Unity in defence

Honeybee workers exhibit conserved molecular responses to diverse pathogens

Vincent Doublet, Yvonne Poeschl, Andreas Gogol-Döring, Cédric Alaux, Desiderato Annoscia, Christian Aurori, Seth M. Barribeau, Oscar C. Bedoya-Reina, Mark J.F. Brown, James C. Bull, Michelle L. Flenniken, David A. Galbraith, Elke Genersch, Sebastian Gisder, Ivo Grosse, Holly L. Holt, Dan Hultmark, H. Michael G. Lattorff, Yves Le Conte, Fabio Manfredini & 8 others Dino P. McMahon, Robin F.A. Moritz, Francesco Nazzi, Elina L. Niño, Katja Nowick, Ronald P. van Rij, Robert J. Paxton, Christina M. Grozinger

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.

Original languageEnglish (US)
Article number207
JournalBMC genomics
Volume18
Issue number1
DOIs
StatePublished - Mar 2 2017

Fingerprint

Bees
Computational Biology
Honey
Varroidae
Genes
Nosema
Meta-Analysis
Infection
Microsporidia
Biological Phenomena
Gene Expression
Mites
RNA Viruses
Virus Diseases
Transcriptome
Insects
Parasites
Genome
Apoptosis
Viruses

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Genetics

Cite this

Doublet, Vincent ; Poeschl, Yvonne ; Gogol-Döring, Andreas ; Alaux, Cédric ; Annoscia, Desiderato ; Aurori, Christian ; Barribeau, Seth M. ; Bedoya-Reina, Oscar C. ; Brown, Mark J.F. ; Bull, James C. ; Flenniken, Michelle L. ; Galbraith, David A. ; Genersch, Elke ; Gisder, Sebastian ; Grosse, Ivo ; Holt, Holly L. ; Hultmark, Dan ; Lattorff, H. Michael G. ; Le Conte, Yves ; Manfredini, Fabio ; McMahon, Dino P. ; Moritz, Robin F.A. ; Nazzi, Francesco ; Niño, Elina L. ; Nowick, Katja ; van Rij, Ronald P. ; Paxton, Robert J. ; Grozinger, Christina M. / Unity in defence : Honeybee workers exhibit conserved molecular responses to diverse pathogens. In: BMC genomics. 2017 ; Vol. 18, No. 1.
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abstract = "Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.",
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Doublet, V, Poeschl, Y, Gogol-Döring, A, Alaux, C, Annoscia, D, Aurori, C, Barribeau, SM, Bedoya-Reina, OC, Brown, MJF, Bull, JC, Flenniken, ML, Galbraith, DA, Genersch, E, Gisder, S, Grosse, I, Holt, HL, Hultmark, D, Lattorff, HMG, Le Conte, Y, Manfredini, F, McMahon, DP, Moritz, RFA, Nazzi, F, Niño, EL, Nowick, K, van Rij, RP, Paxton, RJ & Grozinger, CM 2017, 'Unity in defence: Honeybee workers exhibit conserved molecular responses to diverse pathogens', BMC genomics, vol. 18, no. 1, 207. https://doi.org/10.1186/s12864-017-3597-6

Unity in defence : Honeybee workers exhibit conserved molecular responses to diverse pathogens. / Doublet, Vincent; Poeschl, Yvonne; Gogol-Döring, Andreas; Alaux, Cédric; Annoscia, Desiderato; Aurori, Christian; Barribeau, Seth M.; Bedoya-Reina, Oscar C.; Brown, Mark J.F.; Bull, James C.; Flenniken, Michelle L.; Galbraith, David A.; Genersch, Elke; Gisder, Sebastian; Grosse, Ivo; Holt, Holly L.; Hultmark, Dan; Lattorff, H. Michael G.; Le Conte, Yves; Manfredini, Fabio; McMahon, Dino P.; Moritz, Robin F.A.; Nazzi, Francesco; Niño, Elina L.; Nowick, Katja; van Rij, Ronald P.; Paxton, Robert J.; Grozinger, Christina M.

In: BMC genomics, Vol. 18, No. 1, 207, 02.03.2017.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Unity in defence

T2 - Honeybee workers exhibit conserved molecular responses to diverse pathogens

AU - Doublet, Vincent

AU - Poeschl, Yvonne

AU - Gogol-Döring, Andreas

AU - Alaux, Cédric

AU - Annoscia, Desiderato

AU - Aurori, Christian

AU - Barribeau, Seth M.

AU - Bedoya-Reina, Oscar C.

AU - Brown, Mark J.F.

AU - Bull, James C.

AU - Flenniken, Michelle L.

AU - Galbraith, David A.

AU - Genersch, Elke

AU - Gisder, Sebastian

AU - Grosse, Ivo

AU - Holt, Holly L.

AU - Hultmark, Dan

AU - Lattorff, H. Michael G.

AU - Le Conte, Yves

AU - Manfredini, Fabio

AU - McMahon, Dino P.

AU - Moritz, Robin F.A.

AU - Nazzi, Francesco

AU - Niño, Elina L.

AU - Nowick, Katja

AU - van Rij, Ronald P.

AU - Paxton, Robert J.

AU - Grozinger, Christina M.

PY - 2017/3/2

Y1 - 2017/3/2

N2 - Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.

AB - Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.

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Doublet V, Poeschl Y, Gogol-Döring A, Alaux C, Annoscia D, Aurori C et al. Unity in defence: Honeybee workers exhibit conserved molecular responses to diverse pathogens. BMC genomics. 2017 Mar 2;18(1). 207. https://doi.org/10.1186/s12864-017-3597-6