus necrotic ringspot ilarvirus within pollen grains of infected nectarine trees: evidence from RT-PCR, dot-blot and in situ hybridisation. European Journal of Plant Pathology, 105(6), 623–627. Ascher, J. S. & Pickering, J. (2011). Bee species guide. Discover Life. Retrieved from https://www.discoverlife.org. Ascher, J. S., Rozen Jr, J. G., & Schuh, T. (2008). Apoidea species guide. Discover Life. Retrieved from http://www. discoverlife.org. Arduser, M. 2018. Bees of the tallgrass prairie region and greater Midwest. Bigot, D., Dalmon, A., Roy, B., Hou, C., Germain, M., Romary, M., Deng, S., Diao, Q., Weinert, L. A., Cook, J. M., Herniou, E. A., & Gayral, P. (2017). The discovery of halictivirus resolves the Sinaivirus phylogeny. Journal of General Virology, 98(11), 2864–2875. Blanchet, F. G., Legendre, P. & Borcard, D. (2008). Forward selection of explanatory variables. Ecology, 89(9), 2623–2632. Boncristiani, H., Li, J., Evans, J. D., Pettis, J., & Chen, Y. (2011). Scientific note on PCR inhibitors in the compound eyes of honey bees, Apis mellifera. Apidologie, 42(2), 457–460. Celle, O., Blanchard, P., Olivier, V., Schurr, F., Cougoule, N., Faucon, J. P., & Ribiere, M. (2008). Detection of chronic bee paralysis virus (CBPV) genome and its replicative RNA form in various hosts and possible ways of spread. Virus Research, 133(2), 280–284. Chen, Y. P., Pettis, J. S., Collins, A., Feldlaufer, M. F. (2006). Prevalence and transmission of honey bee viruses. Applied and environmental microbiology, 72(1), 606–611. Chen, Y., Zhao, Y., Hammond, J., Hsu, H. T., Evans, J., & Feldlaufer, M. (2004). Multiple virus infections in the honey bee and genome divergence of honey bee viruses. Journal of invertebrate pathology, 87(2–3), 84–93. Clarke, K. R., Somerfield, P. J., & Chapman, M. G. (2006). On resemblance measures for ecological studies, including taxonomic dissimilarities and a zero-adjusted Bray– Curtis coefficient for denuded assemblages. Journal of Experimental Marine Biology and Ecology, 330(1), 55–80. Daughenbaugh, K. F., Martin, M., Brutscher, L. M., Cavigli, I., Garcia, E., Lavin, M., Flenniken, M. L. (2015). Honey bee infecting Lake Sinai viruses. Viruses, 7(6), 3285–3309. Dixon, P. (2003). VEGAN, a package of R functions for community ecology. Journal of Vegetation Science, 14(6), 927–930. Dolezal, A. G., Hendrix, S. D., Scavo, N. A., Carrillo-Tripp, J., Harris, M. A., Wheelock, M. J., O’Neal, M. E., & Toth A. L. (2016). Honey bee viruses in wild bees: viral prevalence, loads, and experimental inoculation. PloS one, 11(11), e0166190.

Flenniken, M. L. (2014). Honey bee-infecting plant virus with implications on honey bee colony health. MBio, 5(2), e00877–14. Graystock, P., Goulson, D., & Hughes, W. O. (2015). Parasites in bloom: flowers aid dispersal and transmission of pollinator parasites within and between bee species. Proc. R. Soc. B, 282(1813), 20151371. Hung, A. C. F. (2000). PCR detection of Kashmir bee virus in honey bee excreta. Journal of Apicultural Research, 39(3–4), 103–106. Li, J. L., Cornman, R. S., Evans, J. D., Pettis, J. S., Zhao, Y., Murphy, C. W., Peng, W. J., Wu, J., Hamilton, M. C., Boncristiani, H. F., Zhou, L., Hammond, J. H., & Chen, Y. P. (2014). Systemic spread and propagation of a plant-pathogenic virus in European honey bees, Apis mellifera. MBio, 5(1), e00898-13. Li, J., Peng, W., Wu, J., Strange, J. P., Boncristiani, H., & Chen, Y. (2011). Cross-species infection of deformed wing virus poses a new threat to pollinator conservation. Journal of economic entomology, 104(3), 732–739. Levitt, A. L., Singh, R., Cox-Foster, D. L., Rajotte, E., Hoover, K., Ostiguy, N., & Holmes, E. C. (2013). Cross-species transmission of honey bee viruses in associated arthropods. Virus research, 176(1–2), 232–240. McMenamin, A. J., & Genersch, E. (2015). Honey bee colony losses and associated viruses. Current Opinion in Insect Science, 8, 121–129. McMenamin, A. J., & Flenniken, M. L. (2018). Recently identified bee viruses and their impact on bee pollinators. Current opinion in insect science, 26, 120–129. McMenamin, A., Daughenbaugh, K., Parekh, F., Pizzorno, M., & Flenniken, M. (2018). Honey bee and bumble bee antiviral defense. Viruses, 10(8), 395. Martin, S., Highfield, A., Brettell, L., Villalobos, E., Budge, G., Powell, M., & Schroeder, D. (2012). Global honey bee viral landscape altered by a parasitic mite. Science, 336 (6086), 1304–1306. Meeus, I., Pisman, M., Smagghe, G., & Piot, N. (2018). Interaction effects of different drivers of wild bee decline and their influence on host-pathogen dynamics. Current opinion in insect science, 26, 136–141. Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., Minchin, P. R., O’hara, R. B., Simpsom G. L., Solymos P., Stevens M. H. H., Szoecs, E. & Wagner, H. (2011). vegan: Community ecology package. R package version, 117–118. Pavoine, S., Dufour, A. B., & Chessel, D. (2004). From dissimilarities among species to dissimilarities among communities: a double principal coordinate analysis. Journal of theoretical biology, 228(4), 523–537. Santamaria, J., Villalobos, E. M., Brettell, L. E., Nikaido, S., Graham, J. R., & Martin, S. (2018). Evidence of Varroa-mediated deformed wing virus spillover in Hawaii. Journal of invertebrate pathology, 151, 126–130. Singh, R., Levitt, A. L., Rajotte, E. G., Holmes, E. C., Ostiguy, N., vanEngelsdorp, D., lan Lipkin, W., dePamphilis, C. W., Toth, A. L., & Cox-Foster, D. L. (2010). RNA viruses in hymenopteran pollinators: evidence of inter-taxa virus transmission via pollen and potential impact on non-Apis hymenopteran species. PloS one, 5(12), e14357. Sébastien, A., Lester, P. J., Hall, R. J., Wang, J., Moore, N. E., & Gruber, M. A. M. (2015). Invasive ants carry novel viruses in their new range and form reservoirs for a honey bee pathogen. Biology Letters, 11(9), 20150610.

Tehel, A., Brown, M. J., & Paxton, R. J. (2016). Impact of managed honey bee viruses on wild bees. Current opinion in virology, 19, 16–22. Williams, P. H., Thorp, R.W., Richardson, L. L., & Colla, S.R. (2014). Bumble bees of North America: an identification guide. Princeton University Press. Yañez, O., Zheng, H. Q., Hu, F. L., Neumann, P., & Dietemann, V. A. (2012). Scientific note on Israeli acute paralysis virus infection of Eastern honeybee Apis cerana and vespine predator Vespa velutina. Apidologie, 43(5), 587– 58.