SBIR/STTR Research Award

Vibrational spectroscopy with metasurface optics (VISMO) for high-throughput identification of protein post-translational modifications

Award identifier ed5ab3f075083cd6802083f2ef40dc69b664ff0318a8e9b72476adba6d06fb92Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$289,866

Program and phase

SBIR · Phase I

Award year

2023

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
PUMPKINSEED TECHNOLOGIES INC
Proposal award date
2023-09-22
Contract end date
2024-09-21
UEI
Y3J2KMX477W5
Solicitation number
PA22-176
Topic code
400

Research abstract

Project Summary/Abstract Proteins are critical to a wide array of cellular processes - from cell signaling to immune responses, nutrient transport, growth, and metabolic regulation. Proper function of proteins depends sensitively on the type, location, and abundance of post-translational modifications (PTMs). Aberrations in PTM properties can degrade protein function and compromise the physiology and function of the cells in which they reside. Indeed, altered PTMs have been implicated in a variety of diseases, including cancers, auto-immune diseases, neurodegenerative diseases, and inflammation. Nucleic acid sequencing gives almost no insight into PTM attributes, and sensitive and high-throughput characterization and quantification of PTMs remains a daunting challenge for mass spectroscopy (MS) and immunoassays. Pumpkinseed is developing an optics-based and label-free approach to measure protein PTMs, termed Vibrational Spectroscopy with Metasurface Optics (VISMO). VISMO offers high-speed analysis of millions of proteins – including their sequence, structure, and interactions – with three key advantages over other proteomics solutions: (1) In a label-free format, we uniquely identify each molecule via its vibrational scattering spectra, rather than relying on lower-resolution fluorescent tagging. (2) Using nanostructured Si chips, we create highly efficient optical resonators that both dramatically amplify the signal-to-noise ratio – even for very low abundance biomarkers – and increase sample throughput, with simultaneous measurement of ~3 million proteins per square centimeter. (3) We use cutting-edge machine learning (ML) algorithms to dissect information-rich features from the vibrational spectra, including the wavenumbers that correspond to the primary, secondary, and tertiary structure of the protein, as well as changes related to protein or small-molecule binding. Our Phase I proposal will develop this revolutionary platform for sensitive, high-throughput, and high-resolution protein detection, including their abundance, sequence, and PTMs. Aim 1 develops sensors that enable sensitive, few-to-single-molecule spectroscopy, builds our catalog of spectra for particular amino acids, short peptide sequences, and PTMs; and develops machine learning (ML) algorithms that provide interpretability to each molecule’s optical scattering signature. Aim 2 advances our methods for protein sequencing using chemical cleavage and our patented ‘sequencing by subtraction’ methodology. Phase I results will form the foundation of our Phase II proposal, with potentially far-reaching impacts on whole-proteome sequencing and protein-profiling of the vast repertoire of cell types. Biotherapeutic companies and academic researchers studying intact, native proteins will value the high-resolution that Pumpkinseed’s platform offers compared to existing ELISA-type assays, and the higher-sensitivity and throughput compared to traditional mass spectrometry. Our approach provides a new methodology for probing protein structure and interactions in order to reveal new dimensions of disease etiology and distinct opportunities for new therapeutic development.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

4 SBIR/STTR records share this UEI (2023–2025). Reported award amounts total $2,167,185. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

Department of Health and Human Services

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.