Microbes attached to surfaces, commonly known as biofilms, represent multi-million dollar challenges and opportunities in municipal water, marine, manufacturing and oil and gas sectors and a range of other engineering and medical applications. The study of biofilms at the cellular level and the study of materials at the atomic level generate extremely large amounts of rich data. To mine this data and establish connections between biofilm growth and material properties, this Research Infrastructure Improvement Track-2 Focused EPSCoR Collaborations (RII Track-2 FEC) award will form a new collaboration between South Dakota School of Mines and Technology, Montana State University, the University of Nebraska - Omaha and the University of South Dakota to develop Big Data Analytic Tools. This team will develop the Biofilms Data and Information Discovery system (Biofilm-DIDs) to collect and combine these large data sets using artificial intelligence to analyze and predict gene responses and biofilm characteristics influenced by surface properties. By accomplishing this goal the team intends to rapidly accelerate the pace of discovery of new materials to control and leverage biofilm growth. This project will provide education, training and workforce development opportunities for a diverse cohort of junior faculty and post-doctoral researchers and graduate, undergraduate and high-school teachers and students.
The primary objective of this project is to develop Big Data Analytic Tools for understanding rules of life in biofilms on technologically relevant materials modified with an emerging class of single-atom thick, two-dimensional (2D) materials. This will be accomplished by developing the Data Driven Material Discovery (DDMD) Center for Bioengineering Innovation, which will coalesce diverse infrastructure in bioscience, computer science, and material science from South Dakota School of Mines & Technology, Montana State University, the University of Nebraska-Omaha and the University of South Dakota to develop the unique Biofilm-DID system. The DDMD Center will focus on the development of novel interdisciplinary approaches and data analytics to track biofilm phenotypes on 2D materials, coupled with -omics analyses of sulfate-reducing biofilm phenotypes to discover rules of biofilm assembly and organization governed by atomic-scale material surface features. The DDMD Center?s areas of research will include: big data mining, machine learning, and predictive modeling; 2D materials for biological applications; and biofilm composition and diversity. The Biofilm-DIDs will be developed, calibrated and validated to provide a scientific platform for interrogating biological mechanisms in response to nano-scale properties. This platform will be leveraged to understand how the substrate crystallographic orientations and point defects in coatings affect gene expression, signaling pathways, metabolites, and structure formation controlling stress resistance, extracellular electron transfer, and biocorrosion mechanisms of biofilms. The DDMD center infrastructure will offer a series of education, training, and workforce development opportunities in data analytics and informatics approaches customized to material and biofilm sciences.
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.
