Effects of Climate Change on Microbial Food Webs (2022-2023)

Background

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.

Project Description

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. 

Anticipated Outputs

Peer-reviewed publication; science communication piece on interdisciplinarity in STEM; data for dissertations and honors theses; preliminary data for future grant

Timing

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

 

Image: Chlamydomonas reinhardtii, by Wolf G., licensed under CC BY-NC-ND 2.0

Chlamydomonas reinhardtii

Team Leaders

  • 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

/undergraduate Team Members

  • Enzo Bruscato
  • Anushka Goel
  • Matilde Molinari Giglietti, DKU Interdisciplinary Studies (BS)
  • Nicholas Sortisio
  • Kurt Tjossem
  • Happy Yao, Biology (BS)