Deadlines
  • LOI: 01/17/2020
  • Proposal: 03/02/2020

Scope

The Understanding the Rules of Life: Microbiome Theory and Mechanisms (URoL:MTM) program invites integrated, interdisciplinary proposals that develop theoretical predictive frameworks with well-designed experimental and/or computational approaches to generate and test hypotheses about the causal relationships within the microbiome, and among the microbiome, host, and environment. How these relationships affect robustness, resilience, and adaptability of individual organisms, populations, and communities are also of interest. Projects may apply existing ecological and evolutionary theory or develop new experimental, computational, or mathematical tools, models, and theory to: i) explain function and interactions in natural, experimental, and model microbiomes; ii) elucidate the molecular mechanisms that underlie communication between the host and the microbiome and among the members of the microbiome; and/or iii) comparatively analyze microbiomes to discover emergent properties that provide insight into the behavior of living systems.

There are many basic research opportunities for new understanding about interactions between members of the microbiome, between microbiomes and the environment, between microbiome and their hosts, and among microbiomes, hosts, and the environment. The projects considered by the program could address, but are not restricted to, the following topics:

  • The use of engineering, computational, statistical, biological, physical, and chemical approaches, including models and mechanistic studies to understand molecular communication within the microbiome, and between microorganisms and the host and/or environment
  • New combinations of computational approaches, including life-, physical-, and social-science methods to understand scale-invariant principles as well as temporal and spatial variation in microbiome structure and function across different levels of analysis
  • Leveraging computational approaches and different types of datasets from a wide range of organisms, from microbes to humans, in diverse physical and social environments to understand the evolution of microorganisms in microbiomes and the co-evolution of microorganisms, environment, and host
  • The use of predictive ecological and evolutionary principles along with engineering, computational and statistical science to understand, predict, and engineer microbiome assembly
  • The use of data science and control theory approaches to understand the existence of functional redundancy and the role it may play in microbiome diversity and resiliency to changing environmental conditions
  • New computational, engineering, biological, physical-chemical and/or social networking approaches to understand and predict how a host’s genetic composition, physiology, and behavior influence the genetics, physiology, and behavior of the microbiome and vice versa
  • Cross-disciplinary approaches to understand the relationship between the microbiome and brain function in humans and other species
  • New models and cross-disciplinary approaches to understand, predict, and control how horizontal gene transfer affects the function and co-evolution of microbiome and host (and/or environment)

Projects concerning the development of novel experimental model or synthetic microbiomes in defined and controlled environments must demonstrate how these models will lead to generalizable principles that would explain and predict the characteristics of living systems.

URoL:MTM provides two tracks that support projects of different scale and scope:

  • URoL:MTM Track 1 (MTM 1): This track provides support for projects with a total budget (including indirect costs) of up to $500,000 and award duration of up to 3 years.
  • URoL:MTM Track 2 (MTM 2): This track provides support for projects with a total budget (including indirect costs) of up to $3,000,000 and award duration of up to 5 years. Track 2 projects are required to submit a Management Plan as part of Supplementary Documentation.

Contact Information

Cognizant Program Officer(s):

Please note that the following information is current at the time of publishing. See program website for any updates to the points of contact.