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Three-dimensional visualization and a deep-learning model reveal complex fungal parasite networks in behaviorally manipulated ants.
Proc Natl Acad Sci U S A. 2017 11 21; 114(47):12590-12595.PN

Abstract

Some microbes possess the ability to adaptively manipulate host behavior. To better understand how such microbial parasites control animal behavior, we examine the cell-level interactions between the species-specific fungal parasite Ophiocordyceps unilateralis sensu lato and its carpenter ant host (Camponotus castaneus) at a crucial moment in the parasite's lifecycle: when the manipulated host fixes itself permanently to a substrate by its mandibles. The fungus is known to secrete tissue-specific metabolites and cause changes in host gene expression as well as atrophy in the mandible muscles of its ant host, but it is unknown how the fungus coordinates these effects to manipulate its host's behavior. In this study, we combine techniques in serial block-face scanning-electron microscopy and deep-learning-based image segmentation algorithms to visualize the distribution, abundance, and interactions of this fungus inside the body of its manipulated host. Fungal cells were found throughout the host body but not in the brain, implying that behavioral control of the animal body by this microbe occurs peripherally. Additionally, fungal cells invaded host muscle fibers and joined together to form networks that encircled the muscles. These networks may represent a collective foraging behavior of this parasite, which may in turn facilitate host manipulation.

Authors+Show Affiliations

Department of Entomology, Pennsylvania State University, University Park, PA 16802.Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556.Huck Institutes of the Life Sciences Microscopy and Cytometry Facility, Pennsylvania State University, University Park, PA 16802.Department of Entomology, Pennsylvania State University, University Park, PA 16802. Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802.Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802. Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802.Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556.Department of Entomology, Pennsylvania State University, University Park, PA 16802; dhughes@psu.edu. Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802. Department of Biology, Pennsylvania State University, University Park, PA 16802.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

29114054

Citation

Fredericksen, Maridel A., et al. "Three-dimensional Visualization and a Deep-learning Model Reveal Complex Fungal Parasite Networks in Behaviorally Manipulated Ants." Proceedings of the National Academy of Sciences of the United States of America, vol. 114, no. 47, 2017, pp. 12590-12595.
Fredericksen MA, Zhang Y, Hazen ML, et al. Three-dimensional visualization and a deep-learning model reveal complex fungal parasite networks in behaviorally manipulated ants. Proc Natl Acad Sci USA. 2017;114(47):12590-12595.
Fredericksen, M. A., Zhang, Y., Hazen, M. L., Loreto, R. G., Mangold, C. A., Chen, D. Z., & Hughes, D. P. (2017). Three-dimensional visualization and a deep-learning model reveal complex fungal parasite networks in behaviorally manipulated ants. Proceedings of the National Academy of Sciences of the United States of America, 114(47), 12590-12595. https://doi.org/10.1073/pnas.1711673114
Fredericksen MA, et al. Three-dimensional Visualization and a Deep-learning Model Reveal Complex Fungal Parasite Networks in Behaviorally Manipulated Ants. Proc Natl Acad Sci USA. 2017 11 21;114(47):12590-12595. PubMed PMID: 29114054.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Three-dimensional visualization and a deep-learning model reveal complex fungal parasite networks in behaviorally manipulated ants. AU - Fredericksen,Maridel A, AU - Zhang,Yizhe, AU - Hazen,Missy L, AU - Loreto,Raquel G, AU - Mangold,Colleen A, AU - Chen,Danny Z, AU - Hughes,David P, Y1 - 2017/11/07/ PY - 2017/11/9/pubmed PY - 2018/6/27/medline PY - 2017/11/9/entrez KW - ants KW - behavioral manipulation KW - deep learning KW - extended phenotype KW - fungal networks SP - 12590 EP - 12595 JF - Proceedings of the National Academy of Sciences of the United States of America JO - Proc. Natl. Acad. Sci. U.S.A. VL - 114 IS - 47 N2 - Some microbes possess the ability to adaptively manipulate host behavior. To better understand how such microbial parasites control animal behavior, we examine the cell-level interactions between the species-specific fungal parasite Ophiocordyceps unilateralis sensu lato and its carpenter ant host (Camponotus castaneus) at a crucial moment in the parasite's lifecycle: when the manipulated host fixes itself permanently to a substrate by its mandibles. The fungus is known to secrete tissue-specific metabolites and cause changes in host gene expression as well as atrophy in the mandible muscles of its ant host, but it is unknown how the fungus coordinates these effects to manipulate its host's behavior. In this study, we combine techniques in serial block-face scanning-electron microscopy and deep-learning-based image segmentation algorithms to visualize the distribution, abundance, and interactions of this fungus inside the body of its manipulated host. Fungal cells were found throughout the host body but not in the brain, implying that behavioral control of the animal body by this microbe occurs peripherally. Additionally, fungal cells invaded host muscle fibers and joined together to form networks that encircled the muscles. These networks may represent a collective foraging behavior of this parasite, which may in turn facilitate host manipulation. SN - 1091-6490 UR - https://www.unboundmedicine.com/medline/citation/29114054/Three_dimensional_visualization_and_a_deep_learning_model_reveal_complex_fungal_parasite_networks_in_behaviorally_manipulated_ants_ L2 - http://www.pnas.org/cgi/pmidlookup?view=long&pmid=29114054 DB - PRIME DP - Unbound Medicine ER -