Collection: Bee AwareEducator guide

Honeybees (Apis mellifera) are incredibly important pollinators; they, along with other

organisms like wasps, moths, ants, and bats, are responsible for helping the reproduction of

over three quarters of the world's plants. They are also unique in many ways: they are eusocial

insects, which means that they live in a group, work together to care for offspring, have

overlapping generations, and have a division of reproduction & labor.

Researchers use the honeybee to study many things, including learning and memory (how do

bees remember where necar is located?), communication (how do they use waggle dances to

tell other bees where to find flowers?), and the evolution of social behavior (why do they have

only one breeding female in a large group?)

Honeybees have been called the world's third most economically important livestock;

however, you and your students are probably aware of “colony collapse disorder,” a term used

to describe the decline in bee populations.

This collection lets you help your students explore the evolution of eusocial behavior, what a

honeybee colony looks like, what honeybee research is helping us to understand, what may be

contributing to the decline of the honeybees, and more. It includes two Science in the

Classroom annotated articles as well as suggested articles and multimedia resources.

Table of Contents

1. Background

2. Honeybees and learning

a. Teacher guide for: “A caffeine jolt gives bees a buzz to remember”

b. Science article: “Caffeine in floral nectar enhances a pollinator's memory of reward”

3. Pollination and Decline of Honeybees

a. Teacher guide for: “The bee, the mite, and the virus”

b. Science article: “Global honey bee viral landscape altered by a parasitic mite”

c. Other resources

Background

The genetics of society: http://www.the-scientist.com/?articles.view/articleNo/41704/title/The-Genetics-of-Society/

A feature article in the January 2015 issue of The Scientist, this review from Claire Asher and Seirian

Sumner examines research into the molecular evolution of social behavior, succinctly describing eusociality and

current research.

Being queen: http://www.pbs.org/wgbh/nova/nature/being-queen.html

This feature from NOVA, written by Peter Tyson, explores the role of a queen in a colony of eusocial insects,

providing a clearly written overview of division of labor, life cycle, the role of pheromones, and more.

People, plants, and pollinators: https://youtu.be/rmL_XTrPOMw

A National Geographic Live video featuring entomologist Dino Martins explaining the importance of pollinators,

as well as giving an overview of the danger pollinators are facing. Honeybees are featured.

Honeybees and Learning

A caffeine jolt gives bees a buzz to remember

Teacher Guide

Caffeine in Floral Nectar Enhances a Pollinator's Memory of Reward. Geraldine Wright et al. annotated by Tara Bracken

Table of Contents:

ARTICLE-SPECIFIC MATERIALS

a. Student Learning Goals

b. Connect to Learning Standards

c. Summary of the Article for the Teacher

d. Discussion Questions

e. Related Article

Student Learning Goals

Connections to the nature of science from the article

This paper links pollinator behavior with defense compounds produced by flowering plants.

The results of this study have important implications for plant-pollinator interactions and how these

interactions can drive selection in plant populations.

The importance of this scientific research

This study shows that compounds produced by plants can manipulate pollinator behavior and

memory in order to improve reproductive success. Additionally, it implies that pollinator behavior

can drive selection within plant populations.

The actual science involved

Neurobiology

Animal learning behavior

Liquid chromatography-mass spectrometry

Connect to Learning Standards:

The Next Generation Science Standards

Practice 1: Asking questions (for science) and defining problems (for engineering)

Practice 2: Developing and using models

Practice 3: Planning and carrying out investigations

Practice 4: Analyzing and interpreting data

Practice 6: Constructing explanations (for science) and designing solutions (for engineering)

Practice 7: Engaging in argument from evidence

Practice 8: Obtaining, evaluating, and communicating information

The AP Biology Standards

Practice 1: The student can use representations and models to communicate scientific

phenomena and solve scientific problems.

Practice 3: The student can engage in scientific questioning to extend thinking or to guide

investigations within the context of the AP course.

Practice 4: The student can plan and implement data collection strategies appropriate to a

particular scientific question.

Practice 5: The student can perform data analysis and evaluation of evidence.

Practice 6: The student can work with scientific explanations and theories.

Practice 7: The student is able to connect and relate knowledge across various scales, concepts,

and representations in and across domains.

Common Core English Language Arts

11-12.1: Cite specific textual evidence to support analysis of science and technical texts, attending to important distinctions the author makes and to any gaps or inconsistencies in the account.

11-12.2: Determine the central ideas or conclusions of a text; summarize complex concepts, processes, or information presented in a text by paraphrasing them in simpler but still accurate terms.

11-12.3: Follow precisely a complex multistep procedure when carrying out experiments, taking measurements, or performing technical tasks; analyze the specific results based on explanations in the text.

11-12.4: Determine the meaning of symbols, key terms, and other domain-specific words and phrases as they are used in a specific scientific or technical context relevant to grades 11–12 texts and topics.

11-12.6: Analyze the author's purpose in providing an explanation, describing a procedure, or discussing an experiment in a text, identifying important issues that remain unresolved.

11-12.8: Evaluate the hypotheses, data, analyses, and conclusions in a science or technical text, verifying the data when possible and corroborating or challenging conclusions with other sources of information.

Summary of the Article for the Teacher: It is recommended that this not be used by students in place of reading the article. General Overview: Many drugs regularly used by humans, including caffeine and nicotine, are produced by plants as toxic defenses against herbivores. These compounds may deter mammals from eating those plants, but how do they affect the pollinating insects that help these plants reproduce? Because these pollinators play such an important role in flowering plant reproduction, do they affect the production of these toxic defense compounds in plants? Caffeine-producing plants like coffee and citrus plants produce more flowers and fruits when pollinated by bees, improving their reproductive success. Caffeine in the nectar of these plants exists at lower concentrations than in their vegetative material — enough to affect bee neuronal function without being bitter-tasting or toxic. Caffeine in plant nectar stimulates bee neurons, increasing their ability to remember the reward of sugary nectar derived from visiting the caffeinated plant. As a result, the bees visit the same plants more often, improving the reproductive success of that plant. Together, these results show that plant compounds can affect pollinator behavior. In turn, pollinator behavior can also drive selection within plant populations for the production of defense compounds at levels that will have an effect on, but not deter, pollinators. Topics Covered:

Animal behavior

Memory formation

Neuron action potential/neuroelectrophysiology

Liquid chromatography-mass spectrometry

Why this research is important: Understanding how associative learning behaviors affect interactions among natural partners like pollinators and flowering plants gives us important information on how such partnerships may drive selection of a species. Organisms within an ecosystem adapt and evolve to each other’s behavior, producing compounds to ward off predators or to encourage mutualistic behavior by symbionts. It is known that caffeine present in plant vegetative material serves to discourage herbivory; however, it is unknown whether caffeine present in plant nectar plays an ecological role.

This study showed that caffeine present in plant nectar affects pollinator learning behavior, thereby improving pollinator fidelity and increasing reproductive success. Further, this affect on pollinator associative learning in turn drives selection of the concentration of the compound specifically in plant reproductive tissues to levels that are pharmacologically active but not repulsive to pollinators. The implications of this research are that interactions between species can be very complex and can direct the evolution of a species. A thorough understanding such complexities is crucial to understand related issues, such as optimizing effective agricultural practices and anticipating and mitigating the effects of human actions on ecosystems. Methods used in the Research:

Liquid chromatography-mass spectrometry

Whole-cell patch clamp electrophysiology

Classical conditioning Conclusions:

Alkaloids like caffeine are not just defense compounds; they also increase reproductive success by pharmacologically manipulating pollinator behavior.

Bees simultaneously exposed to caffeine, floral scent, and a reward (nectar) are more likely to associate that scent with the reward and return to that plant.

Areas of Further Study:

Does caffeine have a similar effect on associative learning of other important pollinator species?

Do non–caffeine-producing plants have compounds that similarly increase pollinator fidelity, or do they rely on different mechanisms to draw pollinators and ensure reproductive success?

Discussion Questions: 1. What are plant defense compounds and how have they been used by humans? What are some examples of plant defense compounds other than caffeine that you might encounter in your daily life? 2. What is a selective advantage? 3. Why did the authors of the paper expect to find caffeine in the nectar of the flowering plants tested? 4. Explain “classical conditioning” as used by the study’s authors. How would this method help reveal the effect caffeine has on memory formation in honey bees? 5. What is an action potential firing threshold?

Discussion questions associated with the figures Fig. 1:

1. Describe the technique the authors used to measure caffeine concentrations in Figure 1. What could be some other potential uses for this technique?

Fig. 2:

1. How did adding caffeine affect honey bees’ ability to learn? (Be descriptive! For example, did it help with short- or long-term memory? Did it help them learn faster, cause them to learn more slowly, or neither?)

Fig. 3:

1. What technique did the authors use to obtain the trace recordings in Figure 3? What does this technique measure?

2. What is a representative sample? Why would a representative sample be shown instead of the sum of all the data available?

3. Why were the study’s authors interested to find that adding caffeine to honey bee neurons

pushed the membrane potential toward the action potential firing threshold?

4. Why did adding DPCPX eliminate the changes in holding current and membrane potential induced by caffeine? What did the authors learn as a result of this observation?

Fig. 4:

1. What is the significance of a caffeine concentration of 1 mM? How does that concentration correlate to the concentrations observed in plant nectar in Figure 1?

2. Explain the conclusions drawn by authors on the effect of honey bees on flowering plant selection based on the data presented in Figure 4. Do you agree with their reasoning? Why or why not? What evidence presented in this paper confirms their conclusion or calls it into question?

Related Article: Bees Buzzing on Caffeine

A feature from National Geographic describing the Science article

http://news.nationalgeographic.com/news/2013/03/130308-bees-caffeine-animal-behavior-science/

Caffeine in Floral Nectar Enhances aPollinator’s Memory of RewardG. A. Wright,1* D. D. Baker,2 M. J. Palmer,3 D. Stabler,1,2 J. A. Mustard,4 E. F. Power,1,2

A. M. Borland,2 P. C. Stevenson5,6

Plant defense compounds occur in floral nectar, but their ecological role is not well understood.We provide evidence that plant compounds pharmacologically alter pollinator behavior byenhancing their memory of reward. Honeybees rewarded with caffeine, which occurs naturally innectar of Coffea and Citrus species, were three times as likely to remember a learned floral scentas were honeybees rewarded with sucrose alone. Caffeine potentiated responses of mushroombody neurons involved in olfactory learning and memory by acting as an adenosine receptorantagonist. Caffeine concentrations in nectar did not exceed the bees’ bitter taste threshold,implying that pollinators impose selection for nectar that is pharmacologically active but notrepellent. By using a drug to enhance memories of reward, plants secure pollinator fidelity andimprove reproductive success.

Many drugs commonly consumed by hu-mans are produced by plants as a formof toxic defense against herbivores

(1, 2). Although plant-derived drugs like caffeineor nicotine are lethal in high doses (3–5), at lowdoses they have pharmacological effects on mam-malian behavior. For example, low doses of caf-

feine are mildly rewarding and enhance cognitiveperformance and memory retention (6). Caffeinehas been detected in low doses in the floral nectarand pollen of Citrus (7), but whether it has anecological function is unknown.

Two caffeine-producing plant genera, Citrusand Coffea, have large floral displays with strongscents and produce more fruits and seeds whenpollinated by bees (8, 9). If caffeine confers a se-lective advantage when these plants interact withpollinators, we might expect it to be commonlyencountered in nectar. We measured caffeine inthe nectar of three species of Coffea (C. canephora,C. arabica, and C. liberica) and four species ofCitrus (C. paradisi, C. maxima, C. sinensis, andC. reticulata) using liquid chromatography–massspectrometry (10) (fig. S1A). When caffeine waspresent, its concentration ranged from 0.003

to 0.253 mM. The median caffeine concentra-tion in both genera was not significantly dif-ferent (Fig. 1A, Mann-Whitney, Z = –1.09, P =0.272). Caffeine was more common in the nec-tar of C. canephora than in that of C. arabicaor C. liberica (Coffea: logistic regression c2

2 =11.1, P = 0.004); it was always present in Citrusnectar. The mean total nectar sugar concentra-tion ranged from 0.338 to 0.843 M (Fig. 1B; seefig S1B for individual sugars). Caffeine concen-tration in nectar did not correlate with total sugarconcentration (Pearson’s r = 0.063, P = 0.596).

We hypothesized that caffeine could affectthe learning and memory of foraging pollinators.To test this, we trained individual honeybees toassociate floral scent with 0.7 M sucrose andseven different concentrations of caffeine andtested their olfactory memory. Using a methodfor classical conditioning of feeding responses(proboscis extension reflex) (11), we trained beesfor six trials with 30 s between each pairing ofodor with reward. This intertrial interval ap-proximated the rate of floral visitation exhibitedby honeybees foraging from multiple flowers ona single Citrus tree (see methods). The presenceof low doses of caffeine in reward had a weakeffect on the rate of learning (Fig. 2A), but it hada profound effect on long-term memory. Whenrewarded with solutions containing nectar levelsof caffeine, three times as many bees rememberedthe conditioned scent 24 hours later and re-sponded as if it predicted reward (Fig. 2B, lo-gistic regression, c7

2 = 41.9, P < 0.001). Twice asmany bees remembered it 72 hours later (Fig. 2C).This improvement in memory performance wasnot due to a general increase in olfactory sensi-tivity resulting from caffeine consumption (fig.S2A). Indeed, the effect of caffeine on long-term

1Centre for Behaviour and Evolution, Institute of Neuro-science, Newcastle University, Newcastle upon Tyne NE1 7RU,UK. 2School of Biology, Newcastle University, Newcastle uponTyne NE1 7RU, UK. 3Division of Neuroscience, Medical Re-search Institute, Ninewells Medical School, University of Dundee,Dundee DD1 9SY, UK. 4School of Life Sciences, Arizona StateUniversity, Tempe, AZ 85287, USA. 5Jodrell Laboratory, RoyalBotanic Gardens, Kew, Surrey TW9 3AB, UK. 6Natural ResourcesInstitute, University of Greenwich, Chatham, Kent ME4 4TB, UK.

*To whom correspondence should be addressed. E-mail:jeri.wright@ncl.ac.uk

Fig. 1. (A) Caffeine concentration in Coffea and Citrus spp. and a cup ofinstant coffee. Caffeine concentration depended on species within eachgenus (Coffea: Kruskal-Wallis, c2

2 = 28.1, P < 0.001; Citrus: Kruskal-Wallis,c2

2 = 6.98, P = 0.030); C. canephora had the highest mean concentration ofall species sampled. (B) The sum of the concentration of sucrose, glucose,and fructose (total nectar sugars) depended on species (one-way analysis of

variance: F5, 161 = 4.64, P < 0.001) and was greatest in Citrus maxima andhybrids (citron, lemons, clementines). [C. can., Coffea canephora, N = 34;C. lib., Coffea liberica, N = 31; C. arab., Coffea arabica, N = 27; C. par., Citrusparadisi and hybrids, Ncp = 17; C. max., Citrus maxima and hybrids, N = 5;C. sin. and C. ret., Citrus sinensis and Citrus reticulata, NCS = 7, NCR = 5 (datafor these two species were pooled).] Mean responses T SE.

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Fig. 2. (A) The rate of learning of bees conditioned with an odor stimulus paired with a 0.7 Msucrose reward containing caffeine. The rate of learning was slightly greater for the bees fedcaffeine in reward during conditioning (logistic regression, c1

2 = 4.85, P = 0.028). N ≥ 79 for allgroups. (B) Memory recall test for odors at 10 min (white bars) or 24 hours (red bars) after beeshad been trained as in (A). Bright red bars indicate that the response at 24 hours was significantlydifferent from the control (0.7 M sucrose) (least-squares contrasts: P < 0.05); dark red bars werenot significantly different. Nectar levels of caffeine are indicated by hatching. N > 79 for eachgroup. (C) Bees fed 0.1 mM caffeine in sucrose (orange bars) were more likely to remember theconditioned odor than sucrose alone (white bars) (logistic regression, c1

2 = 9.04, P < 0.003) at24 hours and 72 hours after conditioning. N = 40 per group.

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Fig. 3. The effect of caffeine on Kenyon cells. (A andB) Example traces from aKC in intact honeybee brain recorded under voltage-clamp [(A), VH = –73 mV)and current-clamp [(B), at resting VM), showing the increase in IM and de-polarization evoked by bath application of caffeine (100 mM) and subsequentreversal by the nAChR antagonist d-TC (500 mM). (C and D) Mean datashowing the reversal by d-TC (500 mM) of the effect of caffeine (Caff; 100 mM)on IM [(C);N= 6, t5 = 4.03, P= 0.010; t5 = 4.07, P= 0.010] and VM [(D);N= 6,t5 = 34.1, P < 0.001; t5 = 12.0, P < 0.001]. (E and F) Comparison of the mean

effects of caffeine and DPCPX on IM [(E); Caff: N = 10, t9 = 3.84, P = 0.004;DPCPX: N = 6, t5 = 4.04, P = 0.010] and VM [(F) Caff: N = 6, t5 = 34.1, P <0.001; DPCPX: N = 6, t5 = 3.39, P = 0.019]. (G and H) Example traces [(G);rising phase shown on an expanded time scale below] andmean data [(H); rateof rise:N = 6, t5 = 2.20, P= 0.079; tdecay:N = 9, t8 = 3.54, P = 0.008] showingthat DPCPX (100 nM) and caffeine (100 mM) slowed the decay and, in six ofnine KCs, potentiated the fast component of the response evoked by exogenousACh. (Student’s paired t test used in all comparisons.) Mean responses T SE.

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olfactory memory in bees was greater than thatproduced by high concentrations of sucrose whenthe same experimental methods were used (e.g.,2.0 M, fig. S2B).

Caffeine’s influence on cognition in mam-mals is in part mediated by its action as an aden-osine receptor antagonist (6). In the hippocampalCA2 region, inhibition of adenosine receptorsby caffeine induces long-term potentiation (12),a key mechanism of memory formation (13). TheKenyon cells (KCs) in mushroom bodies of theinsect brain are similar in function to hippocam-pal neurons: They integrate sensory input duringassociative learning, exhibit long-term potentiation,and are involved in memory formation (14–16).To determine whether nectar-caffeine doses affectmushroom body function, we made whole-KCrecordings in the intact honeybee brain. Caffeine(100 mM) evoked a small increase in the holdingcurrent (IM) and depolarized KC membrane po-tential (VM) toward the action potential firingthreshold, by increasing nicotinic acetylcholinereceptor (nAChR) activation (Fig. 3, A to D).To determine whether the observed effects ofcaffeine were due to interactions with adeno-sine receptors, we applied the adenosine re-ceptor antagonist DPCPX and observed that itsimilarly increased IM and depolarized VM, butto a lesser extent (Fig. 3, E and F). Both caffeineand DPCPX affected KC response kinetics evokedby brief, local application of ACh, increasing theactivation rate and slowing the decay (Fig. 3, Gand H). Our data show that caffeine modulatescholinergic input via a postsynaptic action, butcould act via presynaptic adenosine receptors topotentiate ACh release (17). The resulting increasein KC excitability should lead to an increasedprobability of action potential firing in responseto sensory stimulation (18), thereby facilitatingthe induction of associative synaptic plasticity inKCs (19). The enhanced activation of KCs mayalso facilitate plasticity at synapses with mush-

room body extrinsic neurons (20), which exhibitspike-timing–dependent plasticity (21). In thisway, a “memory trace” could be formed for theodor associated with reward during and afterconditioning (22, 23).

Caffeine is bitter tasting to mammals and isboth toxic (24) and repellent to honeybees athigh concentrations (25, 26). If bees can detectcaffeine, theymight learn to avoid flowers offeringnectar containing it (27).We found that honeybeeswere deterred from drinking sucrose solutionscontaining caffeine at concentrations greater than1 mM (Fig. 4); they also have neurons that detectcaffeine in sensilla on their mouthparts (fig. S3).However, nectar concentrations did not exceed0.3 mM (0.058 mg/ml), even though levels ofcaffeine in vegetative and seed tissues of Coffeahave been reported to be as great as 24 mg/ml(28). This implies that pollinators drive selectiontoward concentrations of caffeine that are notrepellent but still pharmacologically active.

Our data show that plant-produced alkaloidslike caffeine have a role in addition to defense:They can pharmacologically manipulate a pol-linator’s behavior. When bees and other polli-nators learn to associate floral scent with foodwhile foraging (29), they are more likely to visitflowers bearing the same scent signals. Suchbehavior increases their foraging efficiency (30)while concomitantly leading to more effective pol-lination (31, 32). Our experiments suggest thatby affecting a pollinator’s memory, plants reapthe reproductive benefits arising from enhancedpollinator fidelity.

References and Notes1. R. J. Sullivan, E. H. Hagen, P. Hammerstein, Proc. Biol.

Sci. 275, 1231 (2008).2. J. B. Harborne, Introduction to Ecological Biochemistry

(Academic Press, London, ed. 4, 1993).3. R. G. Hollingsworth, J. W. Armstrong, E. Campbell, Nature

417, 915 (2002).

4. M. Okamoto, T. Kita, H. Okuda, T. Tanaka, T. Nakashima,Pharmacol. Toxicol. 75, 1 (1994).

5. T. Rudolph, K. Knudsen, Acta Anaesthesiol. Scand. 54,521 (2010).

6. A. Nehlig, Neurosci. Biobehav. Rev. 23, 563(1999).

7. J. A. Kretschmar, T. W. Baumann, Phytochemistry 52, 19(1999).

8. T. H. Ricketts, G. C. Daily, P. R. Ehrlich,C. D. Michener, Proc. Natl. Acad. Sci. U.S.A. 101, 12579(2004).

9. D. W. Roubik, Nature 417, 708 (2002).10. Materials and methods are available in the supplementary

materials in Science Online.11. M. E. Bitterman, R. Menzel, A. Fietz, S. Schafer,

J. Comp. Psychol. 97 107–119 (1983).12. S. B. Simons, D. A. Caruana, M. L. Zhao, S. M. Dudek,

Nat. Neurosci. 15, 23 (2012).13. R. G. M. Morris, E. Anderson, G. S. Lynch, M. Baudry,

Nature 319, 774 (1986).14. M. Heisenberg, Nat. Rev. Neurosci. 4, 266

(2003).15. S. Oleskevich, J. D. Clements, M. V. Srinivasan,

J. Neurophysiol. 78, 528 (1997).16. N. J. Strausfeld, L. Hansen, Y. S. Li, R. S. Gomez, K. Ito,

Learn. Mem. 5, 11 (1998).17. B. Sperlágh, E. S. Vizi, Curr. Top. Med. Chem. 11, 1034

(2011).18. J. Perez-Orive et al., Science 297, 359 (2002).19. P. Szyszka, A. Galkin, R. Menzel, Front. Syst. Neurosci. 2,

3 (2008).20. R. Menzel, G. Manz, J. Exp. Biol. 208, 4317

(2005).21. S. Cassenaer, G. Laurent, Nature 482, 47

(2012).22. D. S. Galili, A. Lüdke, C. G. Galizia, P. Szyszka,

H. Tanimoto, J. Neurosci. 31, 7240 (2011).23. P. Szyszka et al., J. Neurosci. 31, 7229 (2011).24. A. Detzel, M. Wink, Chemoecology 4, 8 (1993).25. J. A. Mustard, L. Dews, A. Brugato, K. Dey, G. A. Wright,

Behav. Brain Res. 232, 217 (2012).26. N. Singaravelan, G. Nee’man, M. Inbar, I. Izhaki, J. Chem.

Ecol. 31, 2791 (2005).27. G. A. Wright et al., Curr. Biol. 20, 2234 (2010).28. H. Ashihara, A. Crozier, Trends Plant Sci. 6, 407

(2001).29. G. A. Wright, F. P. Schiestl, Funct. Ecol. 23, 841

(2009).30. L. Chittka, A. Gumbert, J. Kunze, Behav. Ecol. 8, 239

(1997).31. R. Hopkins, M. D. Rausher, Science 335, 1090

(2012).32. W. E. Kunin, Ecology 74, 2145 (1993).

Acknowledgments: We thank staff at Centro AgronomicoTropicale de Investigacion et Ensenanza in Costa Rica foraccess to the Coffea collections and at Technological EducationInstitute of Crete for access to Citrus orchards; M. Thomson,K. Smith, F. Marion-Poll, and A. Popescu for help with thedata collection; M. Thompson for beekeeping; and J. Harveyand C. Connolly for project support. This work was fundedin part by the Linnean Society of London and by a UKgovernment Insect Pollinators Initiative grant BB/I000968/1to G.A.W. and a separate grant to C. Connolly (BB/1000313/1).Methods and additional data are available in the onlinesupplementary materials. All data are archived on theNatural Environment Research Council EnvironmentalInformation Data Centre.

Supplementary Materialswww.sciencemag.org/cgi/content/full/339/6124/1202/DC1Materials and MethodsSupplementary TextFigs. S1 to S3References (33–36)

14 August 2012; accepted 21 December 201210.1126/science.1228806

Fig. 4. Bees are morelikely to reject sucrosesolutions containing caf-feine at concentrationsgreater than 1 mM (lo-gistic regression, c4

2 =23.4, P < 0.001; for 0.7and 1.0 M, 1 mM caf-feine versus sucrose posthoc, P < 0.05; for 0.3 M,100 mM caffeine versussucrose post hoc, P <0.05). Bees were less like-ly to drink 0.3 M sucrose(pale pink diamonds) than0.7M (pink circles) or 1.0Msolutions (red triangles) (lo-gistic regression,c2

2=8.69,P= 0.013). Mean responsesT SE. N0.3M = 29, N0.7M =100, N1.0M = 20.

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DOI: 10.1126/science.1228806, 1202 (2013);339 Science et al.G. A. Wright

Caffeine in Floral Nectar Enhances a Pollinator's Memory of Reward

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Pollination and Decline of Honeybees

The bee, the mite, and the virus

Teacher Guide

Global honey bee viral landscape altered by a parasitic mite. Ethel M. Villalobos annotated by Oya Cingöz

ARTICLE-SPECIFIC MATERIALS

a. Student Learning Goals

b. Connect to Learning Standards

c. Summary of the Article for the Teacher

d. Resources for Interactive Engagement

i. Discussion Questions

Student Learning Goals

Connections to the nature of science from the article

Observation and data collection

Identify association between two events based on previous data

Form hypothesis based on the association

Find a system where the hypothesis can be tested

Design experiments The importance of this scientific research

Provide explanation for colony collapse disorder of honeybees worldwide

Understand how a parasite can alter the viral landscape of the host

Monitor the association between hosts, mites, and viruses

The actual science involved

Field collections

Nucleic acid sequencing and quantification

Assessment of genetic diversity

Statistical analysis Connect to Learning Standards:

The Next Generation Science Standards

Practice 1: Asking questions (for science) and defining problems (for engineering)

Practice 2: Developing and using models

The AP Biology Standards

Practice 1: The student can use representations and models to communicate scientific

phenomena and solve scientific problems.

Common Core English Language Arts

11-12.4: Determine the meaning of symbols, key terms, and other domain-specific words and

phrases as they are used in a specific scientific or technical context relevant to grades 11-12 texts

and topics.

Summary of the Article for the Teacher:

It is recommended that this not be used by students in place of reading the article.

General Overview: The large-scale death of honey bee colonies worldwide has caused significant financial and ecological losses over the past decade. Increased prevalence of an invasive parasitic mite, the aptly named Varroa destructor, has been linked to honey bee colony deaths. It turns out that mite infestation is not the whole story, however. Varroa acts as a viral amplifier by augmenting the viral load present in the bees and the colony as a whole, causing large-scale colony collapse. This study examines the association between Varroa infestation in bee colonies in Hawaii and the rise of a single dominant strain of Deformed Wing Virus (DWV). The co-occurrence of this mite and the selected virus strain may provide an explanation to the mysterious deaths of honey bee colonies worldwide.

Topics Covered:

Host-pathogen interactions

Evolution

Parasitism

Virology Methods used in the Research:

Reverse-Transcription Polymerase Chain Reaction (RT-PCR)

High-Resolution Melting analysis (HRM)

Rarefaction analysis

DNA sequencing

Electron microscopy Conclusions: This paper investigates the reason behind large-scale loss of honey bee colonies worldwide by observing the relationship between Deformed Wing Virus (DWV) and the presence of the Varroa mite in bee colonies across the four main islands of Hawaii. Infestation of bee colonies with Varroa first leads to a steep increase in the prevalence of DWV in those colonies, causing augmented viral loads but decreased diversity of viral strains, where one strain becomes dominant and the others are lost over time. The co-occurrence of Varroa and DWV, as well as the selection of a single DWV strain under these conditions, may be the reason many bee colonies around the world have been dying. The study utilizes a very unique situation to track down the changes in the viral diversity and viral load change. The association of mite infestation with honey bee colony loss may not come off as striking. However, because Varroa and the DWV had already spread in Europe and the United States before molecular techniques were so commonly used, there was no real proof of how the mite had caused changes in the viral content of bees. The unfortunate arrival of the mite to Hawaii provided a chance to track the changes in the viral landscape and help understand the process. Areas of Further Study:

Does the selected virus strain replicate better in the mite?

Which properties are present in the dominant virus strain?

Does the association between Varroa infestation and DWV diversity loss hold true in colonies at different locations?

Is it always the same strain that becomes dominant, even in remote geographical locations?

Does widespread pesticide use have any effect on Varroa infestation and DWV spread?

What would be an effective strategy to reduce colony losses worldwide?

An interesting recent finding is that bumblebees, which can also be affected by DWV, seem to carry the same strain that was selected in honey bees: http://www.nature.com/nature/journal/v506/n7488/full/nature12977.html%3FWT.ec_id%3DNATURE-20140220?message-global=remove&WT.ec_id=NATURE-20140220

Resources for Interactive Engagement: Discussion Questions 1. What is the goal of this study? 2. Why is this study important? 3. Are there any other explanations for the observed results? 4. Assuming this is the only reason behind large-scale colony losses, what would you do to prevent

colonies from dying? 5. What are the physiological impacts of DWV? How do you think this affect bees and their ability to

respond to factors such as pesticide exposure, bacterial and fungal diseases, etc.? 6. Colonies with high levels of mites and DWV will most likely have a reduced population in spring

(infected bees do not do well over winter). What impact will this have on the colony?

15. Materials and methods are available as supplementarymaterials on Science Online.

16. I. J. Fairchild et al.; e.i.M.F., Earth Sci. Rev. 75, 105 (2006).17. J. W. Partin, K. M. Cobb, J. F. Adkins, B. Clark,

D. P. Fernandez, Nature 449, 452 (2007).18. H. Cheng et al., Science 326, 248 (2009).19. K. Tachikawa et al., Quat. Sci. Rev. 30, 3716 (2011).20. G. H. Denton et al., Science 328, 1652 (2010).21. E. Bard, R. E. M. Rickaby, Nature 460, 380 (2009).22. P. C. Tzedakis, H. Hooghiemstra, H. Pälike, Quat. Sci. Rev.

25, 3416 (2006).23. P. J. Fawcett et al., Nature 470, 518 (2011).24. Q. Z. Yin, Z. T. Guo, Clim. Past 4, 29 (2008).25. S. Manabe, R. J. Stouffer, J. Geophys. Res. 85, 5529

(1980).26. M. M. Holland, C. M. Bitz, Clim. Dyn. 21, 221 (2003).

27. Q. Z. Yin, A. Berger, Nat. Geosci. 3, 243 (2010).28. K. T. Lawrence, T. D. Herbert, C. M. Brown, M. E. Raymo,

A. M. Haywood, Paleoceanography 24, PA2218 (2009).29. I. Candy et al., Earth Sci. Rev. 103, 183 (2010).30. J. Laskar et al., Astron. Astrophys. 428, 261 (2004).

Acknowledgments: We thank B. Clark, S. Lejau, andJ. Malang of Mulu National Park, as well as J. Partin forassistance in the field. A. Tuen (Universiti Malaysia Sarawak)greatly facilitated fieldwork in Sarawak. N. Sharma andK. Stewart are acknowledged for assistance with stable isotopemeasurements. D. Lund, A. Subhas, and D. Fernandez arethanked for assistance and advice with U-Th dating. J. Eilerprovided access to his facilities at the California Institute ofTechnology. Support for this work was provided by the SwissNational Science Foundation (SNF) and the German

Research Foundation (DFG) through postdoctoral fellowshipsto A.N.M.; by the US NSF through grants ATM-0318445 andATM-0903099 to J.F.A, as well as ATM-0645291 to K.M.C.; andby an Edinburgh University Principal’s Career Development Ph.D.Scholarship to M.O.C.

Supplementary Materialswww.sciencemag.org/cgi/content/full/science.1218340/DC1Materials and MethodsFigs. S1 to S9Tables S1 to S4References (31–39)

22 December 2011; accepted 19 April 2012Published online 3 May 2012;10.1126/science.1218340

Global Honey Bee Viral LandscapeAltered by a Parasitic MiteStephen J. Martin,1* Andrea C. Highfield,2 Laura Brettell,1 Ethel M. Villalobos,3

Giles E. Budge,4 Michelle Powell,4 Scott Nikaido,3 Declan C. Schroeder2*

Emerging diseases are among the greatest threats to honey bees. Unfortunately, where and whenan emerging disease will appear are almost impossible to predict. The arrival of the parasiticVarroa mite into the Hawaiian honey bee population allowed us to investigate changes in theprevalence, load, and strain diversity of honey bee viruses. The mite increased the prevalenceof a single viral species, deformed wing virus (DWV), from ~10 to 100% within honey beepopulations, which was accompanied by a millionfold increase in viral titer and a massive reductionin DWV diversity, leading to the predominance of a single DWV strain. Therefore, the globalspread of Varroa has selected DWV variants that have emerged to allow it to become one of themost widely distributed and contagious insect viruses on the planet.

The emergence of infectious diseases isdriven largely by socioeconomic, environ-mental, and ecological factors (1), and these

diseases have significant effects on biodiversity,agricultural biosecurity, global economies, andhuman health (2, 3). The honey bee is one of themost economically important insects, providingcrop pollination services and valuable hive pro-ducts (4). During the past 50 years, the globalspread of the ectoparasitic mite Varroa destructorhas resulted in the death of millions of honey bee(Apis mellifera) colonies (5). There is generalconsensus that the mites’ association with a rangeof honey bee RNAviruses is a contributing factorin the global collapse of honey bee colonies(5–10), because the spread ofmites has facilitatedthe spread of viruses (11, 12) by acting as a viralreservoir and incubator (13). In addition, themites’ feeding behavior allows virus to be trans-mitted directly into the bees’ hemolymph, thusbypassing conventional, established oral and sex-ual routes of transmission. In particular, deformedwing virus (DWV) has been associated with the

collapse of Varroa-infested honey bee colonies(5, 8, 14–16), because it is ubiquitous in areaswhere Varroa is well established (6, 9, 17, 18).The rapid global spread of Varroa means thatvery little is known about the natural prevalence,viral load, and strain diversity of honey beeviruses before the Varroa invasion (15). Suchdata are important, because most honey bee viralinfections were considered harmless before thespread of Varroa (9). Large-scale loss of honeybee colonies has been associated with virusesvectored by Varroa (5). The recent arrival and

subsequent spread of Varroa across parts of theHawaiian archipelago has provided an opportu-nity to study the initial phase of the evolution ofthe honey bee–Varroa–DWVassociation. So far,colony collapse disorder (CCD) (6) has not beenreported in Hawaii (19), but all of the associatedpests and pathogens are present.

European honey bees (Apis melliferaL.) werefirst introduced toHawaii fromCalifornia in 1857.Theywere largelymanaged, but feral populationswere soon established on every major island inthe archipelago (20). Hawaii remained Varroa-free until August 2007, when the mite was dis-covered throughout Oahu Island. A subsequentsurvey by S. Nikaido and E. Villalobos during2007–2008 recorded the collapse of 274 of 419untreated colonies belonging to beekeepers. Thedisappearance of feral colonies from urban areason Oahu was also noticed by beekeepers and pestcontrol officers. Despite quarantine measures, themite spread to Hilo on the Big Island in January2009, where it survived an eradication attemptand by November 2009 had spread throughoutthe southern region of the island (Fig. 1). ByNovember 2010, Varroa occurred throughoutthe Big Island. However, the islands of Kauaiand Maui remained mite-free, and no unusualcolony losses or disease problems have beenreported there (19). The aim of this study was toinvestigate the influence that Varroa has in thespread of honey bee viruses during the initial

1Department of Animal andPlant Sciences,University of Sheffield,Sheffield S10 2TN, UK. 2The Marine Biological Association of theUnited Kingdom, Citadel Hill, Plymouth PL1 2PB, UK. 3Depart-ment of Plant and Environmental Protection Sciences, Universityof Hawaii at Manoa, Hawaii, USA. 4The Food and EnvironmentResearch Agency, Sand Hutton, York YO41 1LZ, UK.

*To whom correspondence should be addressed. E-mail: s.j.martin@sheffield.ac.uk (S.J.M.); dsch@mba.ac.uk (D.C.S.)

Fig. 1. (A) The four main Hawai-ian Islands, showing the distribu-tion of Varroa during 2009. Greenand brown indicate Varroa-freeand Varroa infested areas respec-tively. Dots indicate the locationof each study apiary. By November2010,Varroawas present through-out theBig Island. The co-occurrenceof the Varroa mite (B) and DWVcan result in overt symptoms of (C)deformed wings in honey bees, al-though many nondeformed beesalso carry high DWV loads.

Kauai

Oahu Maui

Big Island

100 km

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phase of establishment. The spread of Varroa isnormally from point introductions characteristicof pest species, so the arrival and spread of themite across Hawaii are typical for this species.

In 2009, our study of 293 honey bee colonies,from 35 apiaries on the four main HawaiianIslands (Fig. 1), revealed that the exposure toVarroa had a significant effect on the prevalence,viral load, and strain diversity of DWV (Fig. 2).In contrast, neither the prevalence nor the viralload of any of the other four viruses investigated[Kashmir bee virus (KBV), slow paralysis virus(SPV), acute bee paralysis virus (ABPV), or Israeliacute paralysis virus (IAPV)] was affected by thepresence of Varroa (fig. S1).

In Varroa-free areas, DWV was detected in 6to 13% of colonies, but it increased to 75 to 100%where Varroa had been established (Fig. 2). In-creased DWV prevalence was accompanied by amillionfold difference in viral load betweenVarroa-free areas (<1000 DWV copies per bee)and Varroa-infested areas (>1,000,000,000 DWVcopies per bee) (Fig. 2), although there was atime lag associated with changes in strain di-versity (that is, between 2009 and 2010 on theBig Island) (Fig. 2 and fig. S2). High-resolutionmelting (HRM) analysis of DWV–reverse tran-scription polymerase chain reaction (RT-PCR)products showed that in 2009, 20 colonies fromfive apiaries, each maintained by independentbee farmers on Oahu, were primarily dominatedby a single genotype cluster (Fig. 2 and fig. S2),and sequencing showed that this sequence wasidentical to DWV sequences previously detectedin the United Kingdom, Italy, Denmark, Spain,and France (fig. S3). In 2009, the HRM profilesfor Kauai, Maui, and Big Island samples ex-hibited multiple peaks, indicating the presence of

a range of DWV variant sequences (Fig. 2 andfig. S2). Rarefaction analysis of DWV diversityon each island confirmed these findings, withthe cumulative number of strains reachingsaturation in areas where Varroa had been es-tablished. In recently invaded or Varroa-free re-gions, the rarefaction curves did not approachsaturation, which is typical of highly diversesystems (fig. S4). One year later, Varroa hadspread across the Big Island, and a follow-upstudy of 38 colonies from six apiaries showed thesame pattern as previously seen on Oahu: an in-crease in viral load and a decrease in variantdiversity (Fig. 2 and figs. S2 and S4). After 1 yearof effective Varroa control on Oahu, data from 11colonies in one apiary in 2010 indicated that thesame DWV strain remained dominant (fig. S2),suggesting that Varroa-induced changes to theviral landscape are capable of persisting despitethe Varroa populations being under control.

Using 40 clones, sequence analysis revealed10 virus variants in single bee colonies from eachof the four islands, with Kauai, Maui, and theBig Island each having a unique DWV variant(fig. S5). This indicated that a single colony froma Varroa-free area contained more viral diversitythan that detected across Oahu or the Big Island(in 2010) after Varroa had become well estab-lished. Subsequent analysis of sequence data sep-arated two distinguishable DWV variant groups(figs. S3 and S5): (i) the “classic”DWV sequenceknown from symptomatic and asymptomatic hon-ey bees in both Varroa-free and Varroa-infestedcolonies; and (ii) a DWV sequence sharing ap-proximately 18 nucleotide substitutions with theclosely related Varroa destructor virus (VaDV-1)and only 82% sequence homology to the classicDWV sequence (fig. S3).

Varroa populations are largely controlled bythe use of pesticides, but depending on theseason, nearly all bee colonies are infected byDWV (9). Such observations are probably due tothe fact that Varroa is never fully eradicated frominfested colonies, and vertical transmission throughmales (drones) and queens exists (21). Varroa’sarrival at Hawaii has fundamentally altered theviral landscape in both managed and feral beecolonies. On Oahu, all six feral colonies testedhad high levels of DWV (6.1 × 108 copies perbee), similar to that found in managed colonies(Fig. 2), whereas only one of nine feral coloniesfrom the Varroa-free area of the Big Island carriedDWV, and this was the only honey bee colony ina Varroa-free area with a high viral level (4.6 ×107 copies per bee) (Fig. 2). This colony had asimilar melt curve to that produced by the Oahucluster and subsequently died within a year. HighDWV loads (>107 copies per bee) have alsobeen associated with colony death in Varroa-freeareas, indicating that naturally virulent variantscan cause colony death, with or without signs ofwing deformity, although rarely (15).

Variant group A virus is usually associatedwith symptomatic DWV in the presence ofVarroa, although it has also been found inVarroa-free colonies at significantly lower levels,such as those from Kauai. Rather than resultingfrom recent recombination events, the B variantand putative DWV/VaDV-1 hybrids (22) maysimply represent sequence variants that havealways existed, and perhaps they highlight theextent of the natural genetic diversity within thecollective DWVvariants. Furthermore, we foundthat the Oahu variants had a greater similarityto DWV than to VaDV-1 at regions sequencedon both sides of the proposed recombinationpoints (22) (fig. S6). Additionally, leader proteinsequence data from Oahu variants clustered withDWVand not VaDV-1 sequences (fig. S7). Thesefindings indicate that the increase in viral load onOahu is not a result of the formation of DWV/VaDV-1 hybrids. The replicative form of DWVhas been detected in mites (23), and this studyindicates that the presence of Varroa over timeis selecting for particular variants that may givethem a competitive advantage. In Hawaii, themain Oahu strain was also detected in coloniesfrom the Big Island, Maui, and Kauai during2009 but at much lower frequencies (Fig. 2),supporting the hypothesis that Varroa facilitatesthe dominance of certain strains (23), which isstrengthened by the loss of strain diversity be-tween 2009 and 2010 as Varroa became estab-lished on the Big Island (Fig. 2 and fig. S2).Many factors are likely to influence the DWVvariant population in different colonies, but thearrival of DWV variants that can replicate in themite (13) means that these strains would rapidlyincrease in abundance. There have been nomajorintroductions of honey bees into Hawaii, becausestrict importation regulations have been enactedsince the widespread occurrence of Varroamites.It seems likely that the now mite-associated

Fig. 2. Viral load, prevalence, and geneticdiversity of DWV across the four main Ha-waiian Islands that have been exposed toVarroa for different periods of time. 1.E + 04=1 × 104, etc. The asterisk indicates a Varroa-free feral colony that died. Red indicates theproportion of positive colonies (supportedby two or more positive RT-PCR tests) in theDWV prevalence pie charts, with the totalnumber of colonies sampled from each pop-ulation shown beneath. Strain diversity isbased on HRM analysis of three randomlyselected colonies from each population (figs.S2 and S5) and is supported by the rarefac-tion curves (fig. S4).

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European DWV variants were already presentin honey bee populations before the arrival ofthe mites. Studies in the United Kingdom (14)and New Zealand (24) have found that DWVinfections and colony collapse did not coincidewith the arrival and establishment of Varroa, butthere was with a 1- to 3-year time lag, which wealso observed on Hawaii. This lag appears to bethe time required for the selection of virus var-iants adapted to mite transmission.

Recent studies have found no correlationbetween the presence of Varroa and changes inhost immune responses (10, 25, 26), and thecommon occurrence of time lags between miteintroduction and establishment suggests that theincrease in DWV titer and reduction in variantdiversity cannot be explained by Varroa-inducedimmunosuppression of honey bees (27). The ap-parent lack of association between ABPV, IAPV,and KBVand Varroa in this study may reflect thefact that the latter viruses require a longer lagperiod to become established in Varroa than doesDWV, although the prevalence of these virusesvaries greatly in Varroa-infected areas. Furtherwork is required to elucidate the precise role thatVarroamay have in influencing the prevalence ofthe range of viruses that infect bees and theirrole in colony collapse.

Complete viral genome sequencing and ex-perimental infections of honey bees with differ-ent DWV strains are required for testing virulenceand Varroa-associated honey bee colony lossesas was seen on Oahu and the Big Island. Thecurrent Varroa-adapted DWV variants will con-tinue to evolve, and investigations of virus strain

differences may explain the different pathologiescurrently seen globally in honey bee colonies(7). Such variants may interact with other pests,pathogens, environmental factors, and regionalbeekeeping practices, resulting in recent large-scale losses of honey bee colonies (6). This studyshows that the spread of Varroa in Hawaii hascaused DWV, originally an insect virus of lowprevalence, to emerge. This association may beresponsible for the death of millions of coloniesworldwide wherever Varroa and DWV co-occur.

References and Notes1. A. R. Blaustein, P. T. J. Johnson, Nature 465, 881

(2010).2. K. E. Jones et al., Nature 451, 990 (2008).3. J. K. Waage, J. D. Mumford, Philos. Trans. R. Soc. London

Ser. B 363, 863 (2008).4. R. A. Morse, N. W. Calderone, Bee Culture 128, 1 (2000)5. S. J. Martin, J. Appl. Ecol. 38, 1082 (2001).6. D. L. Cox-Foster et al., Science 318, 283 (2007).7. A. C. Highfield et al., Appl. Environ. Microbiol. 75, 7212

(2009).8. N. L. Carreck, B. V. Ball, S. J. Martin, J. Apic. Res. 49, 93

(2010).9. E. Genersch, M. Aubert, Vet. Res. 41, 54 (2010).10. R. M. Johnson, J. D. Evans, G. E. Robinson, M. R. Berenbaum,

Proc. Natl. Acad. Sci. U.S.A. 106, 14790 (2009).11. P. L. Bowen-Walker, S. J. Martin, A. Gunn, J. Invertebr.

Pathol. 73, 101 (1999).12. D. Sumpter, S. J. Martin, J. Anim. Ecol. 73, 51 (2004).13. S. Gisder, P. Aumeier, E. Genersch, J. Gen. Virol. 90, 463

(2009).14. S. J. Martin, A. Hogarth, J. van Breda, J. Perrett,

Apidologie (Celle) 29, 369 (1998).15. J. R. de Miranda, E. Genersch, J. Invertebr. Pathol. 103

(suppl. 1), S48 (2010).16. E. Genersch et al., Apidologie (Celle) 41, 332 (2010).17. D. Tentcheva et al., Appl. Environ. Microbiol. 70, 7185

(2004).

18. A. C. Baker, D. C. Schroeder, J. Invertebr. Pathol. 98, 239(2008).

19. S. J. Martin, Am. Bee J. 150, 381 (2010).20. K. M. Roddy, L. A. Arita-Tsutsumi, J. Hawaiian Pacific

Agriculture 8, 59 (1997).21. C. Yue, M. Schröder, S. Gisder, E. Genersch, J. Gen. Virol.

88, 2329 (2007).22. J. Moore et al., J. Gen. Virol. 92, 156 (2011).23. C. Yue, E. Genersch, J. Gen. Virol. 86, 3419 (2005).24. J. H. Todd, J. R. de Miranda, B. V. Ball, Apidologie (Celle)

38, 354 (2007).25. P. G. Gregory, J. D. Evans, T. Rinderer, L. de Guzman,

J. Insect Sci. 5, 7 (2005).26. M. Navajas et al., BMC Genomics 9, 301 (2008).27. X. Yang, D. L. Cox-Foster, Proc. Natl. Acad. Sci. U.S.A.

102, 7470 (2005).

Acknowledgments: We thank all the Hawaiian beekeepersthat participated in this study and D. Jackson of SheffieldUniversity and C. Godfray of Oxford University for comments.S.J.M. and L.B. were funded by a Natural EnvironmentResearch Council urgency grant (NE/H013164/1), anOrganisation for Economic Co-operation and Developmentfellowship, and the C. B. Dennis Trust. G.E.B. and M.P.were funded by a grant from the Waterloo foundationwith support from Defra and the Welsh AssemblyGovernment. D.C.S. and A.C.H. were funded by theC. B. Dennis Trust. S.N. and E.M.V. were funded bythe U.S. Department of Agriculture’s National Instituteof Food and Agriculture Tropical and Subtropical AgriculturalResearch (TSTAR) Program (grant no. 2010-34135-21499)and by support from the Hawaii Department of Agriculture.The data are available in the DRYAD depository athttp://dx.doi.org/10.5061/dryad.d54cc.

Supplementary Materialswww.sciencemag.org/cgi/content/full/336/6086/1304/DC1Materials and MethodsTable S1Figs. S1 to S7References (28–37)

22 February 2012; accepted 27 April 201210.1126/science.1220941

Vitamin K2 Is a MitochondrialElectron Carrier That RescuesPink1 DeficiencyMelissa Vos,1,2 Giovanni Esposito,1,2 Janaka N. Edirisinghe,3 Sven Vilain,1,2

Dominik M. Haddad,1,2 Jan R. Slabbaert,1,2 Stefanie Van Meensel,1,2 Onno Schaap,1,2

Bart De Strooper,1,2 R. Meganathan,3 Vanessa A. Morais,1,2 Patrik Verstreken1,2*

Human UBIAD1 localizes to mitochondria and converts vitamin K1 to vitamin K2. Vitamin K2 isbest known as a cofactor in blood coagulation, but in bacteria it is a membrane-bound electroncarrier. Whether vitamin K2 exerts a similar carrier function in eukaryotic cells is unknown.We identified Drosophila UBIAD1/Heix as a modifier of pink1, a gene mutated in Parkinson’sdisease that affects mitochondrial function. We found that vitamin K2 was necessary and sufficientto transfer electrons in Drosophila mitochondria. Heix mutants showed severe mitochondrialdefects that were rescued by vitamin K2, and, similar to ubiquinone, vitamin K2 transferredelectrons in Drosophila mitochondria, resulting in more efficient adenosine triphosphate (ATP)production. Thus, mitochondrial dysfunction was rescued by vitamin K2 that serves as amitochondrial electron carrier, helping to maintain normal ATP production.

Parkinson’s disease (PD) is a common neu-rodegenerative disorder, and genetic causesof the disease allow us to elucidate the

molecular pathways involved (1, 2). Mutationsin pink1, encoding an evolutionarily conserved

mitochondrial kinase, cause PD in humans andmitochondrial defects in model organisms (3–6).To understand Pink1 function in vivo, we per-formed a genetic modifier screen in Drosoph-ila. Because PD affects the nervous system we

screened 193 chemically induced recessive lethalmutants that were selected for defects in neuro-communication (7–9). We tested dominant mod-ification of pink1B9 null mutant flight defects(fig. S1A). Although none of the chemically in-duced mutants showed dominant flight defectswhen crossed to a wild-type pink1RV allele, 24mutants suppressed and 32 enhanced the pink1B9

flight defect, such that pink1B9 flies failed to fly(fig. S1A).

To reveal the mechanism by which the mod-ifiers affected Pink1, we mapped one of the stron-gest enhancers that, in combination with pink1B9,results in enhanced lethality to heixuedian (heix).We named this allele heix2 and identified sev-eral additional heix alleles (fig. S1, B to E) (10).To test whether loss of heix specifically exac-erbated pink1 phenotypes, we assessed flight,adenosine triphosphate (ATP) levels, and neu-ronal mitochondrial membrane potential (Ym)(10). Heterozygosity for heix combined with

1VIB Center for the Biology of Disease, 3000 Leuven, Belgium.2KU Leuven, Center for Human Genetics and Leuven ResearchInstitute for Neurodegenerative Diseases (LIND), 3000 Leuven,Belgium. 3Department of Biological Sciences, Northern IllinoisUniversity, DeKalb, IL 60115, USA.

*To whom correspondence should be addressed. E-mail:patrik.verstreken@med.kuleuven.be

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DOI: 10.1126/science.1220941, 1304 (2012);336 Science

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Other Resources

Bee declines driven by combined stress from parasites, pesticides, and lack of flowers:

http://science.sciencemag.org/content/347/6229/1255957.full

A review article from a March 2015 issue of Science details the various stresses leading to colony collapse

disorder in honeybees, including parasites, pesticides, and a decline in available flowers.

Presidential Memorandum - Creating a federal strategy to promote the health of honey bees and other pollinators:

http://www.fs.fed.us/wildflowers/pollinators/documents/PresMemoJune2014/PresidentialMemo-

PromoteHealthPollinators.pdf

A memo issued in June 2014 by U.S. President Barack Obama directs federal agencies to address colony collapse

disorder in honeybees and other problems resulting in a decrease in pollinator populations.

RoboBees to the rescue: http://www.pbs.org/wgbh/nova/tech/robobees-rescue.html

A video from NOVA addressing a method of artificial pollination: “As colony collapse disorder decimates

beehives, scientists are developing mini drones, called RoboBees, to help pollinate our crops.”