Effects of Climate Change on Microbial Food Webs (2022-2023)
Microbial communities (collections of microbes and their interactions) play a crucial role in the global carbon cycle that sets the pace of global climate change. These communities can evolve rapidly in response to a changing environment, but we don’t currently understand how that rapid evolution may influence their response to global warming.
Unicellular organisms have long been a model system to understand fundamental principles of biology, from genetics to ecosystems. For example, the unicellular green alga Chlamydomonas reinhardtii — a model organism in cell biology used for studying cell function and biochemical pathways — is now also recognized as an important player in the global carbon cycle responsible for climate change through carbon sequestration. Because of their very short generation times, these algae are prone to evolve rapidly and thus provide a unique window into how rapid evolution may influence the global carbon cycle under global warming.
This project team will combine the fields of biology, evolutionary biology, ecology, microbiology and math to address the role of microbial communities in the global carbon cycle. The project will be divided into subteams that will carry out paired mathematical modeling and experimental designs to address the following questions:
- How does microbial food web structure affect rapid evolution in the algae C. reinhardtii?
- What are the effects of rapid evolution of C. reinhardtii on microbial food webs and what are the traits involved?
- How does temperature influence these processes?
The math subteam will analyze differential equation models that track population growth and account for rapid evolution of traits that mediate interactions between C. reinhardtii and its predators across temperatures. Team members will devise a mathematical model to address each of the above questions and generate testable predictions for the other two subteams to test experimentally.
The ecology and evolution subteam will experimentally address the theoretical assumptions made by the math subteam. Team members will design experiments that involve manipulations of temperature (using temperature-controlled growth chambers), food web structure (by manipulating the number of possible C. reinhardtii predators) and genetic variability (by manipulating the number of genetic strains of C. reinhardtii, which influences evolvability).
The cell biology subteam will work with the ecology and evolution subteam to extract DNA from experimental samples and prepare it for next-gen sequencing. Team members will prepare the sequencing data to be analyzed, and explore physiological and cellular traits related to motility, cell division, cell size control and development of multicellularity. This study will serve as a novel high-throughput genetic screening to identify previously unknown genes involved in predation-prey interactions and thermal responses.
Peer-reviewed publication; science communication piece on interdisciplinarity in STEM; data for dissertations and honors theses; preliminary data for future grant
Ideally, this project team will include 2 graduate students and 6 undergraduate students. Participants can come from a wide variety of fields, such as cell and molecular biology, microbiology, ecology, evolution, environmental sciences, math, engineering, physics, statistics and computer science.
Participants will receive training in experimental design and tools for cell biology and ecology research. All students will learn statistics and data analysis for both ecological data and genetic data and will gain understandings of math modeling.
Undergraduate students will be encouraged to develop independent projects and honors theses around the focal topics and may use the data generated to address such questions. Graduate students will hone their mentoring and management skills by becoming team leaders, leading weekly meetings and designing experiments with undergraduates. In Fall 2022, the team will meet on Fridays from 3:00-4:00 p.m. Graduate participants will also practice their scientific communication skills by speaking with general audiences and their scientific community and will receive advice and training from senior team members on experimental setup, math modeling and data analysis.
Ze-Yi Han will serve as project manager.
Fall 2022 – Spring 2023
- Fall 2022: Finalize the collaborative project design; conduct the project; collect data; design and conduct independent projects
- Spring 2023: Complete data processing and data analysis; draft scientific papers and science communication piece
Academic credit available for fall and spring semesters
Image: Chlamydomonas reinhardtii, by Wolf G., licensed under CC BY-NC-ND 2.0
- Maria Veronica Ciocanel, Arts & Sciences-Mathematics
- Jean Philippe Gibert, Arts & Sciences-Biology
- Ze-Yi Han, Arts and Sciences–Biology–Ph.D. Student
- Masayuki Onishi, Arts & Sciences-Biology
- Daniel Wieczynski, Arts & Sciences-Biology
- Yaning Yuan, Arts and Sciences–Biology–Ph.D. Student
/yfaculty/staff Team Members
Angelica Leigh, Fuqua School of Business