Award Abstract # 2133504
NSF Engineering Research Center for Precision Microbiome Engineering (PreMiEr)

NSF Org: EEC
Division of Engineering Education and Centers
Recipient: DUKE UNIVERSITY
Initial Amendment Date: August 9, 2022
Latest Amendment Date: November 15, 2024
Award Number: 2133504
Award Instrument: Cooperative Agreement
Program Manager: Randy Duran
rduran@nsf.gov
 (703)292-5326
EEC
 Division of Engineering Education and Centers
ENG
 Directorate for Engineering
Start Date: September 1, 2022
End Date: August 31, 2027 (Estimated)
Total Intended Award Amount: $26,000,000.00
Total Awarded Amount to Date: $13,703,000.00
Funds Obligated to Date: FY 2022 = $3,500,000.00
FY 2023 = $4,500,000.00

FY 2024 = $5,703,000.00
History of Investigator:
  • Claudia Gunsch (Principal Investigator)
    ckgunsch@duke.edu
  • Jennifer Kuzma (Co-Principal Investigator)
  • Anthony Fodor (Co-Principal Investigator)
  • Joseph Graves (Co-Principal Investigator)
  • Joe Brown (Co-Principal Investigator)
  • Jill Stewart (Former Co-Principal Investigator)
Recipient Sponsored Research Office: Duke University
2200 W MAIN ST
DURHAM
NC  US  27705-4640
(919)684-3030
Sponsor Congressional District: 04
Primary Place of Performance: Duke University
Box 90287, 121 Hudson Hall
Durham
NC  US  27708-0287
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): TP7EK8DZV6N5
Parent UEI:
NSF Program(s): ERC-Eng Research Centers
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01002526DB NSF RESEARCH & RELATED ACTIVIT

01002627DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 113E, 123E, 124E, 125E, 126E, 128E, 131E, 132E, 1480, 7680
Program Element Code(s): 148000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Microbes have colonized and adapted to most every environment on Earth, including the built environments that humans have created, such as the homes where we live and the pipes that bring us drinking water. It has been well established that microbial communities, or microbiomes, that colonize people have a direct influence on human health. The microbiome of the built environment, in particular, has gained increasing recognition for its key role in human health through its interaction with the human microbiome. However, despite this knowledge, no systematic infrastructure exists to decipher how microbial systems adapt to and grow within built environments, impeding our ability to diagnose built environment health and harness the power inherent to those microbiomes. The Engineering Research Center for Precision Microbiome Engineering (PreMiEr) will create microbiome-based diagnostic tools and develop microbiome engineering approaches to monitor and operate built environments that maximize human health protection. Informed by societal needs and research-stakeholder teams, PreMiEr's research design will work to prevent the spread of infectious agents, promote the colonization of beneficial microorganisms, and lead to strategies for controlling pandemics and antibiotic resistance-phenomena that have led to over six million deaths worldwide (as of June 2022) and cost the global economy an estimated $8 trillion in the last year alone. Integral to its research vision, PreMiEr will create diverse and inclusive interdisciplinary research and training hubs where engineers, microbiologists, social scientists, and ethicists work alongside theorists, model builders, and computational scientists to develop technologies that enable transformative engineering discoveries in safe, sustainable and responsible ways.

Our capacity to engineer microbiomes requires a fundamental understanding of concepts of community ecology and an ability to track, control, and model those interactions. To apply microbiome engineering to real-world systems, community level interactions must be integrated into a comprehensive, scalable modeling framework that requires iterative evaluation and validation in model testbeds. PreMiEr?s research organization is designed to generate fundamental understanding across these levels and functionalities, culminating in the development of a framework that enables the biodesign of smart and healthy built environments. PreMiEr will leverage advances in high-throughput genomic sequencing, high-resolution mass spectrometry, computational performance, and statistical modeling to unravel previously unknown mechanistic interactions. Enabling technologies will be developed to detect and define interactions in the built environment, including approaches that probe microbial dark matter for the development of built-environment health diagnostic tools; methods for targeted delivery of desired genetic features and microbial vectors; tools for fine in situ functional tuning; and predictive scalable statistical microbiome engineering models that consider high dimensionality, sparsity, and heterogeneity. These new technology elements will enable us to test hypotheses related to microbiome assembly and function. Importantly, by incorporating social scientists and ethicists into PreMiEr?s research framework, non-social scientists? work will be informed by consideration of the ethical, societal, and policy implications of their microbiome engineering discoveries. Through rigorous evaluation and iterative refinement of curricula, and institutional practices designed to support a culture of convergence and the dissemination of findings, PreMiEr will contribute to best practices in domestic training. The PreMiEr ERC provides immersive research and training experiences at the interface of multiple disciplines to address complex challenges, training the next generation of engineers and scientists with the technical and professional skills needed to compete in the emerging arenas of microbial science and engineering. Ultimately, PreMiEr?s work advances collaborations and discovery focused on environmental microbiomes to engineer healthy built environments.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 12)
Childs, Sarah K and Jones, A-Andrew D "A microtiter peg lid with ziggurat geometry for medium-throughput antibiotic testing and in situ imaging of biofilms" Biofilm , v.6 , 2023 https://doi.org/10.1016/j.bioflm.2023.100167 Citation Details
Ferdous, Jannatul and Kunkleman, Samuel and Taylor, William and Harris, April and Gibas, Cynthia J and Schlueter, Jessica A "A gold standard dataset and evaluation of methods for lineage abundance estimation from wastewater" Science of The Total Environment , v.948 , 2024 https://doi.org/10.1016/j.scitotenv.2024.174515 Citation Details
Hardwick, Andrew and Cummings, Christopher and Graves, Jr., Joseph and Kuzma, Jennifer "Can societal and ethical implications of precision microbiome engineering be applied to the built environment? A systematic review of the literature" Environment Systems and Decisions , v.44 , 2024 https://doi.org/10.1007/s10669-024-09965-y Citation Details
Jeje, Olusola and Ewunkem, Akamu J. and Jeffers-Francis, Liesl K. and Graves, Joseph L. "Serving Two Masters: Effect of Escherichia coli Dual Resistance on Antibiotic Susceptibility" Antibiotics , v.12 , 2023 https://doi.org/10.3390/antibiotics12030603 Citation Details
Ji, Zhicheng and Ma, Li "Controlling taxa abundance improves metatranscriptomics differential analysis" BMC Microbiology , v.23 , 2023 https://doi.org/10.1186/s12866-023-02799-9 Citation Details
LaMontagne, Connor D and Christenson, Elizabeth C and Rogers, Anna T and Jacob, Megan E and Stewart, Jill R "Relating Antimicrobial Resistance and Virulence in Surface-Water E. coli" Microorganisms , v.11 , 2023 https://doi.org/10.3390/microorganisms11112647 Citation Details
McCumber, Alexander W and Kim, Yeon Ji and Granek, Joshua and Tighe, Robert M and Gunsch, Claudia K "Soil exposure modulates the immune response to an influenza challenge in a mouse model" Science of The Total Environment , v.922 , 2024 https://doi.org/10.1016/j.scitotenv.2024.170865 Citation Details
Mullowney, Michael W. and Duncan, Katherine R. and Elsayed, Somayah S. and Garg, Neha and van der Hooft, Justin J. and Martin, Nathaniel I. and Meijer, David and Terlouw, Barbara R. and Biermann, Friederike and Blin, Kai and Durairaj, Janani and Gorostiol "Artificial intelligence for natural product drug discovery" Nature Reviews Drug Discovery , v.22 , 2023 https://doi.org/10.1038/s41573-023-00774-7 Citation Details
Prince, Joshua and Jones, A-Andrew D "Heterogenous biofilm mass-transport model replicates periphery sequestration of antibiotics in Pseudomonas aeruginosa PAO1 microcolonies" Proceedings of the National Academy of Sciences , v.120 , 2023 https://doi.org/10.1073/pnas.2312995120 Citation Details
Song, Kuncheng and Zhou, Yi-Hui "C3NA: correlation and consensus-based cross-taxonomy network analysis for compositional microbial data" BMC Bioinformatics , v.23 , 2022 https://doi.org/10.1186/s12859-022-05027-9 Citation Details
Song, Kuncheng and Zhou, Yi-Hui "Leveraging Scheme for Cross-Study Microbiome Machine Learning Prediction and Feature Evaluations" Bioengineering , v.10 , 2023 https://doi.org/10.3390/bioengineering10020231 Citation Details
(Showing: 1 - 10 of 12)

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