SBIR Phase I:Developing Vibrational spectroscopy with metasurface optics (VISMO) for label-free, high-resolution, high-throughput protein screening

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to facilitate improved biomanufacturing and the transition to a sustainable bioeconomy. Proteins are the working molecules of biology and can be used for products spanning sustainable fuels, pharmaceuticals, plastics, and packaging materials. Cell-based manufacturing can produce millions of variations of proteins, yet existing tools do not provide the resolution, throughput, or sensitivity to screen the cell sequence and structure.The resulting services and products will reduce the time and cost to optimize protein-based products, en-route to a sustainable bio-based economy and improved personal and planetary health. The approach will enable simultaneous, minute-scale measurement of millions of samples, increasing the suite of detectable molecules beyond any available technology.The technology will enable collection of dynamic information about protein-protein and protein-drug interactions will dramatically improve the lengthy and costly cycles associated with drug development and synthetic biology-based optimization of protein-based products and accelerate advances for the US bioeconomy. The technology may enable the transition to personalized medicine, where medical professionals can access patient-specific proteomic and drug-interaction data in real-time, to maintain wellness, monitor disease emergence and progression, improve treatment efficacy,_x000D_ and extend health spans. _x000D_ _x000D_ This project aims to develop vibrational spectroscopy with metasurface optics to screen for proteoforms. The research objectives are to determine protein sequence and structure, utilizing the vibrational scattering spectra of the protein. Aim 1 of this project will develop a nanostructured silicon chip that strongly amplifies the vibrationally-scattered light from proteins, for high-sensitivity analysis. Aim 2 of this project will develop cutting-edge machine learning algorithms to provide interpretability to the Raman spectra, including the wavenumber features that correspond to the primary, secondary, and tertiary structure of the protein. Aim 3 of this project will develop microfluidic capabilities that enable high-throughput sample processing, with up to 3 million molecules analyzed per square centimeter. Upon completion, this Phase I project will de-risk the technological foundations for label-free, high-resolution, high-speed protein screening and sequencing technologies._x000D_ _x000D_ 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.