Microbes can be social. In some groups of microbes that have parasitic lifecycles the social behavior of the many microbial cells can lead to the precise control of the animal they infect. The microbes orchestrate within the body and coordinate to form interactions that are as impressive as any other collective behavior from fish shoals to flocks of birds to ant trails. In some biological systems the manipulated animal is an ant and therefore belongs to its own collective, the colony. In our system we study the `zombie-ant' fungi (Ophiocordyceps) of tropical and temperate forests, which precisely control ants to leave their nest and bite into vegetation directly over the foraging trails of the colony. The function of such altered behavior becomes apparent when the fungus kills the ant and grows a stalk from its head that shoots out spores that infect other ants. The goal of this application is o develop models of such complex collective behavior by fungi controlling ants. We will develop computational and physical diffusion models of the development of the fungal collective, within its ant host. We will use high throughput Scanning Electron Microscopy of ant muscles and computer vision algorithms to develop 3D computational models and accurate networks of cells. We will perform micro-acoustic fluidic experiments to measure fungal behavior and develop physical diffusion models of the emergence of collective behavior. At the macroscopic scale we will measure infected ant behavior in the forest and build agent-based models to determine the rules explaining the effective targeting of ant trails by the fungal collective using the ant as a vehicle. Finally, we will perform experiments to understand the role of competition for the social behavior of microbes. This work is a collaboration among David Hughes, an expert of animal behavior and parasites, Ephraim Hanks, an expert on models of animal behavior, Danny Chen, a computer scientist expert in 3D models of cells, Francesco Costanzo, a theoretical mechanical expert in physical diffusion models and Tony Huang, an engineer expert in micro-acoustic fluidic experiments. Extensive collaboration already exists among the five researchers and four of the five occupy the same building at Penn State, ensuring an easy collaboration.

Public Health Relevance

Fungal parasites can act as a group to control the behavior of ants to increase transmission to the next host. We will use a diversity of modeling approaches to study parasite social behavior across scales. Insights may inform studies of cancer cells in humans.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM116927-03
Application #
9433672
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Marcus, Stephen
Project Start
2016-02-01
Project End
2021-01-31
Budget Start
2018-02-01
Budget End
2019-01-31
Support Year
3
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Pennsylvania State University
Department
Zoology
Type
Earth Sciences/Resources
DUNS #
003403953
City
University Park
State
PA
Country
United States
Zip Code
16802
Fredericksen, Maridel A; Zhang, Yizhe; Hazen, Missy L et al. (2017) Three-dimensional visualization and a deep-learning model reveal complex fungal parasite networks in behaviorally manipulated ants. Proc Natl Acad Sci U S A 114:12590-12595