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PFI has five broad goals, as set forth by the American Innovation and Competitiveness Act of 2017 ("the Act", S.3084 - 114th Congress; Sec. 602. Translational Research Grants): (1) identifying and supporting NSF-sponsored research and technologies that have the potential for accelerated commercialization; (2) supporting prior or current NSF-sponsored investigators, institutions of higher education, and non-profit organizations that partner with an institution of higher education in undertaking proof-of-concept work, including the development of technology prototypes that are derived from NSF-sponsored research and have potential market value; (3) promoting sustainable partnerships between NSF-funded institutions, industry, and other organizations within academia and the private sector with the purpose of accelerating the transfer of technology; (4) developing multi-disciplinary innovation ecosystems which involve and are responsive to the specific needs of academia and industry; (5) providing professional development, mentoring, and advice in entrepreneurship, project management, and technology and business development to innovators.

In 2016, the National Science Foundation (NSF) unveiled a set of "Big Ideas," 10 bold, long-term research and process ideas that identify areas for future investment at the frontiers of science and engineering (seehttps://www.nsf.gov/news/special_reports/big_ideas/index.jsp). The Big Ideas represent unique opportunities to position our Nation at the cutting edge of global science and engineering leadership by bringing together diverse disciplinary perspectives to support convergence research. As such, when responding to this solicitation, even though proposals must be submitted tothe Division of Emerging Frontiers in the Directorate for Biological Sciences (BIO/EF),once received, the proposals will be managed by a cross-disciplinary team of NSF Program Directors. The purpose of the Understanding the Rules of Life: Epigenetics (URoL:Epigenetics) program is to enable innovative research and to promote multidisciplinary education and workforce training in the broad area of epigenetics. The URoL:Epigenetics program is a widecollaborationacross Directorates/Offices within the National Science Foundation with a focus on understanding the relationship between epigenetic mechanisms associated with environmental change, the resultant phenotypes of organisms, and how these mechanisms lead to robustness and adaptability of organisms and populations. Understanding the Rules of Life (URoL): PredictingPhenotypeis one of NSF's 10 Big Ideasand is focused on predicting the set of observable characteristics (phenotype) from the genetic makeup of the individual and the nature of its environment.

The Understanding the Rules of Life: Microbiome Theory and Mechanisms (URoL:MTM) program is an integrative collaborationacross Directorates and Offices within the National Science Foundation. The objective of URoL:MTM is to understand and establish the theory and mechanisms that govern the structure and function of microbiomes, a collection of microbes in a specific habitat/environment. This may include but is not limited to host-associated microbiomes, such as those with humans and other organisms, where i) the microbiome impacts host physiology, behavior, development, and fitness; ii) the host influences the metabolic activity, dynamics and evolution of the microbiome, and iii) the environment (biological, chemical, physical, and social) influences and is influenced by both the host and the microbiome. Recent progress has transformed our ability to identify and catalogue the microbes present in a given environment and measure multiple aspects ofbiological, chemical, physical, and social environments that affect the interactions among the members of the microbiome, the host, and/or habitat. Much descriptive and correlative work has been performed on many microbiome systems, particularly those in the human, soil, aquatic, and built environments. This research has resulted in new hypotheses about the microbiome's contributions to potential system function or dysfunction. The current challenge is to integrate the wide range of accumulated data and information and build on them to develop new causal/mechanistic models or theories of interactions and interdependencies across scales and systems.