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High-Throughput High-Content Nanoscale Extracellular Vesicle Analysis

Award Number: R43GM156162
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 07/05/2024
PERIOD OF PERFORMANCE END DATE: 06/30/2026

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High-Throughput High-Content Nanoscale Extracellular Vesicle Analysis - PROJECT SUMMARY There is growing recognition that extracellular vesicles (EVs)¾micrometer- or nanometer-sized lipid particles containing protein and nucleic acid cargoes (information)¾are highly promising for new diagnostics/prognostics and experimental therapies. There is, however, a key unmet need for technical platforms able to solve a fundamental problem confounding the exploitation of EV information in biology and medicine. That is, because EV populations are naturally complex and thus heterogeneous, it can be challenging to detect and characterize unique subpopulations-of-interest present only at low abundance in a sample containing other (normal) EVs from, e.g., a host. In this Phase I project, we will apply a novel technology platform designed to address the problem of resolving multiple EV subpopulations at the single- particle level by directly identifying specific surface proteins of dispersed particles, through rapid highly- multiplexed fluorescence imaging analysis We have chosen to focus on analyzing medically important categories of EVs called exosomes (here from human cancer cells) and outer membrane vesicles (OMVs; from bacterial cells). Our goal ultimately is to develop a unique imaging platform for the high-content, high- throughput analysis of the surface proteins of single exosomes or OMVs present in clinically relevant specimens. Briefly, our innovative platform will simultaneously analyze, in one pass, up to 10 known or potential exosome/OMV surface markers in up to 107 dispersed particles obtained from a biofluid such as blood, saliva, or stool. Unlike conventional methods, our platform can rapidly: a) analyze diverse EVs; b) simultaneously read multiple protein surface markers (cargoes) and thus detect subpopulations-of-interest; c) read single particle protein surface cargoes, greatly raising information yield compared to typical bulk methods producing pooled cargo data; and d) identify exosome/OMV subpopulations based on unique combinations of biomarkers from points a-c. We propose three stepwise aims in development of a highly multiplexed, high throughput platform for nano-scale EV detection: (1) construction of the instrument based on an existing high speed hyperspectral designed specifically for cells and tissue sections; (2) testing and calibration of the platform using fluorescent nanoparticles and fluorescently labeled liposomes; and (3) application of the platform to detecting exosomes from human cancer cell lines or OMVs from Gram-negative and Gram-positive bacteria (represented by E. coli and S. aureus, respectively). We anticipate that our platform could become a new tool for EV research; a new diagnostic/prognostic tool for studying and managing pathologies in which EV analysis is clinically informative; and a novel method for monitoring normal or aberrant microbiome status.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = $298,999 )
2024	2024	NUMENTUS TECHNOLOGIES INC	333 RAVENSWOOD AVE	MENLO PARK	CA	94025	SAN MATEO	USA	Biomedical Research and Research Training	000	1	7/9/2024	NEW	$298,999
														Subtotal = $298,999

Grand Total All Awards = $298,999

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High-Throughput High-Content Nanoscale Extracellular Vesicle Analysis

Award Number: R43GM156162

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 07/05/2024

PERIOD OF PERFORMANCE END DATE: 06/30/2026

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