Determining extracellular analyte concentration with nanoplasmonic sensors
Inventors
Raphael, Marc P. • Christodoulides, Joseph A. • Byers, Jeff M. • Delehanty, James B.
Assignees
Publication Number
US-10761028-B2
Publication Date
2020-09-01
Expiration Date
2036-06-20
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Abstract
Methods and systems for determining extracellular concentration data of an analyte are disclosed. A method for determining extracellular concentration data of an analyte includes receiving sensor data from one or more arrays of functionalized plasmonic nanostructures on a localized surface plasmon resonance imaging chip in contact with a fluid containing at least one living cell for a plurality of times, determining intensity data for the one or more arrays, determining fractional occupancy based on the intensity data, and determining extracellular concentration data based on the fractional occupancy data. A system for determining extracellular concentration data of an analyte includes a LSPRi chip, a sensor component, an intensity component, a fractional occupancy component, a concentration component, and a processor to implement the components.
Core Innovation
Methods and systems for determining extracellular concentration data of an analyte are disclosed. The method includes receiving sensor data from one or more arrays of functionalized plasmonic nanostructures on a localized surface plasmon resonance imaging (LSPRi) chip in contact with a fluid containing at least one living cell for a plurality of times. Intensity data is determined for the nanostructures based on the sensor data. Fractional occupancy data is determined from the intensity data, and extracellular concentration data is derived from the fractional occupancy data. The system includes an LSPRi chip, sensor component, intensity component, fractional occupancy component, concentration component, and a processor implementing these components.
The key problem addressed is the measurement of extracellular protein concentrations and gradients secreted by living cells in real time, non-invasively, and without disrupting cellular signaling pathways. Traditional methods such as fluorescent tagging are limited by size and interference with protein secretion or signaling, and spectrometry-based techniques require high light exposure and are limited to single array quantification. The difficulty lies in establishing causal relationships between secreted protein concentrations and cell fate due to these limitations.
The invention overcomes these barriers by employing arrays of gold plasmonic nanostructures for real-time, label-free imaging of secreted protein concentrations with high temporal and spatial resolution. The invention leverages a discovered linear relationship between normalized LSPRi image intensity data and fractional occupancy, enabling concentration determination without the need for a spectrometer. A temporal filtering approach based on the law of mass action and reaction rate constants processes fractional occupancy data to accurately map extracellular analyte concentrations spatially and temporally.
Claims Coverage
The patent contains one independent method claim covering an imaging method for determining analyte concentrations using plasmonic nanostructures and LSPRi technology, focusing on measurement and data processing without a spectrometer.
Imaging method using functionalized plasmonic nanostructures on an LSPRi chip
Forming at least one array of functionalized plasmonic nanostructures on an LSPRi chip contacting a fluid containing an analyte, illuminating with visible light, and imaging sensor data over multiple times using camera imagery.
Determination of fractional occupancy based on linear relationship with image intensity
Determining fractional occupancy data from brightness intensity data of the nanostructures where a linear relationship exists between camera intensity data and fractional occupancy, enabling accurate analysis without spectrometer usage.
Determination of analyte concentration using law of mass action from fractional occupancy data
Calculating analyte concentration data from fractional occupancy data based on the law of mass action kinetic model, including using subsampling via a temporal filter and calculation of time-derivative fractional occupancy.
Temporal filtering framework for analyzing fractional occupancy data
Using a temporal filter with defined center and width to assign weights to fractional occupancy data, calculating local linear models, and deriving probability distributions as negative log likelihood or exact bivariate normal distributions for concentration determination.
Mapping analyte movement spatially and temporally from concentration data
Determining analyte movement in the fluid by mapping concentration data over time and space from one or more arrays of functionalized nanostructures.
Calibration of the LSPRi chip by saturating nanostructures with known analyte concentrations
Calibrating arrays by applying a saturating known analyte concentration to relate intensity data to fractional occupancy.
The claims cover a comprehensive method and system for label-free, real-time determination of extracellular analyte concentrations using functionalized plasmonic nanostructures and imaging without a spectrometer. It centers on establishing a linear intensity-to-fractional occupancy relationship, advanced temporal data filtering, and application of kinetic binding models for precise concentration mapping and analyte movement tracking.
Stated Advantages
Enables measurement of extracellular analyte concentrations in real time without disrupting cellular signaling pathways.
Label-free detection avoids issues associated with fluorescent tags such as photobleaching and interference with secretion.
Eliminates need for spectrometer, reducing light exposure harmful to live cells and allows simultaneous imaging of multiple arrays.
High temporal (approximately 15 seconds) and spatial (over 130 micrometers) resolution of analyte secretion mapping.
Integration with traditional microscopy techniques allows correlative imaging methods.
Documented Applications
Measurement and spatio-temporal mapping of secreted protein concentrations from single living cells and cell clusters.
Quantification of steady-state and burst-like secretions of antibodies from hybridoma cells.
Application in co-culture experiments to correlate secretions of one cell type with responses of another.
Studying cell differentiation, motility, proliferation, and cell signaling pathways involving extracellular proteins.
Potential for multiplexing to quantify various secreted proteins in parallel using lithography-based printing methods.
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