Abstract
Emerging infectious diseases (EIDs) pose a risk to human welfare, both directly1 and indirectly, by affecting managed livestock and wildlife that provide valuable resources and ecosystem services, such as the pollination of crops2. Honeybees (Apis mellifera), the prevailing managed insect crop pollinator, suffer from a range of emerging and exotic high-impact pathogens3,4, and population maintenance requires active management by beekeepers to control them. Wild pollinators such as bumblebees (Bombus spp.) are in global decline5,6, one cause of which may be pathogen spillover from managed pollinators like honeybees7,8 or commercial colonies of bumblebees9. Here we use a combination of infection experiments and landscape-scale field data to show that honeybee EIDs are indeed widespread infectious agents within the pollinator assemblage. The prevalence of deformed wing virus (DWV) and the exotic parasite Nosema ceranae in honeybees and bumblebees is linked; as honeybees have higher DWV prevalence, and sympatric bumblebees and honeybees are infected by the same DWV strains, Apis is the likely source of at least one major EID in wild pollinators. Lessons learned from vertebrates10,11 highlight the need for increased pathogen control in managed bee species to maintain wild pollinators, as declines in native pollinators may be caused by interspecies pathogen transmission originating from managed pollinators.
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References
Binder, S., Levitt, A. M., Sacks, J. J. & Hughes, J. M. Emerging infectious diseases: public health issues for the 21st century. Science 284, 1311–1313 (1999)
Oldroyd, B. P. Coevolution while you wait: Varroa jacobsoni, a new parasite of western honeybees. Trends Ecol. Evol. 14, 312–315 (1999)
Ratnieks, F. L. W. & Carreck, N. L. Clarity on honey bee collapse? Science 327, 152–153 (2010)
Vanbergen, A. J. The Insect Pollinator Initiative. Threats to an ecosystem service: pressures on pollinators. Front. Ecol. Environ 11, 251–259 (2013)
Williams, P. H. & Osborne, J. L. Bumblebee vulnerability and conservation world-wide. Apidologie 40, 367–387 (2009)
Cameron, S. A. et al. Patterns of widespread decline in North American bumble bees. Proc. Natl Acad. Sci. USA 108, 662–667 (2011)
Evison, S. E. F. et al. Pervasiveness of parasites in pollinators. PLoS ONE 7, e30641 (2012)
Genersch, E., Yue, C., Fries, I. & de Miranda, J. R. Detection of deformed wing virus, a honey bee viral pathogen, in bumble bees (Bombus terrestris and Bombus pascuorum) with wing deformities. J. Invertebr. Pathol. 91, 61–63 (2006)
Meeus, I., Brown, M. J. F., De Graaf, D. C. & Smagghe, G. Effects of invasive parasites on bumble bee declines. Conserv. Biol. 25, 662–671 (2011)
Fisher, M. C. et al. Emerging fungal threats to animal, plant and ecosystem health. Nature 484, 186–194 (2012)
Krebs, J. et al. Bovine Tuberculosis in Cattle and Badgers (MAFF Publications, 1997)
Vitousek, P. M., Dantonio, C. M., Loope, L. L. & Westbrooks, R. Biological invasions as global environmental change. Am. Sci. 84, 468–478 (1996)
Daszak, P. Emerging infectious diseases of wildlife — threats to biodiversity and human health. Science 287, 443–449 (2000)
Dobson, A. Population dynamics of pathogens with multiple host species. Am. Nat. 164, S64–S78 (2004)
Alderman, D. J. Geographical spread of bacterial and fungal diseases of crustaceans. Rev. Sci. Tech. 15, 603–632 (1996)
Neumann, P. & Carreck, N. L. Honey bee colony losses. J. Apic. Res. 49, 1–6 (2010)
Paxton, R. J. Does infection by Nosema ceranae cause “Colony Collapse Disorder” in honey bees (Apis mellifera)? J. Apic. Res. 49, 80–84 (2010)
Murray, T. E., Coffey, M. F., Kehoe, E. & Horgan, F. G. Pathogen prevalence in commercially reared bumble bees and evidence of spillover in conspecific populations. Biol. Conserv. 159, 269–276 (2013)
Singh, R. et al. RNA viruses in Hymenopteran pollinators: evidence of inter-taxa virus tansmission via pollen and potential impact on non-Apis Hymenopteran species. PLoS ONE 5, e14357 (2010)
Graystock, P. et al. The Trojan hives: pollinator pathogens, imported and distributed in bumblebee colonies. J. Appl. Ecol. 50, 1207–1215 (2013)
Ongus, J. R. et al. Complete sequence of a picorna-like virus of the genus Iflavirus replicating in the mite Varroa destructor. J. Gen. Virol. 85, 3747–3755 (2004)
Moore, J. et al. Recombinants between deformed wing virus and Varroa destructor virus-1 may prevail in Varroa destructor-infested honeybee colonies. J. Gen. Virol. 92, 156–161 (2011)
Xie, W., Lewis, P. O., Fan, Y., Kuo, L. & Chen, M.-H. Improving marginal likelihood estimation for Bayesian phylogenetic model selection. Syst. Biol. 60, 150–160 (2011)
Martin, S. J. et al. Global honey bee viral landscape altered by a parasitic mite. Science 336, 1304–1306 (2012)
Graystock, P., Yates, K., Darvill, B., Goulson, D. & Hughes, W. O. H. Emerging dangers: deadly effects of an emergent parasite in a new pollinator host. J. Invertebr. Pathol. 114, 114–119 (2013)
Smart, M. D. & Sheppard, W. S. Nosema ceranae in age cohorts of the western honey bee (Apis mellifera). J. Invertebr. Pathol. 109, 148–151 (2012)
Otterstatter, M. C. & Thomson, J. D. Does pathogen spillover from commercially reared bumble bees threaten wild pollinators? PLoS ONE 3, (2008)
Donnelly, C. A. & Woodroffe, R. Reduce uncertainty in UK badger culling. Nature 485, 582 (2012)
Higes, M., Martin-Hernandez, R., Garrido-Bailon, E., Garcia-Palencia, P. & Meana, A. Detection of infective Nosema ceranae (Microsporidia) spores in corbicular pollen of forager honeybees. J. Invertebr. Pathol. 97, 76–78 (2008)
Cole, R. J. Application of the “triangulation” method to the purification of Nosema spores from insect tissues. J. Invertebr. Pathol. 15, 193–195 (1970)
Bailey, L. L. & Ball, B. V. Honey bee pathology 2nd edn, (Academic Press, 1991)
Yañez, O. et al. Deformed wing virus and drone mating flights in the honey bee (Apis mellifera): implications for sexual transmission of a major honey bee virus. Apidologie 43, 17–30 (2012)
Murray, T. E., Fitzpatrick, U., Brown, M. J. F. & Paxton, R. J. Cryptic species diversity in a widespread bumble bee complex revealed using mitochondrial DNA RFLPs. Conserv. Genet. 9, 653–666 (2008)
Chen, Y., Evans, J. D., Smith, I. B. & Pettis, J. S. Nosema ceranae is a long-present and wide-spread microsporidian infection of the European honey bee (Apis mellifera) in the United States. J. Invertebr. Pathol. 97, 186–188 (2008)
Genersch, E. Development of a rapid and sensitive RT-PCR method for the detection of deformed wing virus, a pathogen of the honeybee (Apis mellifera). Vet. J. 169, 121–123 (2005)
Hornáková, D., Matouskova, P., Kindl, J., Valterova, I. & Pichova, I. Selection of reference genes for real-time polymerase chain reaction analysis in tissues from Bombus terrestris and Bombus lucorum of different ages. Anal. Biochem. 397, 118–120 (2010)
de Miranda, J. R. & Genersch, E. Deformed wing virus. J. Invertebr. Pathol. 103, S48–S61 (2010)
Yue, C. & Genersch, E. RT-PCR analysis of deformed wing virus in honeybees (Apis mellifera) and mites (Varroa destructor). J. Gen. Virol. 86, 3419–3424 (2005)
Craggs, J. K., Ball, J. K., Thomson, B. J., Irving, W. L. & Grabowska, A. M. Development of a strand-specific RT-PCR based assay to detect the replicative form of hepatitis C virus RNA. J. Virol. Methods 94, 111–120 (2001)
Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010)
Huelsenbeck, J. P. & Ronquist, F. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17, 754–755 (2001)
Rambaut, A. & Drummond, A. J. Tracer v1.5. http://beast.bio.ed.ac.uk/Tracer (30 November 2009)
de Bruyn, M. et al. Paleo-drainage basin connectivity predicts evolutionary relationships across three southeast Asian biodiversity hotspots. Syst. Biol. 62, 398–410 (2013)
Therneau, T. Coxme: Mixed Effects Cox Models. http://CRAN.R-project.org/package=coxme (15 May 2012)
Reiczigel, J., Foldi, J. & Ozsvari, L. Exact confidence limits for prevalence of a disease with an imperfect diagnostic test. Epidemiol. Infect. 138, 1674–1678 (2010)
Blaker, H. Confidence curves and improved exact confidence intervals for discrete distributions. Can. J. Statist. 28, 783–798 (2000)
epiR:. an R package for the analysis of epidemiological data v. R package version 0.9-45. (30 November 2012)
Rossi, R. E., Mulla, D. J., Journel, A. G. & Franz, E. H. Geostatistical tools for modeling and interpreting ecological spatial dependence. Ecol. Monogr. 62, 277–314 (1992)
Larmarange, J., Vallo, R., Yaro, S., Msellati, P. & Meda, N. Methods for mapping regional trends of HIV prevalence from demographic and health surveys (DHS). Cybergeo. http://cybergeo.revues.org/24606 (2011)
Moran, P. A. Notes on continuous stochastic phenomena. Biometrika 37, 17–23 (1950)
Gittleman, J. L. & Kot, M. Adaptation: statistics and a null model for estimating phylogenetic effects. Syst. Biol. 39, 227–241 (1990)
Paradis, E., Claude, J. & Strimmer, K. APE: Analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004)
Baayen, R. H., Davidson, D. J. & Bates, D. M. Mixed-effects modeling with crossed random effects for subjects and items. J. Mem. Lang. 59, 390–412 (2008)
Bates, D., Maechler, M. & Bolker, B. lme4: Linear mixed-effects models using S4 classes (22 June 2012)
Schielzeth, H. Simple means to improve the interpretability of regression coefficients. Meth. Ecol. Evol. 1, 103–113 (2010)
R Foundation for Statistical Computing R: a language and environment for statistical computing (26 October 2012)
Acknowledgements
The authors are grateful to E. Fürst for technical support and R. J. Gill for discussions. We thank C. Jones, G. Baron and O. Ramos-Rodriguez for comments on previous versions of the manuscript. They also thank Hymettus Ltd for help with the field collections, K. Liu for help in the laboratory and B. McCrea and S. Baldwin for technical help in the bee laboratory. The study was supported by the Insect Pollinators Initiative (funded jointly by the Biotechnology and Biological Sciences Research Council, the Department for Environment, Food and Rural Affairs, the Natural Environment Research Council, The Scottish Government and The Wellcome Trust, under the Living with Environmental Change Partnership: grants BB/I000151/1 (M.J.F.B.), BB/I000100/1 (R.J.P.) and BB/I000097/1 (J.L.O.).
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The study was jointly conceived by R.J.P., J.L.O. and M.J.F.B. Experiments were designed by M.A.F. and M.J.F.B.; M.A.F prepared the manuscript; M.J.F.B., D.P.M., R.J.P. and J.L.O. edited the manuscript. M.A.F. carried out the experimental, molecular work and analyses, and D.P.M. undertook the phylogenetic analyses.
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Extended data figures and tables
Extended Data Figure 1 Host bee species and sampling-site distributions.
Distribution of sampling sites across Great Britain and the Isle of Man. The most common Bombus species on a given site is represented by coloured letters and the second most common Bombus species is represented by the colours of the dots. Total sample sizes for each site are given in the table.
Extended Data Figure 2 Prevalence of DWV and N. ceranae per site and host bee species.
a–d, Pathogen prevalence in Bombus spp. in per cent per site for DWV (a) and for N. ceranae (b), and per species for DWV (c) and for N. ceranae (d). Bars indicate 95% confidence intervals. Note different scales.
Extended Data Figure 3 Raw data for prevalence of DVW and N. ceranae.
The linear models shown only illustrate the relationships but do not drive the conclusions in the main text. a, DWV presence in Apis and Bombus (adjusted R2 = 0.34, P < 0.001). b, DWV replicating in Bombus and DWV presence in Bombus (adjusted R2 = 0.46, P < 0.001). c, N. ceranae presence in Apis and Bombus (adjusted R2 = −0.04, P > 0.728). The line shows the best fit and the dark grey region shows 95% confidence interval of fit.
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Fürst, M., McMahon, D., Osborne, J. et al. Disease associations between honeybees and bumblebees as a threat to wild pollinators. Nature 506, 364–366 (2014). https://doi.org/10.1038/nature12977
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DOI: https://doi.org/10.1038/nature12977
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