The Darwin Project at MIT: Modeling Marine Microbes from Cellular to Global Scales. What is the Darwin Project? Goals Investigators Funding Modeling global phytoplankton biogeography Prochlorococcus ecotypes Some future directions

What is the Darwin Project? An inter-disciplinary, inter-departmental effort at MIT to develop and apply novel models of marine microbes and microbial communities from molecular and cellular scales that regulate an individual’s response to its environment to the large scale environmental influences What regulates observed community structure? What are feedbacks on the environment? How might structure and feedbacks vary with climate?

Ecosystem structure and function Physical and Chemical Environment Genomes Proteins Metabolism Growth and reproduction Physical and Chemical Environment competition predation natural selection community self-assembly Ecosystem structure and function

The Darwin Project at MIT Genomes Proteins Metabolism Growth and reproduction Physical and Chemical Environment competition predation natural selection community self-assembly Earth, Atmospheric and Planetary Sciences Computational and Systems Biology Civil and Environmental Engineering Ecosystem structure and function

Who are the Darwin Project Investigators? Microbial ecologists, microbiologists, climate scientists, biogeochemists, computer scientists across the campus at MIT: PI’s: Follows, Chisholm, Marshall, Tidor, Mastudaira, Hill, Delong, Polz Investigators: Stephanie Dutkiewicz, Jason Bragg… Matt Gardner Links to the wider community: CAMERA, C-MORE, …

How is the Darwin Project Funded How is the Darwin Project Funded? The Moore Foundation Marine Microbiology Initiative Personnel: Mick and Steph 2 post-docs, programmer 2 grad students Computational Infrastructure: 128 node compute cluster 512 terabyte storage facility 64 panel visualization wall National Lambda Rail link

What have we been doing? Pursuing a “self-organizing” approach to modeling the phytoplankton community structure of the global ocean The emergent biogeography and physiological characteristics of model analogs of Prochlorococcus provide a proof-of-concept.

Prochlorococcus ecotype habitats along AMT13 (Johnson et al., Science, 2006) Genetically distinct ecotypes Correlated physiological differences Expressed as different habitats

What sets ecosystem structure? physical and chemical environment genetics and physiology competition predation selection ecosystem structure and function

physical and genetics and chemical physiology environment competition Empirical physiological descriptions MITgcm – simulated environment physical and chemical environment genetics and physiology O(100) cell types competition predation selection ecosystem structure and function Emergent ecosystem

Emergent biogeography – 16 most abundant phytoplankton types Prochlorococcus analogs Synechococcus & small eukaryotes . Diatoms In these runs 15 – 20 “phytoplankton functional types” are “fit” i.e. maintain a population above some threshold value KEY: 1 – 4, top row: The four most abundant Prochlorococcus analogues (small phyto, cannot assimilate NO3) 5 – 9, second row + 1: Small phyto, can consume NO3 (Synchococcus and small eukaryote analogues) 10 – 12, rest of third row: Diatom analogues (large phyto, need Si) 13 – 16, bottom row: Other large phyto Other large eukaryotes

Prochlorococcus ecotypes Plausible emergent analogs of Prochlorococcus ecotypes Model ecotype physiologies are also consistent with real-world counterparts. Prochlorococcus ecotypes AMT13 (Johnson et al., 2006) Emergent model-ecotypes

What next? Examine emergent microbial community structure in the light of ecological theory (Steph and Jason) Examine the role of unresolved ocean eddies in shaping community structure (Andrew) Model and interpret variations of community structure and relationship to climate Address genomic and metagenomic data sets Mechanistic cellular scale parameterizations: systems biology Address a broader range of organism types: heterotrophs, mixotrophs, grazers, virus Adaptive organisms, mutation, natural selection

Addressing metagenomic data DeLong Lab Mapping microbial communities by function CAMERA – metagenomic storehouse and analysis facility C-MORE

Climate Variations and Community Structure Continuous Plankton Recorder – Sir Alister Hardy Foundation Continuous sampling of ~250 planktonic taxa in North Atlantic since 1930’s Can we simulate changes? Response to climate variations? Diatom abundance, NE/SE regions

Systems Biology Develop mechanistic descriptions of environmental sensitivities Replace/enhance empirical parameterizations

The Darwin Project at MIT Genomes Proteins Metabolism Growth and reproduction Physical and Chemical Environment competition predation natural selection community self-assembly Ecosystem structure and function

P P Self-organizing ecosystem model: initialize many organism types fittest organisms selected for by interactions of organisms and environment, reflecting real world organization P P Complex initialized food web self-organized state

Simulation of Prochlorococcus ecotypes provides Proof of concept for the approach Test-bed for ecological theory and interpretation (e.g. Tilman, 1977; Steph and Jason) Basis for Darwin Projects flagship, regional and global simulations examining broader spectrum of organisms and biogeographical controls Investigating links to biogeochemical cycles and climate change