DIGITAL LSPR FOR ENHANCED ASSAY SENSITIVITY
Systems, methods, and devices related to detecting a presence of an analyte and/or determining a concentration of analytes are provided. An analyte may be provided on an LSPR-active surface. The LSPR-active surface may comprise sensitivity enhancing labels. The analyte may induce a local change near the LSPR-active surface. The LSPR-active surface may be imaged with an imaging device for images before, during, or after a reaction takes place. Local regions of interest within the images may be analyzed to detect the local changes.
1 . A method for detecting an analyte in a sample, comprising:
capturing a series of two or more images of a sensor surface, wherein the sensor surface is capable of sustaining a localized surface plasmon resonance;
selecting one or more corresponding regions of interest in the series of two or more images;
measuring a change in color within the selected regions of interest over the series of two or more images; and
detecting an analyte based on the measured change in color.
2 . The method of claim 1 , wherein a limit of detection for detecting the analyte is better than 1 ng/mL.
3 . The method of claim 1 , wherein a limit of detection for detecting the analyte is better than 1 pg/mL.
4 . The method of claim 1 , wherein a limit of detection for detecting the analyte is better than 1 fg/mL.
5 . The method of claim 1 , further comprising determining a concentration of the analyte based on the measured change in color.
6 . The method of claim 1 , wherein the change in color is a change in RGB value of pixels in the corresponding regions of interest.
7 . The method of claim 1 , wherein the measured change in color is a change in color of light reflected from the sensor surface.
8 . The method of claim 1 , wherein each of the selected regions of interest is an area of the sensor surface of about or less than 5 um 2 .
9 . The method of claim 1 , wherein each of the selected regions of interest is a grid of 3×3 pixels.
10 . The method of claim 1 , wherein the series of two or more images are captured before and after the local analyte-induced change occurs.
11 . The method of claim 1 , wherein the analyte is selected from the group consisting of a peptide, a protein, an oligonucleotide, a DNA molecule, an RNA molecule, a virus, a bacterium, a cell, a lipid molecule, a carbohydrate molecule, a small organic molecule, a drug molecule, or an ion.
12 . The method of claim 1 , wherein the sensor surface is contacted with a primary binding component, the analyte, and a secondary binding component sequentially or simultaneously, wherein the secondary binding component is a sensitivity enhancing label.
13 . The method of claim 12 , wherein the sensitivity enhancing label is an enzyme that catalyzes a conversion of a reactant to an insoluble product, thereby forming a precipitate on the sensor surface.
14 . The method of claim 13 , wherein the sensitivity enhancing label catalyzes a reaction that results in a deposition of a polymer, a biopolymer, a chemical compound, or an enzymatic reaction product selected from a group consisting of inorganic compounds, organic compounds, chemiluminescent compounds, and fluorescent compounds.
15 . The method of claim 12 , wherein the sensitivity enhancing label is a metallic nanoparticle that is capable of inducing plasmon-plasmon coupling between the metallic nanoparticle and the sensor surface.
16 . The method of claim 1 , wherein the one or more corresponding regions of interest is randomly selected.
17 . The method of claim 16 , wherein a plurality of corresponding regions of interest is selected.
18 . The method of claim 17 , wherein the plurality of corresponding regions of interest is 10 or more corresponding regions of interest.
19 . The method of claim 17 , wherein the plurality of corresponding regions of interest is 100 or more corresponding regions of interest.
20 . The method of claim 1 , wherein an integration time required for capturing the series of two or more images is less than 50 ms.
21 . The method of claim 1 , wherein the analyte is present in the sample in an amount of 100 ng/mL or less.
22 . The method of claim 1 , wherein the analyte is present in the sample in an amount of 1 ng/mL or less.
23 . The method of claim 1 , wherein the analyte is present in the sample in an amount of 1 pg/mL or less.
24 . The method of claim 1 , 13 , 15 , or 21 further comprising receiving a report comprising a result of the method and making a healthcare decision based on the reported result, wherein the sample is a patient sample.
25 . A system for detecting an analyte in a sample, the system comprising:
a sensor surface, wherein the sensor surface is capable of sustaining a localized surface plasmon resonance;
an optical imaging device, wherein the optical imaging device is capable of capturing a series of two or more images; and
a processor, wherein the processor is capable of selecting one or more corresponding regions of interest in the series of two or more images, measuring a change in color within the selected regions of interest, and detecting an analyte based on the measured change in color.
26 . The system of claim 25 , wherein a limit of detection for detecting the analyte is better than 1 ng/mL.
27 . The system of claim 25 , wherein a limit of detection for detecting the analyte is better than 1 pg/mL.
28 . The system of claim 25 , wherein a limit of detection for detecting the analyte is better than 1 fg/mL.
29 . The system of claim 25 , wherein the processor is capable of determining a concentration of the analyte based on the measured change in color.
30 . The system of claim 25 , wherein the change in color is a change in RGB value of pixels in the corresponding regions of interest.
31 . The system of claim 25 , wherein the sensor surface is opaque and reflects light.
32 . The system of claim 25 , wherein each of the corresponding regions of interest is an area of the sensor surface of about or less than 5 um 2 .
33 . The system of claim 25 , wherein each of the corresponding regions of interest is a grid of 3×3 pixels.
34 . The system of claim 25 , wherein the series of two or more images are captured before and after the change in color.
35 . The system of claim 25 , wherein the analyte is selected from the group consisting of a peptide, a protein, an oligonucleotide, a DNA molecule, an RNA molecule, a virus, a bacterium, a cell, a lipid molecule, a carbohydrate molecule, a small organic molecule, a drug molecule, or an ion.
36 . The system of claim 25 , further comprising a fluidic system for delivery of a sample and assay reagents to the sensor surface, wherein the assay reagents comprise a primary binding component and a secondary binding component, and wherein the secondary binding component comprises a sensitivity enhancing label.
37 . The system of claim 36 , wherein the sensitivity enhancing label is an enzyme that catalyzes a conversion of a reactant to an insoluble product, thereby forming a precipitate on the sensor surface.
38 . The system of claim 37 , wherein the enzyme catalyzes a reaction that results in a deposition of a polymer, a biopolymer, a chemical compound, or an enzymatic reaction product selected from a group consisting of inorganic compounds, organic compounds, chemiluminescent compounds, and fluorescent compounds.
39 . The system of claim 36 , wherein the sensitivity enhancing label is a metallic nanoparticle that is capable of inducing plasmon-plasmon coupling between the metallic nanoparticle and the sensor surface.
40 . The system of claim 25 , wherein the processor is capable of randomly selecting one or more corresponding regions of interest in the series of two or more images.
41 . The system of claim 40 , wherein the processor is capable of selecting a plurality of corresponding regions of interest.
42 . The system of claim 41 , wherein the plurality of corresponding regions of interest is 10 or more corresponding regions of interest.
43 . The system of claim 41 , wherein the plurality of corresponding regions of interest is 100 or more corresponding regions of interest.
44 . The system of claim 25 , wherein an integration time of the optical imaging device is less than 50 ms.
45 . The system of claim 25 , wherein the analyte is present in the sample in an amount of 100 ng/mL or less.
46 . The system of claim 25 , wherein the analyte is present in the sample in an amount of 1 ng/mL or less.
47 . The system of claim 25 , wherein the analyte is present in the sample in an amount of 1 pg/mL or less.
48 . The system of claim 25 , 37 , 39 , or 45 , wherein the sample comprises a patient sample and the detection of the analyte is used for clinical diagnostic applications.
49 . A computer readable medium including code for causing a computer to execute a method comprising:
selecting one or more corresponding regions of interest, in each of a series of two or more images of a sensor surface, wherein the sensor surface is capable of sustaining a localized surface plasmon resonance;
measuring a change in color by comparing the color for corresponding regions of interest in the series of two or more images; and
determining presence of an analyte based on the measured change in color.
50 . The computer readable medium of claim 49 , wherein the one or more corresponding regions of interest is randomly selected.
51 . The computer readable medium of claim 50 , wherein a plurality of regions of interest is selected.
52 . The computer readable medium of claim 49 , wherein the change in color is a change in RGB value of pixels within the corresponding region of interest.
53 . The computer readable medium of claim 52 , wherein the change in RGB value is measured according to the formula D=√{square root over ((ΔR) 2 +(ΔG) 2 (ΔB) 2 )}{square root over ((ΔR) 2 +(ΔG) 2 (ΔB) 2 )}{square root over ((ΔR) 2 +(ΔG) 2 (ΔB) 2 )} wherein ΔR, ΔG, and ΔB correspond to changes in red, green and blue pixel values in an image.
54 . The computer readable medium of claim 49 further comprising calculating a moment for the distribution of changes in RGB or greyscale values.
55 . The computer readable medium of claim 49 , further comprising using pattern mining algorithms to delineate areas of the sensor surface that exhibit different responses to contact by the analyte.