U.S. patent application number 17/489193 was filed with the patent office on 2022-03-17 for systems and methods for performing immunoassays.
The applicant listed for this patent is THE REGENTS OF THE UNIVERSITY OF MICHIGAN. Invention is credited to Pengyu Chen, Meng Ting Chung, Timothy T. Cornell, Katsuo Kurabayashi, Walker M. McHugh, Thomas P. Shanley, Yujing Song.
Application Number | 20220082559 17/489193 |
Document ID | / |
Family ID | |
Filed Date | 2022-03-17 |
United States Patent
Application |
20220082559 |
Kind Code |
A1 |
Chen; Pengyu ; et
al. |
March 17, 2022 |
SYSTEMS AND METHODS FOR PERFORMING IMMUNOASSAYS
Abstract
Provided herein are systems and methods for assays. In
particular, provided herein are systems and methods for performing
high throughput immunoassays.
Inventors: |
Chen; Pengyu; (Ann Arbor,
MI) ; Kurabayashi; Katsuo; (Ann Arbor, MI) ;
Cornell; Timothy T.; (Ann Arbor, MI) ; Shanley;
Thomas P.; (Ann Arbor, MI) ; Chung; Meng Ting;
(Ann Arbor, MI) ; Song; Yujing; (Ann Arbor,
MI) ; McHugh; Walker M.; (Dexter, MI) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
THE REGENTS OF THE UNIVERSITY OF MICHIGAN |
Ann Arbor |
MI |
US |
|
|
Appl. No.: |
17/489193 |
Filed: |
September 29, 2021 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
15551164 |
Aug 15, 2017 |
11137394 |
|
|
PCT/US2016/018060 |
Feb 16, 2016 |
|
|
|
17489193 |
|
|
|
|
62245066 |
Oct 22, 2015 |
|
|
|
62116741 |
Feb 16, 2015 |
|
|
|
International
Class: |
G01N 33/543 20060101
G01N033/543; B01L 3/00 20060101 B01L003/00; C40B 40/10 20060101
C40B040/10 |
Goverment Interests
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
[0002] This invention was supported by Grant No. 1263889 awarded by
the National Science Foundation. The government has certain rights
in the invention.
Claims
1.-47. (canceled)
48. A device, comprising: a transparent substrate having a first
broad surface; an array of nanoparticles coupled to the first broad
surface of the transparent substrate, wherein the array of
nanoparticles is patterned onto the first broad surface using an
adhesion layer and is functionalized with antibodies specific for
target material of a sample; and a microfluidic channel in fluid
communication with the array of nanoparticles, wherein the
microfluidic channel has an inlet and an outlet supporting
pump-driven fluid flow through the microfluidic channel; wherein
the device is operable in an assessment mode wherein: the
microfluidic channel contains a sample, comprising a target
component, from a subject, an interaction between the target
component and the antibodies functionalized at the array of
nanoparticles produces a set of signals associated with light
scattering, and the set of signals is detected, at an optical
detection platform, from the transparent substrate.
49. The device of claim 48, wherein the array of nanoparticles is
patterned with an aminated silane layer.
50. The device of claim 48, wherein the array of nanoparticles is
arranged for multiplexed detection of different targets of said
target material of the sample, with distinct antibodies positioned
at different locations within the array.
51. The device of claim 48, wherein the array of nanoparticles is
structured for specific binding of different epitopes of said
target material of the sample.
52. The device of claim 48, wherein the array of nanoparticles
comprises particles composed of at least one of gold, silver,
copper, titanium, and chromium fabricated into at least one of:
nanorods, nanostars, nanopyramids, nanodiamonds, nanorings, and
core-shells.
53. The device of claim 48, wherein the transparent substrate is
structured for transmission of light corresponding to at least one
of absorbance and scattering of light from the array of
nanoparticles.
54. The device of claim 48, wherein said antibodies are attached to
nanoparticle surfaces via a linker, and wherein the linker
comprises a thiol linker.
55. The device of claim 48, wherein the microfluidic channel
comprises a reservoir for supplying the sample to the array of
nanoparticles.
56. The device of claim 48, wherein the microfluidic channel has a
volumetric capacity greater than 10 nL.
57. The device of claim 48, wherein the microfluidic channel has a
first channel dimension at one of the inlet and the outlet that is
different than a second channel dimension at an intermediate
portion of the microfluidic channel.
58. The device of claim 48, wherein said target material of the
sample comprises at least one of: cytokines, proteins, antibodies,
and nucleic acids.
59. The device of claim 48, wherein the transparent substrate is
treated with plasma for material removal.
60. The device of claim 48, wherein the sample comprises a saliva
sample.
61. The device of claim 48, further comprising: a detection
apparatus comprising the optical detection platform, wherein the
optical detection platform comprises a lens operable to transmit
light from an interaction between target material of the sample and
the array of nanoparticles, through a filter and to a sensor
subsystem in communication with a computing subsystem for
processing the set of signals generated from the sensor
subsystem.
62. The device of claim 48, further comprising a syringe pump in
fluid communication with the microfluidic channel.
63. A method, comprising: receiving a sample into a reservoir;
transmitting the sample from the reservoir into a microfluidic
channel, by way of a pump, and into communication with an array of
nanoparticles coupled to a broad surface of a transparent
substrate, wherein the array of nanoparticles is patterned onto the
first broad surface using an adhesion layer and is functionalized
with antibodies specific for target material of the sample;
promoting an interaction between said target material and said
antibodies functionalized at the array of nanoparticles; and
detecting a set of signals produced from the interaction, through
the transparent substrate.
64. The method of claim 63, wherein the sample comprises a saliva
sample.
65. The method of claim 63, wherein the interaction is associated
with localized surface plasmon resonance (LSPR).
66. The method of claim 63, wherein said target material of the
sample comprises at least one of: cytokines, proteins, antibodies,
and nucleic acids.
67. The method of claim 63, further comprising performing
multiplexed detection of different targets of said target material
of the sample, with distinct antibodies positioned at different
locations within the array of nanoparticles.
Description
[0001] The present application is a continuation of U.S. patent
application Ser. No. 15/551,164, filed Aug. 15, 2017, which is a
National Stage Application of PCT/US2016/018060, filed Feb. 16,
2016, which claims priority to U.S. Provisional Patent Application
Ser. No. 62/116,741 filed Feb. 16, 2015, and U.S. Provisional
Patent Application Ser. No. 62/245,066 filed Oct. 22, 2015, each of
which are hereby incorporated by reference in their entireties.
FIELD OF THE DISCLOSURE
[0003] Provided herein are systems and methods for performing
assays. In particular, provided herein are systems and methods for
performing high throughput immunoassays.
BACKGROUND
[0004] Cytokines are bioactive proteins responsible for cell
signaling and regulating the maturation, growth, and responsiveness
of immune cells (Opal, S. M. & DePalo, V. A. Chest 117,
1162-1172 (2000); Rothenberg, E. V. Nat. Immunol. 8, 441-444
(2007)). Quantifying cytokines in human serum provides highly
valuable clinical information to monitor the immune status of hosts
and adjust therapies in different inflammatory disease conditions,
such as sepsis (Damas, P., et al. Crit. Care Med. 25, 405-412
(1997)), cancer (Lippitz, B. E. Lancet Oncol. 14, E218-E228
(2013)), lupus (Maczynska, I., et al. Immunol. Lett. 102, 79-82
(2006)), and graft-versus-host disease (GVHD) (Visentainer, J. E.
L., et al. Exp. Hematol. 31, 1044-1050 (2003)). Given the
complexity and dynamic nature of the human immune system, detection
and trending of biomarker signatures and subtle changes occurring
during a diseased state requires rapid analysis of a complex panel
of multiple cytokines at high accuracy, sensitivity and throughput.
However, conventional methods based on fluorescence sandwich
immunoassays fall short of meeting this demand as they face
stringent limitations on their practical implementation in an ideal
immune monitoring approach. These limitations arise primarily due
to the need for multiple time-consuming labeling and washing
processes while consuming a large sample volume. At present, no
assay exists that satisfies all the requirements of near-real-time
immune status monitoring that involve analysis of complex
biological samples.
[0005] Systems and methods for high-throughput immunoassays are
needed.
SUMMARY
[0006] Provided herein are systems and methods for performing
assays. In particular, provided herein are systems and methods for
performing high throughput immunoassays.
[0007] Embodiments of the present disclosure provide multiplex
capable LSPR immunoassays that meet a need for rapid (e.g., near
real time), accurate immunoassays (e.g. for use in beside
diagnostics). The LSPR assays are as accurate as existing ELISA
assays but provide the advantage of increased speed and multiplex
capability. In addition, the LSPR immunoassays are able to analyze
small volumes of complex patient samples (e.g., serum).
[0008] For example, in some embodiments, the present disclosure
provides a localized surface plasmon resonance device (LSPR),
comprising: a) an array of metal spots (e.g., gold or other noble
metal as a nanorods, sphere, pyramid, bipyramid, star or other
shape) localized on e.g., glass or thermoplastic substrate, wherein
the metal spots comprise antibodies specific for at least one
polypeptide; and b) a plurality of microfluidic channels in fluid
communication with the array. In some embodiments, the antibodies
comprise a plurality (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) of
antibodies, wherein each antibody is specific for a different
polypeptide. In some embodiments, the polypeptides are cytokines,
polypeptides, antibodies, or nucleic acids. In some embodiments,
the cytokines are selected from, for example, interleukin-2 (IL-2);
interleukin-4 (IL-4); interleukin-6 (IL-6); interleukin-10 (IL-10);
interferon-gamma (IFN-.gamma.); tumor-necrosis-factor alpha
(TNF-.alpha.) acylation stimulating protein, adipokine,
albinterferon, CCL1, CCL11, CCL12, CCL13, CCL14, CCL15, CCL16,
CCL17, CCL18, CCL19, CCL2, CCL20, CCL21, CCL22, CCL23, CCL24,
CCL25, CCL26, CCL27, CCL28, CCL3, CCLS, CCL6, CCL7, CCL8, CCL9,
colony-stimulating factor, CX3CL1, CX3CR1, CXCL1, CXCL10, CXCL11,
CXCL13, CXCL14, CXCL15, CXCL16, CXCL17, CXCL2, CXCL3, CXCL5, CXCL6,
CXCL7, CXCL9, erythropoietin, Gc-MAF, granulocyte
colony-stimulating factor, granulocyte macrophage
colony-stimulating factor, hepatocyte growth factor, IL-17, IL1A,
IL1B, inflammasome, interferome, interferon, interferon beta 1a,
interferon beta 1b, interferon gamma, interferon type I, interferon
type II, interferon type III, interferon-stimulated gene,
interleukin 1 family, interleukin 1 receptor antagonist,
interleukin 12, interleukin 12 subunit beta, interleukin 13,
interleukin 16, interleukin 2, interleukin 23, interleukin 23
subunit alpha, interleukin 34, interleukin 35, interleukin 7,
interleukin 8, interleukin-36, leukemia inhibitory factor,
leukocyte-promoting factor, lymphokine, lymphotoxin, lymphotoxin
alpha, lymphotoxin beta, macrophage colony-stimulating factor,
macrophage inflammatory protein, macrophage-activating factor,
monokine, myokine, myonectin, nicotinamide
phosphoribosyltransferase, oncostatin M, oprelvekin, platelet
factor 4, proinflammatory cytokine, promegapoietin, RANKL, stromal
cell-derived factor 1, talimogene laherparepvec, XCL1, XCL2, XCR1
Interleukin-1, Interleukin-1 receptor antagonist, Interleukin-2,
Interleukin-2 receptor antagonist, Interleukin-4, Interleukin-6,
Interleukin-8, Interleukin-10, Interleukin-12, Interleukin-17,
Interluekin-23, Tumor necrosis factor alpha, Interferon gamma,
Granzyme B, HSP1AB, MMP-8, MIP-1a, antibodies (e.g., monoclonal or
polyclonal), nucleic acids (e.g., DNA, mRNA, miRNA, lncRNA),
nucleic acid probes, Chemokine (c-c motif) ligand 3 (Macrophage
inflammatory protein 1-alpha), Matrix metalloproteinase-8, or Heat
shock protein 70 A1B. In some embodiments, the microfluidic
channels are orthogonal to the array of metal particles. In some
embodiments, the device comprises at least 5 (e.g., 10 or more)
parallel microfluidic channels. In some embodiments, the
microfluidic channels have a volume of approximately 10 nl to 10
.mu.l (e.g., 50 to 500 nL). In some embodiments, each of the
microfluidic channels has an inlet port and an outlet port. In some
embodiments, the microfluidic channels are constructed of PDMS or
thermoplastic. In some embodiments, the substrate comprises at
least 100 (e.g., at least 200, at least 300, at least 400, at least
500, at least 750, or at least 1000) antibodies. In some
embodiments, the substrate is treated with oxygen plasma, UV/ozone,
or silanization. In some embodiments, the antibodies are attached
to said substrate via linker (e.g., a C1-C10 bifunctional thiol
linker).
[0009] In some embodiments, the substrate further comprises a
plurality of microelectrodes configured for AC electroosmosis,
wherein the microelectrodes are in operable communication with the
array of metal particles. In some embodiments, each of the arrays
of metal nanoparticles is in operable communication with a pair of
microelectrodes. In some embodiments, the microelectrodes are
configured to deliver alternating current.
[0010] Further embodiments provide a system, comprising a) any of
the aforementioned devices; and b) a LSPR detection apparatus. In
some embodiments, the system further comprises one or more of a
sample handling component, a data analysis component, or a user
interface. In some embodiments, the device is provided as a
cartridge.
[0011] Additional embodiments provide a method of measuring levels
of one or more polypeptides, comprising a) contacting the system
described herein with a sample (e.g., a sample from a subject); and
b) measuring the level of one or more polypeptides in the sample
using LSPR. In some embodiments, the detection is multiplex
detection of two or more distinct polypeptides. In some
embodiments, the polypeptides are cytokines. In some embodiments,
the sample is a biological sample (e.g., including but not limited
to, serum, blood, urine, sputum, CSF, or saliva). In some
embodiments, the level of the cytokines is indicative of the
presence of an inflammatory response (e.g., in sepsis, cancer,
lupus, or graft-versus-host disease (GVHD)), an immune response,
organ damage, or infection in the subject. In some embodiments, the
subject is undergoing chemotherapy, cell or gene based therapy,
immunomodulation, or surgery. In some embodiments, the results of
the measuring are used to determine a treatment course of action in
the subject (e.g., administration of an immune suppressant, a drug
that blocks the activity of a cytokine (e.g., etanercept and/or
tocilizumab), anti-rejection drug (e.g., tacrolimus), or a drug
comprising recombinant proteins (e.g., sargramostim and/or
filgrastim). In some embodiments, the measuring is completed in 2
hours (e.g., 1 hour, 50 minutes, 45 minutes, 40 minutes, 35
minutes, 30 minutes, 25 minutes, 20 minutes, 15 minutes, 10
minutes, 5 minutes) or less.
[0012] Yet other embodiments provide a method of measuring levels
of one or more cytokines in a biological sample from a subject,
comprising: a) contacting the system described herein with a
biological sample from a subject; and b) measuring the level of one
or more polypeptides in the sample using LSPR.
[0013] Additional embodiments are described herein.
DESCRIPTION OF THE FIGURES
[0014] FIG. 1 shows a schematic and principle of exemplary
immunoassays. (A) Schematic of the LSPRmi chip. (B) Histograms of
the particle-to-particle distance of the AuNRs on the LSPRmi chip
characterized using SEM images. (C) The principle of the LSPRmi
method.
[0015] FIG. 2 shows real-time AuNR microarray signals during
multiplex cytokine detection.
[0016] FIG. 3 shows LSPRmi intensity mapping and calibration
curves. (A) LSPRmi chip layout consisting of 60
antibody-functionalized AuNR stripes segmented by 8 microfluidic
detection channels. (B) Mapping of LSPR signal intensity shifts
over the 480 AuNR barcode sensor spots on the LSPRmi chip obtained
by the multi-analyte calibration process for the six cytokines in
a). (C) Calibration curves of TNF-.alpha., IFN-.gamma., IL-2, IL-4,
IL-6, IL-10 obtained from the LSPR barcode intensity mapping in
(B).
[0017] FIG. 4 shows multiplex cytokine detection in healthy donor
serum matrix and patient serum samples. (A) Darkfield images of
AuNR microarrays within a single microfluidic detection channel
loaded with different sample mixtures of recombinant cytokines
spiked in serum matrix. (B) Cytokine concentrations quantified for
the samples in (A). (C) Correlation between data obtained from the
LSPRMi assay and gold standard ELISA for the spiked-in serum
samples with cytokine concentrations ranging from 32-5000 pg/mL. d)
Five-day cytokine concentration variations measured by the LSPRmi
assay for serum samples extracted from two post-CPB-surgery
pediatric patients.
[0018] FIG. 5 shows (A) Scanning electron micrograph of AuNR drop
cast onto a conductive glass substrate. (B) Statistics of the
length and width of the AuNRs measured from high magnification
electron microscopy in (A). (C) Extinction spectra of AuNRs in
solution showing the resonant Rayleigh scattering wavelength at
around 626 nm.
[0019] FIG. 6 shows a schematic of the LSPRmi chip patterning
process that entails glass pre-treating, AuNR deposition, and
antibody function.
[0020] FIG. 7 shows scanning electron microscope images of AuNR
particles within a microarray pattern on a glass substrate.
[0021] FIG. 8 shows (A) Schematic of the dark-field microscope
setup for LSPRmi immunoassay. (B) Illustration of the LSPRmi assay
protocol using the prepared LSPRmi chip and dark-field imaging. (C)
Microarray images analyzed by customized Matlab program.
[0022] FIG. 9 shows A) FDTD simulation scheme on light scattering
response from one single AuNR. B) Near-field LSPR intensity profile
of a bare single AuNR excited by incident light. D) Predicted
scattering spectrum (or LSPR spectrum) variation with the thickness
of the protein coating on the AuNR.
[0023] FIG. 10 shows calculated scattering spectrum peak wavelength
(alternatively, scattering cross section normalized by the value
for a bare AuNR surface) as a function of the thickness of protein
layer covering the AuNR surface, r.
[0024] FIG. 11 shows (A) Line intensity profile of the uniformly
fabricated AuNR microarrays, which was measured using dark-field
imaging microscopy. (B) Calibration plots showing the LSPRmi signal
variation with recombinant TNF-.alpha. concentration, where each
star represents an individual measurement data point.
[0025] FIG. 12 shows cytokine levels in serum of leukemia
patients.
[0026] FIG. 13 shows a schematic of ACEO flow and its effect on
surface reaction.
[0027] FIG. 14 shows (a) Deposition of microelectrodes (b) Surface
functionalization of AuNR microarrays (c) Analyte sample loading
using PDMS flow channel (d) Real-time detection of target analytes
under ACEO vortex flow (e) Picture of an exemplary ACEO device (f)
Dark field image of AuNRs barcode coupled with electrodes.
[0028] FIG. 15 shows (a) Schematic of the dark-field microscope
setup (b) Surface reaction inside an exemplary ACEO coupled
nanobiosensor (c) Real-time dark-field image collected by
EMCCD.
[0029] FIG. 16 shows (a) Real-time binding curve of
biotin-streptavidin under different concentration (b) Calibration
curve (c) Schematic of surface function (d) Test of non-specific
binding.
[0030] FIG. 17 shows detection of cytokines using devices of
embodiments of the present disclosure.
[0031] FIG. 18 shows a workflow for an exemplary analysis system of
embodiments of the present disclosure.
DEFINITIONS
[0032] The term "assay reagents" as used herein is used in the
broadest sense and refers to any reagent useful, necessary, or
sufficient for performing the immunoassays of the present
disclosure. Examples include, but are not limited to, antibodies,
controls, buffers, calibration standards and the like.
[0033] The term "sample" in the present specification and claims is
used in its broadest sense. It is meant to include both biological
and environmental samples. A sample may include a specimen of
synthetic origin.
[0034] Biological samples may be animal, including human, fluid,
solid (e.g., stool) or tissue, as well as liquid and solid food and
feed products and ingredients such as dairy items, vegetables, meat
and meat by-products, and waste. Biological samples may be obtained
from all of the various families of domestic animals, as well as
feral or wild animals, including, but not limited to, such animals
as ungulates, bear, fish, lagamorphs, rodents, etc.
[0035] Environmental samples include environmental material such as
surface matter, soil, water and industrial samples, as well as
samples obtained from food and dairy processing instruments,
apparatus, equipment, utensils, disposable and non-disposable
items. These examples are not to be construed as limiting the
sample types applicable to the present disclosure.
[0036] As used herein, the term "in vitro" refers to an artificial
environment and to processes or reactions that occur within an
artificial environment. In vitro environments can consist of, but
are not limited to, test tubes and cell culture. The term "in vivo"
refers to the natural environment (e.g., an animal or a cell) and
to processes or reaction that occur within a natural
environment.
[0037] "Antigen binding molecule" refers to a molecule that binds a
specific antigen. Examples include, but are not limited to,
proteins, nucleic acids, aptamers, synthetic molecules, etc.
[0038] "Antigen binding protein" refers to proteins that bind to a
specific antigen. "Antigen binding proteins" include, but are not
limited to, immunoglobulins, including polyclonal, monoclonal,
chimeric, single chain, and humanized antibodies, Fab fragments,
F(ab')2 fragments, and Fab expression libraries.
[0039] "Specific binding" or "specifically binding" when used in
reference to the interaction of an antibody and an antigen means
that the interaction is dependent upon the presence of a particular
structure (e.g., the antigenic determinant or epitope) on the
antigen; in other words the antibody is recognizing and binding to
a specific structure rather than to antigens in general. For
example, if an antibody is specific for epitope "A," the presence
of a protein containing epitope A (or free, unlabelled A) in a
reaction containing labeled "A" and the antibody will reduce the
amount of labeled A bound to the antibody.
[0040] As used herein, "microfluidic" refers to, for example, a
device for transport or storage of small volumes (e.g., of liquids
such as assay reagents). In some embodiments, individual channels
or chamber of microfluidic devices comprise a volume of 10 nL to 1
.mu.L (e.g., 10, 20, 50, 100, 200, 300, 400, 500, or 750 nL),
although other sizes are contemplated.
[0041] The terms "test compound" and "candidate compound" refer to
any chemical entity, pharmaceutical, drug, and the like that is a
candidate for use to treat or prevent a disease, illness, sickness,
or disorder of bodily function. Test compounds comprise both known
and potential therapeutic compounds. A test compound can be
determined to be therapeutic by screening using the screening
methods of the present disclosure.
DETAILED DESCRIPTION
[0042] Provided herein are systems and methods for conducting
assays. In particular, provided herein are systems and methods for
performing high throughput immunoassays.
[0043] LSPR is a plasmonic phenomenon that arises around nanoscale
structures or nanoparticles of noble metal (e.g., ruthenium,
cesium, palladium, silver, gold, iridium, platinum, gold, and
combinations thereof) when light is illuminated onto a nanoscale
featured sensing surface. When the incident light frequency matches
the natural frequency of electron oscillation of the conductive
metal nanoparticles, the interactions between the incident light
and the nanostructured surface maximize the optical extinction of
the particles with electrons highly enhanced near the particles'
surfaces and trigger the LSPR. The resonance wavelength and
intensity can be readily modified by the temporal or irreversible
absorption of analyte as small as protein, nucleic acids and
cytokines. As such, it has been proven to be an effective
label-free detection method for antibody-antigen binding that
permits high-sensitivity and real-time analysis. In addition, the
elimination of secondary antibody labeling can significantly
suppress cross-reactivity. Since the sensor elements used in LSPR
technique can be as small as a few tens of nanometers in diameter,
it provides a significant advantage in constructing a large number
of sensor arrays integrated on a single chip, which enables a
high-throughput, high multiplicity sensing platform with
drastically reduced sample volume and total assay time.
[0044] Relying upon the measurement of labeling signals,
conventional sandwich immunoassays often employed in ELISA provide
the end-point analyte readout only after the completion of all the
multiple reagent processes. Without precisely knowing the end-point
timing, users of these assay techniques need to follow a protocol
requiring two hours for the analyte incubation. Additional labeling
and washing steps together with the time-consuming incubation
process result in a total assay time of typically eight hours or
longer. In contrast, both the label-free nature and real-time
analyte binding monitoring capability demonstrated in the present
disclosure provide the significant advantages. These features
allowed for elimination of a multi-step assay processes and reduced
the analyte incubation time to, for example, less than 30 min. From
the real-time sensor signal saturation point, it was possible to
determine the endpoint of the analyte-binding assay where the
washing process could be initiated to remove the non-specifically
adsorbed analyte molecules. This allowed the entire LSPRmi
immunoassay involving the parallel sample loading, multi-analyte
(IL-2, IL-4, IL-6, IL-10, TNF-.alpha., and IFN-.gamma.) binding,
incubation, and washing across 480 on-chip biosensing spots to be
completed within such a short period of time (e.g., 40 min). This
assay time is more than ten times shorter than that of the
conventional ELISA.
[0045] Despite the impressive rapidness, sample efficiency, and
throughput, multi-arrayed LSPR biochip schemes in serum cytokine
screening have faced a major issue in the past--the poor limit of
detection (LOD). For instance, major efforts have been made to
identify serum cytokine profiles useful for either the early
detection of sepsis or to assess illness severity (Wong, H. R., et
al. Critical Care 16, article R174 (2011); Bozza, F. A., et al.
Critical Care 11, article R49 (2007)). Serum cytokine
concentrations for patients with sepsis can vary widely
necessitating both a wide dynamic range and low LOD to provide
meaningful information with clinical utility. Bozza et al. report
the ability to predict 28-day mortality in patients with sepsis by
measuring serum IL-8 within the first 72 hours of admission (Bozza
et al., supra). A serum IL-8 cutoff able to meaningfully
discriminate between survivors and non-survivors with reasonable
accuracy would be an assay capable of measuring serum cytokines
concentrations<100 pg/mL. This cutoff value is already
comparable to or far below the LOD's obtained by previous studies
(Endo, T., et al. Anal. Chem. 78, 6465-6475 (2006); Acimovic, S.
S., et al. Nano Lett. 14, 2636-2641 (2014)). To achieve such high
sensitivity, embodiments of the detection method described herein
employ dark-field imaging that scans the scattering light intensity
across the LSPR biosensing spots (FIG. 8).
[0046] Nonspecific antibody cross-reactions pose significant
challenges in retaining high accuracy for multiplex sandwich
immunoassays. This issue becomes serious when the assay involves a
large number of antibody pairs in a complex biological medium, such
as human serum. It prevents the scaling up of multiplexing because
non-specific bindings among antibodies, target analytes and other
biological components in the solution (e.g., free plasma proteins,
lipids, electrolytes, etc.) exponentially increase. The LSPR assay
described herein overcomes these problems. It provides the
additional advantage of the label-free nature of the LSPR
biosensing scheme that eliminates the secondary antibody labeling.
The direct measurement of the sensor response upon analyte binding
substantially quenched the non-specific adsorption among all the
biological species. As a result, the assay displayed a negligible
cross-reactivity at cytokine concentrations of 500 pg/mL in human
serum. The LSPRmi assay showed a significantly better correlation
with singleplex ELISA than the commercial multiplex bead array
assays (MBAA) for human serum analysis (Bozza, F. A., et al.
Critical Care 11, article R49 (2007)).
[0047] Obtaining the serum samples from CPB-surgery pediatric
patients, it was possible to exactly define the source of the
inflammatory response of the hosts--the surgery and predict the
anticipated assay outcomes. The LSPRmi assay successfully measured
elevated cytokine levels, most notable for IL-6 and IL-10, in both
neonates at 24 h after surgery for congenital heart disease using
cardiopulmonary bypass. A very similar pattern to those previously
reported where elevations in patient's serum cytokine levels most
commonly return to pre-surgical levels within 48 hours of surgery
was observed. Such information is valuable because very high and/or
prolonged expression of both pro-inflammatory (e.g. IL-6) and
anti-inflammatory (e.g. IL-10) cytokines are associated with the
acute immune dysfunction following cardiopulmonary bypass and
predict worse outcomes (Ashraf, et al., Eur. J. Pediatr. Surg. 12,
862-868 (1997); Seghaye, M. C., et al. J. Thorac. Cardiovasc. Surg.
111, 545-553 (1996)). The LSPR assay of embodiments of the present
disclosure was capable of detecting variable degrees of responses
in the two subjects after CPB. There are multiple mechanisms
contributing to this variable cytokine expression (e.g., patient
age, cardiac lesion, length of surgery and CPB, use of
intraoperative steroids, etc.), however, no methodology exists to
safely, routinely and repetitively measure serum cytokines in near
real-time to enable clinicians to monitor a host inflammatory
response and thereby alter therapeutic strategies as needed. The
experiments described herein demonstrate the capability to
routinely monitor multiple serum cytokines in patients using the
LSPR assay. The rapid turn-around time (e.g., .about.40 min), high
sensitivity (e.g., down to .about.6.46 pg/mL-20.56 pg/mL), extreme
sample sparing ability (e.g., .about.1 .mu.L sample for six
cytokines with 10 technical replicate measurements) and negligible
cross-reactivity enable routine monitoring of serum cytokines with
statistically high accuracy. Such characteristics provide use in
monitoring a substantial number of different disease
states--particularly in infants and neonates where sample volume
has been a mitigating factor. Such key characteristics do not exist
with current methods as the assay turn-around time and blood volume
required make them impractical to use, especially in small
infants.
[0048] Accordingly, provided herein is a multi-arrayed LSPR
microarray (LSPRmi) device for parallel (e.g., massively parallel)
high-throughput detection of multiple cytokine biomarkers in serum.
Exemplary devices, systems, and methods are described herein.
I. Devices and Systems
[0049] Embodiments of the present disclosure provide devices and
systems for use in LSPR immunoassays. In some embodiments, devices
comprise a LSPR component and a microfluidic component. Exemplary
devices are shown in FIG. 1. The present disclosure further
provides systems for performing LSPR using the described
devices.
[0050] A. LSPR surface s
[0051] In some embodiments, devices comprise a LSPR component
comprising a solid surface functionalized with a metal. In some
embodiments, the solid surface is glass. Glass substrates offer
good optical properties for imaging and surface modification
capacity for surface function. Alternative surfaces include, but
are not limited to, transparent plastics, such as poly(methyl
methacrylate) (PMMA), known as acrylic glass, a transparent
thermoplastic that can be modified with surface moieties for
antibody function; polycarbonate; cyclic olefin copolymer (COC);
cyclo olefin polymer (COP); polystyrene; polypropylene; and
polyethylene terephthalate glycol-modified (PEGT).
[0052] In some embodiments, substrates are coated with metals that
allow for the resonant oscillation of conduction electrons at the
interface between a negative and positive permittivity material
stimulated by incident light. This can occur as deposition of bulk
material allowing detection of surface plasmon resonance (SPR), or
as described herein as discrete plasmonic nanoparticles allowing
detection of localized plasmon resonance (LSPR). Metals that
support surface plasmons include, but are not limited to, silver,
gold, copper, titanium or chromium. In some embodiments metals are
provided as localized nanotubes or other geometric configurations.
In some exemplary embodiments (See e.g., FIG. 1), metal nanorods or
other metal configurations are arranged in stripes or other regular
patterns on the surface (See e.g., Williams S E, Davies P R, Bowen
J L, and Allender C J. Controlling the nanoscale patterning of
AuNPs on silicon surfaces. Nanomaterials 2013; 3: 192-203; herein
incorporated by reference in its entirety). In addition to
nanorods, other suitable particle configurations include, but are
not limited to, nanospheres, nanostars, nanodiamonds, nanopyramids,
nanobipyramids, or nanorings and metal core-shell structures (e.g.,
gold/silver core-shell structures). Silver exhibits good optical
properties but may be toxic in a biological environment due to the
release of silver ions. The chemically inert gold nanoshell
provides biocompatibility while maintaining the extraordinary
optical properties of the silver core. In some embodiments, other
noble metals are utilized (e.g., ruthenium, rhodium, palladium,
osmium, iridium, platinum).
[0053] In some embodiments, metallic surfaces or areas are
functionalized with antibodies (e.g., monoclonal or polyclonal
antibodies) that bind to a specific peptide or polypeptide (e.g.,
antigen). The present disclosure is not limited to particular
antibodies. In some embodiments, antibodies are specific for a
cytokine or chemokine (e.g., one or more of interleukin-2 (IL-2);
interleukin-4 (IL-4); interleukin-6 (IL-6); interleukin-10 (IL-10);
interleukin-(IL-8); interleukin-12 (IL-12) interferon-gamma
(IFN-.gamma.); or tumor-necrosis-factor alpha (TNF-.alpha.)).
Additional cytokines include, but are not limited to, acylation
stimulating protein, adipokine, albinterferon, CCL1, CCL11, CCL12,
CCL13, CCL14, CCL15, CCL16, CCL17, CCL18, CCL19, CCL2, CCL20,
CCL21, CCL22, CCL23, CCL24, CCL25, CCL26, CCL27, CCL28, CCL3, CCLS,
CCL6, CCL7, CCL8, CCL9, colony-stimulating factor, CX3CL1, CX3CR1,
CXCL1, CXCL10, CXCL11, CXCL13, CXCL14, CXCL15, CXCL16, CXCL17,
CXCL2, CXCL3, CXCL5, CXCL6, CXCL7, CXCL9, erythropoietin, Gc-MAF,
granulocyte colony-stimulating factor, granulocyte macrophage
colony-stimulating factor, hepatocyte growth factor, IL-17, IL1A,
IL1B, inflammasome, interferome, interferon, interferon beta 1a,
interferon beta 1b, interferon gamma, interferon type I, interferon
type II, interferon type III, interferon-stimulated gene,
interleukin 1 family, interleukin 1 receptor antagonist,
interleukin 12, interleukin 12 subunit beta, interleukin 13,
interleukin 16, interleukin 2, interleukin 23, interleukin 23
subunit alpha, interleukin 34, interleukin 35, interleukin 7,
interleukin 8, interleukin-36, leukemia inhibitory factor,
leukocyte-promoting factor, lymphokine, lymphotoxin, lymphotoxin
alpha, lymphotoxin beta, macrophage colony-stimulating factor,
macrophage inflammatory protein, macrophage-activating factor,
monokine, myokine, myonectin, nicotinamide
phosphoribosyltransferase, oncostatin M, oprelvekin, platelet
factor 4, proinflammatory cytokine, promegapoietin, RANKL, stromal
cell-derived factor 1, talimogene laherparepvec, XCL1, XCL2, and
XCR1.
[0054] Additional suitable analytes include, but are not limited
to, Interleukin-1, Interleukin-1 receptor anatagonist,
Interleukin-2, Interleukin-2 receptor antagonist, Interleukin-4,
Interleukin-6, Interleukin-8, Interleukin-10, Interleukin-12,
Interleukin-17, Interluekin-23, Tumor necrosis factor alpha,
Interferon gamma, Granzyme B, HSP1AB, MMP-8, MIP-1a, antibodies
(e.g., monoclonal or polyclonal), nucleic acids (e.g., DNA, mRNA,
miRNA, lncRNA), nucleic acid probes, Chemokine (c-c motif) ligand 3
(Macrophage inflammatory protein 1-alpha), Matrix
metalloproteinase-8, and Heat shock protein 70 A1B.
[0055] In some embodiments, linkers are utilized to attach
antibodies to surfaces (e.g., using carbodiimide (e.g., EDC
(1-Ethyl-3-(3-dimethylaminopropyl)-carbodiimide))/NHS chemistry).
In some embodiments, linker is a bifunctional thiol linker. The
present disclosure is not limited to the length of the linker. In
some embodiments, the linker comprises a 1 to 10 carbon atom chain
(e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 carbons).
[0056] In some embodiments, multiplex detection is enabled by
providing distinct antibodies in addressable locations on the array
surface (e.g., by physically addressed barcodes). For example, in
some embodiments, individual rows or channels each contain one
specific antibody (e.g., at shown in FIG. 1A). This provides a
barcode array that allows for multiplexing by assigning distinct
antibodies to specific locations (e.g., spots or dots) on the
array.
[0057] Surfaces (e.g., glass or thermoplastic surfaces) are
generated using any suitable method. In some embodiments, the
method described in Example 1 is utilized. For example, in some
embodiments, the substrate is treated with oxygen plasma, UV/ozone,
and metal nanorods or other metal component are patterned using a
microfluidic patterning technique through electrostatic
interactions between the metal and the glass surface. In some
embodiments, the constructed metal patterns are functionalized
(e.g., with thiolated alkane 10-Carboxy-1-decanethiol
(HS--(CH2)10-COOH)) through ligand exchange and subsequently
activated for antibody attachment using standard EDC/NHS coupling
chemistry.
[0058] Other suitable protocols for functionalizing surfaces
include, but are not limited to, APTES functioned glass or
thermoplastic covalently interact with gold nanorods (Kathryn Mayer
et. al., ACS Nano, 2, 687-692, 2008; herein incorporated by
reference in its entirety); Silane functioned surfaces covalently
interact with citrate stabilized god nanoparticles (Maniraj
Bhagawati et. al. Anal. Chem., 85, 9564-9571, 2013; herein
incorporated by reference in its entirety); and random deposited
CTAB gold nanorods with aptamers for detection (Christina Rosman
et. al. Nano Lett. 13, 3243-3247, 2013; herein incorporated by
reference in its entirety).
[0059] In some embodiments, surfaces are silanized (See e.g.,
Haddada M B, et al. Gold Bull 2013; 46: 335-341; Cant N E, et al.
Thin Solid Films 2003; 426: 31-39). In some embodiments, silanes
are aminated, thiolated, or disulfide modified. In some
embodiments, silanization is performed via chemical vapor
deposition (e.g., plasma-enhanced CVD or low pressure CVD or via
protic solvent).
[0060] In some embodiments, surfaces comprise AC electroosmosis
(ACEO) components. ACEO is a nonlinear electrokinetic phenomenon of
induced-charge electroosmotic flow around electrodes when applying
an alternating voltage. The polarization of the electrode surface
induces a diffuse ion layer called electrical double layer (EDL)
(See, e.g., FIG. 13). At a given frequency, the electrical
potential at the outer edge of the EDL causes a tangential
electrical field, which exerts a non-zero time-averaged outward
direction (as shown by the green arrows on the electrode surface)
force on the induced charge (EDL). This movement of EDL leads to a
circumferential fluid motion inside the microfluidic channel and
can work as a micropump to facilitate the transportation of
analytes down to the sensing surface. Therefore, the depletion zone
formed under a diffusion-limit regime can be significantly reduced
by ACEO. The surface reaction rate is thus greatly enhanced due to
this continuous fluid motion, especially for ultra-low
concentration biomarker detection. Accordingly, in some
embodiments, devices further comprise a plurality of microelctrodes
configured for ACEO in communication with the arrays of metal
particles. In some embodiments, each array (e.g., nanotube) is
attached to a plurality of electrodes.
[0061] B. Microfluidic Component
[0062] In some embodiments, devices of embodiments of the present
disclosure comprise a microfluidic component. The microfluidic
component is in fluid communication with the LSPR component and
serves to transport assay components (e.g., patient samples and
assay reagents) to the LSPR component. In some embodiments, the
microfluidic component comprises a plurality (e.g., 2, 4, 6, 8, 10,
12 or more depending on the size of the device) of microfluidic
channels. In some embodiments, channels have outlet and inlet
components and/or reservoir components for supplying fluids to
regions the device. In some embodiments, microfluidic channels are
placed perpendicular to LSPR patterned components.
[0063] The microfluidic component is constructed of any suitable
material. In some embodiments, layers are made by supplying a
negative "master" and casting a castable material over the master.
Castable materials include, but are not limited to, polymers,
including epoxy resins, curable polyurethane elastomers, polymer
solutions (e.g., solutions of acrylate polymers in methylene
chloride or other solvents), curable polyorganosiloxanes, and
polyorganosiloxanes which predominately bear methyl groups (e.g.,
polydimethylsiloxanes ("PDMS")). Curable PDMS polymers are well
known and available from many sources. Both addition curable and
condensation-curable systems are available, as also are
peroxide-cured systems. All these PDMS polymers have a small
proportion of reactive groups which react to form crosslinks and/or
cause chain extension during cure. Both one part (RTV-1) and two
part (RTV-2) systems are available.
[0064] In some embodiments, transparent devices are desirable. Such
devices may be made of glass or transparent polymers. PDMS polymers
are well suited for transparent devices. A benefit of employing a
polymer that is slightly elastomeric is the case of removal from
the mold and the potential for providing undercut channels, which
is generally not possible with hard, rigid materials. Methods of
fabrication of microfluidic devices by casting of silicone polymers
are well known. See, e.g. D. C. Duffy et al., "Rapid Prototyping of
Microfluidic Systems in Poly(dimethylsiloxane)," Analytical
Chemistry 70, 4974-4984 (1998). See also, J. R. Anderson et al.,
Analytical Chemistry 72, 3158-64 (2000); and M. A. Unger et al.,
Science 288, 113-16 (2000), each of which is herein incorporated by
reference in its entirety. In some embodiments, fluids are supplied
to the device by any suitable method.
[0065] Fluids may, for example, be supplied from syringes, from
microtubing attached to or bonded to the inlet channels, etc.
[0066] Fluid flow may be established by any suitable method. For
example, external micropumps suitable for pumping small quantities
of liquids are available. Micropumps may also be provided in the
device itself, driven by thermal gradients, magnetic and/or
electric fields, applied pressure, etc. Integration of
passively-driven pumping systems and microfluidic channels is
described by B. H. Weigl et al., Proceedings of MicroTAS 2000,
Enshede, Netherlands, pp. 299-302 (2000).
[0067] In some embodiments, fluid flow is established by a gravity
flow pump, by capillary action, or by combinations of these
methods. A simple gravity flow pump consists of a fluid reservoir
either external or internal to the device, which contains fluid at
a higher level (with respect to gravity) than the respective device
outlet. Such gravity pumps have the deficiency that the hydrostatic
head, and hence the flow rate, varies as the height of liquid in
the reservoir drops. For many devices, a relatively constant and
non-pulsing flow is desired.
[0068] To obtain constant flow, a gravity-driven pump as disclosed
in published PCT application No. WO 03/008102 A1 (Jan. 18, 2002),
herein incorporated by reference, may be used. In such devices, a
horizontal reservoir is used in which the fluid moves horizontally,
being prevented from collapsing vertically in the reservoir by
surface tension and capillary forces between the liquid and
reservoir walls. Since the height of liquid remains constant, there
is no variation in the hydrostatic head.
[0069] Flow may also be induced by capillary action. In such a
case, fluid in the respective channel or reservoir will exhibit
greater capillary forces with respect to its channel or reservoir
walls as compared to the capillary forces in the associated device.
This difference in capillary force may be brought about by several
methods. For example, the walls of the outlet and inlet channels or
reservoirs may have differing hydrophobicity or hydrophilicity.
Alternatively, the cross-sectional area of the outlet channel or
reservoir is made smaller, thus exhibiting greater capillary
force.
[0070] In some embodiments, construction of fluidic devices is by
soft lithography techniques as described for example by Duffy et al
(Analytical Chem 70 4974-4984 1998; See also Anderson et al,
Analytical Chem 72 158-64 2000 and Unger et al., Science 288 113-16
2000). Addition-curable RTV-2 silicone elastomers such as
SYLGARD.TM. 184 Dow Corning Co can be used for this purpose. The
dimensions of the channels are readily determined by volume and
flow rate properties etc.
[0071] The substrate may be of one layer or plurality of layers.
The individual layers may be prepared by numerous techniques
including laser ablation, plasma etching, wet chemical methods,
injection molding, press molding, etc. Casting from curable
silicone is most preferred, particularly when optical properties
are important. Generation of the negative mold can be made by
numerous methods all of which are well known to those skilled in
the art. The silicone is then poured onto the mold degassed if
necessary or desired and allowed to cure. Adherence of multiple
layers to each other may be accomplished by conventional
techniques.
[0072] A method of manufacture of some devices employs preparing a
master through use of negative photoresist SU-8 50 photoresist from
Micro Chem Corp Newton Mass.
[0073] In some embodiments, devices are injection molded. For
example, in some embodiments, devices comprise injection molded
thermoplastic fluidic layers bonded to the detection substrate.
[0074] C. Systems
[0075] In some embodiments, LSPR signals are detected by any
suitable detector. An exemplary detector is shown in FIG. 8. In
some embodiments, devices are placed on a movable platform or stage
for scanning multiple locations on the device. In some embodiments,
detectors comprise a light source, one or more objectives, filters,
dark field condensers, and imaging components (e.g., CCD
detectors).
[0076] In some embodiments, devices are configured for multiplex
detection of multiple polypeptides. For example, as described
above, a bar code component is provided by providing specific
distinct antibodies in addressable locations on the LSPR
surface.
[0077] In some embodiments, following imaging, a software component
is utilized to analyze signal from the array. For example, in some
embodiments, software is configured to process an image, determine
which locations have target antigen bound, and provide a report. In
some embodiments, binding data is quantitative. For example, in
some embodiments, a calibration curve is obtained prior to
performing the assay (See e.g., FIG. 3) and/or in parallel on each
chip (e.g., as internal positive and negative controls).
[0078] In some embodiments, systems are automated. For example, in
some embodiments, systems (See e.g., FIG. 18) comprise one or more
of a packaged, ready to use cartridge (LSPR chip), integrated
sample processing component (e.g., robotic sample handling system),
automated optical detection platform (e.g., those described
herein), and computer-based sample analysis and display component
(e.g., display screen, tablet, smart phone, etc.). In some
embodiments, a computer-based analysis program is used to translate
the raw data generated by the detection assay (e.g., the presence,
absence, or level of an antigen) into data of predictive value for
a clinician (e.g., choice of therapy). The clinician can access the
predictive data using any suitable means. Thus, in some preferred
embodiments, the present disclosure provides the further benefit
that the clinician, who is not likely to be trained in immunology
or molecular biology, need not understand the raw data. The data is
presented directly to the clinician in its most useful form. The
clinician is then able to immediately utilize the information in
order to optimize the care of the subject.
[0079] The present disclosure contemplates any method capable of
receiving, processing, and transmitting the information to and from
laboratories conducting the assays, information provides, medical
personal, and subjects. For example, in some embodiments of the
present disclosure, a sample (e.g., a blood, urine or serum sample)
is obtained from a subject and submitted to a profiling service
(e.g., clinical lab at a medical facility, profiling business,
etc.), located in any part of the world (e.g., in a country
different than the country where the subject resides or where the
information is ultimately used) to generate raw data. Where the
sample comprises a tissue or other biological sample, the subject
may visit a medical center to have the sample obtained and sent to
the profiling center, or subjects may collect the sample themselves
(e.g., a urine sample) and directly send it to a profiling center.
Where the sample comprises previously determined biological
information, the information may be directly sent to the profiling
service by the subject (e.g., an information card containing the
information may be scanned by a computer and the data transmitted
to a computer of the profiling center using an electronic
communication systems). Once received by the profiling service, the
sample is processed and a profile is produced (e.g., levels of
antigens), specific for the diagnostic or prognostic information
desired for the subject.
[0080] The profile data is then prepared in a format suitable for
interpretation by a treating clinician. For example, rather than
providing raw data, the prepared format may represent a diagnosis
or risk assessment (e.g., likelihood of organ rejection or immune
response) for the subject, along with recommendations for
particular treatment options. The data may be displayed to the
clinician by any suitable method. For example, in some embodiments,
the profiling service generates a report that can be printed for
the clinician (e.g., at the point of care) or displayed to the
clinician on a computer monitor.
[0081] In some embodiments, the information is first analyzed at
the point of care or at a regional facility. The raw data is then
sent to a central processing facility for further analysis and/or
to convert the raw data to information useful for a clinician or
patient. The central processing facility provides the advantage of
privacy (all data is stored in a central facility with uniform
security protocols), speed, and uniformity of data analysis. The
central processing facility can then control the fate of the data
following treatment of the subject. For example, using an
electronic communication system, the central facility can provide
data to the clinician, the subject, or researchers.
[0082] In some embodiments, the subject is able to directly access
the data using the electronic communication system. The subject may
chose further intervention or counseling based on the results. In
some embodiments, the data is used for research use. For example,
the data may be used to further optimize the inclusion or
elimination of markers as useful indicators of a particular
condition or stage of disease.
[0083] In some embodiments, systems comprising devices, detectors,
software, and computer components (e.g., computer processor and
display screen, smart phone, etc.) are provided. In some
embodiments, the detection and analysis components are provided as
a platform and the devices are provided as cartridges or plates
(e.g., disposable or re-usable devices). For example, in some
embodiments, the portion of the system that contacts patient sample
is provided as a disposable cartridge or strip and the detection
and analysis platform is a stand-alone reusable component that can
accept and analyze cartridges specific for one or more target
antigens.
[0084] In some embodiments, the entire system is provided as a hand
held device (e.g., suitable for bedside use). In some embodiments,
handheld devices comprise a disposable strip or cartridge for
patient sample. In some embodiments, handheld devices are target
specific (e.g., dedicated to a specific antigen) or target
independent (e.g., suitable for accepting different cartridges or
strips specific for different antigens).
II. Methods
[0085] Embodiments of the present disclosure provide the use of the
devices and systems described herein for detection of antigens
(e.g., in patient samples). In some embodiments, the entire assay
is completed in one hour (e.g., 50 minutes, 40, minutes, 30
minutes, 20 minutes, 10 minutes, 5 minutes, 4 minutes, 3 minutes, 2
minutes, 1 minute, etc.) or less. This provides a distinct
advantage over traditional ELISA assays, which often require
multiple hours to complete. Such rapid assays are especially useful
in patient care settings where decisions about treatment and
interventions need to be made rapidly.
[0086] The present disclosure is not limited to particular patient
samples. Examples include, but are not limited to, serum, whole
blood, urine, sputum, semen, cerebral spinal fluid (CSF), or
saliva. In some embodiments, samples are processed or purified
prior to use. In some embodiments, samples are utilized without
processing (e.g., from a finger prick or urine sample). In some
embodiments, sample volumes are 1 .mu.L or less (e.g., 900 nL, 800
nL, 700 nL, 600 nL, 500 nL, 400 nL, 300 nL, 200 nL, or 100 nL or
less).
[0087] In some embodiments, the present disclosure provides methods
for detecting one or more cytokines (e.g., those disclosed herein),
chemokines, or other makers of inflammation, immune response, organ
damage, or infection. In some embodiments, the presence and/or
levels of the cytokines in the sample is used to determine the
presence of an inflammatory response, an immune response, organ
damage, or infection in the subject. The present disclosure is not
limited to particular inflammatory or immune responses. Examples
include, but are not limited to, surgical trauma, sepsis, cancer,
lupus, graft versus host disease (GVHD), autoimmune hepatitis,
multiple sclerosis, systemic lupus erythematosus, myasthenia
gravis, Type I diabetes, rheumatoid arthritis, psoriasis,
Hashimoto's thyroiditis, Grave's disease, ankylosing spondylitis,
Sjogrens disease, CREST syndrome, scleroderma, Crohn's disease,
acute respiratory distress syndrome (ARDS), patients who have under
gone solid organ transplants and are receiving immunosuppression
therapy, ulcerative Colitis, polyarteritis nodosa, Whipple's
disease, primary sclerosing cholangitis, etc.
[0088] In some embodiments, the subject is undergoing chemotherapy
or has undergone surgery. In some embodiments, the levels of the
cytokines are used to determine a treatment course of action. For
example, in a patient found to be undergoing GVHD, sepsis, or an
inflammatory response, an immune suppressant drug (e.g., steroid)
or immune modulating drug (e.g., filgrastim) is administered.
[0089] In some embodiments, patients undergoing chemotherapy (e.g.,
chimeric antigen receptor T-cell therapy (CAR T-cell)), which
results in release of cytokines, are monitored to measure cytokine
levels. The levels of the cytokines are monitored to determine when
patients have cytokine levels that are clinically too high (e.g.,
result in shock and/or hemodynamic instability). Such patients are
administered anti-cytokine therapy (e.g., etanercept and/or
tocilizumab). In some embodiments, cytokine levels are monitored to
determine when levels have decreased sufficiently to reduce or halt
therapy. In some embodiments, patients that do not have elevated
levels of cytokines are not administered anti-cytokine therapy.
[0090] In some embodiments, patients are monitored (e.g., using
bedside devices) multiple times during the course of treatment,
recovery from surgery, or after treatment with an immune
suppressing drug to determine if changes in treatment are needed.
For example, in some embodiments, patient found to need immune
suppressing therapy are monitored to determine when the
inflammation or GVHD has subsided in order to determine that a
decrease in dosage or discontinuation of treatment is
advisable.
EXPERIMENTAL
Example 1
Methods
[0091] LSPRmi chip fabrication: Positively charged AuNRs (CTAB
coating) used in this study were purchased from Nanoseedz. The
AuNRs were patterned on an oxygen plasma treated glass substrate
using a microfluidic patterning technique through electrostatic
interactions between the AuNRs and the glass surface. The
constructed AuNR barcode patterns were functioned with thiolated
alkane 10-Carboxy-1-decanethiol (HS--(CH2)10-COOH) through ligand
exchange and subsequently activated using standard EDC/NHS coupling
chemistry. The probe cytokine antibodies were then loaded into
individual patterning channel forming a barcode array consisting of
six parallel stripes each functioned with distinct antibodies to
afford multiplexed detection of 6 different cytokines at one
time.
[0092] LSPRmi assay protocol: The prepared LSPRmi assay chip was
mounted on the motorized stage (ProScanIII, Prior Scientific,
Rockland, Mass.) that allowed for 3D positioning and automated
image scanning. The back of the glass substrate of the chip was
attached with a dark-field condenser (NA=1.45, Nikon) via the lens
oil. 250 nL sample was injected from the inlet, flown through the
sample channel, and collected from the outlet. The light scattered
from the barcodes was collected by the 10.times. objective lens
beneath the assay chip, filtered by a band pass filter (610-680
nm), imaged by an electron-multiplying CCD (EMCCD, Photometrics,
Tucson, Ariz.) camera and recorded using the NIS-Element BR
analysis software. The obtained images were then analyzed by a
customized Matlab program. Before each measurement, .about.10 mins
was elapsed to establish temperature stabilization of EMCCD to
minimize the background signal drift.
[0093] LSPRmi assay human serum matrix multiplex performance
characterization. To characterize both the multiplex capability and
the assay's performance three separate mixtures of cytokines was
used. One mixture contained a single cytokine species
(TNF-.alpha.), one containing three analytes (IL-4, IFN-.gamma.,
and TNF-.alpha.), and finally one containing all six cytokines
(IL-2, IL-4, IL-6, IL-10, IFN-.gamma., and TNF-.alpha.).
Recombinant cytokines (Life Technologies, Frederick, Md.) were
spiked into a commercially available heat-inactivated, charcoal
absorbed human serum matrix to remove trace levels of cytokines
(EMD Millipore, St. Charles, Mo.).
[0094] LSPRmi assay performance comparison to `gold standard`
ELISA. All six cytokines (IL-2, IL-4, IL-6, IL-10, IFN-.gamma.,
TNF-.alpha.) were spiked into healthy donor human serum obtained
via venipuncture following informed written consent. The study was
approved by the University of Michigan Institutional Review Board.
Serum was obtained via venipuncture into vacutainer tubes
containing clot activator (BD Diagnostics, Franklin Lake, N.J.).
Tubes were processed according to the manufacturer's instructions.
Serum samples doped with all six cytokines were diluted further
with healthy donor serum to obtain samples across the entire
dynamic range of the LSPRmi assay (32 pg/mL-5,000 pg/mL). Serum
cytokine concentrations were quantified using the LSPRmi assay and
compared to commercially available ELISA kits (IL-6, IL-10,
IFN-.gamma., TNF-.alpha., BioSource Europe S.A., Nivelles, Belgium;
IL-2, IL-4, Thermo-Fisher Scientific, Rockford, Ill.).
[0095] LSPRmi assay for Serum cytokine quantification of pediatric
patients following open-heart surgery with cardiopulmonary bypass.
All studies described here were approved by the University of
Michigan Institutional Review Board and conducted following
informed parental consent. Briefly, two patients enrolled in an
ongoing clinical trial for serum cytokine quantification were
selected. Serum samples were collected prior to surgery, and then
on post-operative days one, two, three, and four (Pre, D1, D2, D3,
and D4 respectively), using SST microtainer (BD Diagnostics)
according to the manufacturer's instructions. Serum cytokines
(IL-2, IL-4, IL-6, IL-10, IFN-.gamma., TNF-.alpha.) were quantified
using the LSPRmi immunoassay as described above.
[0096] FDTD simulations: The optical simulations to calculate the
scattering efficiency on a single AuNR were performed using
commercial multi-physics simulation software, COMSOL. In the
simulation, the dimensions of the AuNR were set according to the
results from the material characterization (40 nm in diameter,
aspect ratio: 2). The frequency-dependent complex permittivity of
gold was derived from Lorenze-Drude model. The far-field domain was
defined as a spherical shell surrounding the AuNR with a radius
identical with half the wavelength of incident light. The boundary
condition was set to be a perfectly matched layer. The wave vector
and electric field polarization of the incident light wave were set
to be perpendicular and parallel to the orientation of the An. The
mesh size was set to be 1 nm on the AuNR surface and no larger than
1/10 of the studied wavelength elsewhere. The spatial distribution
of the electromagnetic field on the far-field plane was measured at
varying frequencies with and without the presence of the AuNR to
determine the intensity of scattering wave from the AuNR. FDTD
simulations were performed by modeling the AuNR with dielectric
layers mimicking the antibody/analyte binding. The calculated
scattering spectrum for the bare AuNR and coated AuNR can be found
in FIG. 9.
[0097] Characterization of gold nanorods. Gold nanorods (AuNRs)
used in this study (FIG. 5A) were purchased from NanoSeedz in
aqueous etrimonium bromide (CTAB, 0.1 M) buffer. These nanorods
were originally synthesized using the standard seed-mediated growth
method. This yielded single crystalline nanoparticles with an
average length of 80.+-.5 nm and an average width of 40.+-.3 nm.
(FIG. 5B) The CTAB coating on the AuNRs resulted in a positively
charged surface with a zeta potential of 42.+-.5 mV (Zetasizer Nano
ZS90, Malvern). The extinction spectrum of the AuNRs in solution
was obtained using a customized spectrophotometer. (Oh, B. et al.
ACS Nano 8, 2667-2676 (2014)). The resonance peak wavelength of the
AuNR lays around 626 nm, in consistent with the simulation results
as shown below.
[0098] Gold nanorod microarray fabrication. Prior to the AuNR
microarray fabrication, a microfluidic flow-patterning mask layer
made of PDMS was constructed using soft lithography. The mask layer
contains multiple sets of parallel microfluidic channels for
patterning the AuNR microarrays. Specifically, a mold for the PDMS
flow-patterning mask layer was patterned within a silicon substrate
using deep reactive-ion etching (DRIE) (Deep Silicon Etcher,
Surface Technology Systems, Allenton, Pa.). The mold surface was
silanized with
(tridecafluoro-1,1,2,2,-tetrahydrooctyl)-1-trichlorosilane vapor
(United Chemical Technologies) for 1 hour in vacuum to facilitate
subsequent PDMS release. PDMS prepolymer (Sylgard-184, Dow
Corning), prepared by thoroughly mixing a curing agent with a base
monomer (wt:wt=1:10) was poured onto the silicon mold and cured it
in an oven at 110.degree. C. for 4 hrs. The cured PDMS mask layer
was then peeled off from the mold to form a microfluidic
flow-patterning layer. The layer was cut into multiple pieces, each
hole-punched to create inlets and outlets for its channels in
further use.
[0099] Subsequently, AuNR stock solution (0.2 nM) was centrifuged
three times at 5700 rpm for 10 min, and the pellet was resuspended
the pellet in deionized (D.I.) water to remove excessive CTAB in
the solution. The AuNR solution was further diluted 8 times before
the microarray fabrication. Glass slides (type) were first treated
with Piranha solution (H.sub.2SO.sub.4:H.sub.2O.sub.2=3:1) for 10
min, rinsed thoroughly with D.I. water and kept in an ultrasonic
bath with ethanol for 30 min. The surfaces of the glass substrates
were treated under 02 plasma for 2 min at 18 W (COVANCE 1-MP,
Femto). This created a negatively charged glass surface owing to
the dissociated hydroxyl groups existing on the glass, which
enabled the glass substrate to attract the CTAB stabilized
positively charged AuNRs onto its surface. Immediately after the
surface treatment, one of the microfluidic flow-patterning PDMS
mask layer pieces prepared above was bonded onto each glass
substrate. Two .mu.L of AuNR solution was loaded into each channel
at a flow rate of 1 .mu.L/min and incubated overnight, which was
followed by sealing of the inlets and outlets with a cover glass to
prevent evaporation and avoid dry-out of the AuNR solution.
[0100] After the incubation, all the channels were washed with 100%
ethanol to remove unbound AuNRs. This resulted in formation of AuNR
microarray patterns on the regions of the glass surface covered by
the channels. The SEM image showed that the resulting surface
density of AuNRs on each microarray is around 1 particle per 2.56
.mu.m2.
[0101] Gold nanorod microarray functionalization. After
constructing the AuNR microarray patterns on the glass substrate,
they were functionalized within the microfluidic flow-patterning
channels constructed above by forming a self-assembled monolayer
(SAM) through simple ligand exchange (Eck, W. et al. ACS Nano 2,
2263-2272 (2008). A stock solution of thiolated alkane
10-Carboxy-1-decanethiol (HS--(CH.sub.2)10-COOH) was diluted to 1
mM in 100% ethanol and flown through the patterning channel on the
glass substrate. The strong binding of the thiol anchor group with
the gold surface enabled the thiolated alkane to replace the CTAB
coating and serve as a linker to probe antibodies. The antibody
linking was performed by way of the antibody binding to the --COOH
functional group through standard
1-ethyl-3-[3-dimethylaminopropyl]carbodiimide/Nhydroxysuccinimide
(EDC/NHS) coupling chemistry (Grabarek, Z. & Gergely, J. Anal.
Biochem. 185, 131-135 (1990)) Briefly, a mixture of 0.4 M EDC
(Thermo Scientific) and 0.1 M NHS (Thermo Scientific) were injected
at a 1:1 volume ratio in 0.1 M
MES(1-ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride,
Thermo Scientific) solution through the microfluidic
flow-patterning channels and activated the AuNRs microarray
surfaces on the glass substrate. After the surface activation,
primary cytokine antibodies (Ebioscience) were diluted from 100 to
10 .mu.g/mL in 1.times.PBS, loaded into individual channels and
incubated at room temperature for 60 min. This resulted in the
construction of six meandering parallel AuNR stripe patterns of 25
.mu.m in width and 2 cm in length at a pitch of 50 .mu.m on the
glass substrate, each functionalized with distinct antibody
molecules. These patters formed the LSPR biosensor microarrays
affording multiplex detection of 6 different cytokines. To suppress
the non-specific binding on the detection surface, 10 .mu.L of 1%
BSA (Albumin, from bovine serum, SIGMA) in 1.times.PBS and 1.times.
casein (5.times. Casein block solution, Surmodics BioFX) blocking
buffer was added into the microfluidic flow-patterning channels and
incubated for 20 min. During all the process steps, the reagent
solutions were loaded using a syringe pump (LEGATO210, Kd
Scientific) at 1 .mu.L/min. Between every step, the AuNR microarray
surface was thoroughly washed to remove any excessive solutions or
molecules using 20 .mu.L of 1.times.PBS at 3 .mu.L/min.
[0102] Optical setup and LSPR microarray imaging (LSPRmi)
measurement. Following the AuNR microarray antibody
functionalization process, the PDMS mask layer was removed from the
glass substrate and immediately replaced with another PDMS layer
with sample-flow microfluidic channel arrays. This new PDMS layer
was fabricated following the same procedure as described for the
construction of the PDMS microfluidic flow-patterning mask layer as
described above. During the process of assembling the assay chip,
the new PDMS layer was bonded onto the glass substrate such that
the sample-flow channel arrays (200 .mu.m (W).times.2.5 cm
(L).times.50 .mu.m (H)) were placed perpendicular to the LSPR
microarray stripes. The constructed microarray assay chip was
mounted on a motorized X-Y stage (ProScanIII, Prior Scientific,
Rockland, Mass.), manually loaded a sample of 5 .mu.L to each of
the on chip flow channels using a pipette, and performed automated
image scanning at a rate of 180 sensing spots/min. FIG. 8 shows the
system setup by which the AuNR microarray arrays were detected and
imaged based on a dark-field LSPR imaging technique.
[0103] Briefly, the LSPR microarray imaging process started with
guiding white illumination light into the dark-field condenser oil
lens (n.a. 1.20 to 1.45, Mager Scientific) installed on the
inverted fluorescent microscope (Nikon Eclipse Ti-S, Nikon).
Binding of analyte molecules onto the nanostructured metal surface
of each microarray induced an increase in the scattering rate of
light within a certain spectral band as well as a red shift in the
LSPR peak (630 nm for the AuNRs as shown in FIG. 5). A band pass
filter (610-680 nm) was used to capture the maximum intensity
increase observed for the microarrays during analyte surface
binding. Images of microarrays were obtained with the EMCCD camera
and recorded using NIS-Element BR analysis software. A customized
Matlab program was used to analyze and quantify the scattering
intensity shift for each microarray pattern. The region of interest
was automatically selected through an edge detection/background
subtraction algorithm, and then the raw data of each pixel was read
out and processed.
[0104] Electromagnetic-field optical simulation on a single gold
nanorod upon local refractive index change. In order to
theoretically estimate the limit of detection of the LSPRmi
measurement, a finite difference time domain (FDTD) simulation was
performed and the scattering efficiency on a single AuNR was
predicted using commercial multi-physics simulation software,
COMSOL. The simulation used the dimensions of the AuNR that were
determined by the results of the material characterization
described above Information (40 nm in diameter, aspect ratio: 2).
The plasmonically decoupled AuNR arrangement in the fabricated
microarray patterns (FIG. 1) allowed one to focus attention to the
LSPR behavior of the single AuNR, which significantly simplified
the simulation. The frequency-dependent complex permittivity of
gold was derived from Lorenze-Drude model (Kabashin, A. V. et al.
Nature Mater. 8, 867-871 (2009)).
[0105] The far-field domain was defined as a spherical shell
surrounding the AuNR with a radius identical with half the
wavelength of incident light. As the boundary condition of the
simulation, a perfectly matched layer of thickness identical with
half the incident light wavelength was set on top of the surface of
the far-field domain spherical shell, where the intensity of
scattering light from the AuNR exponentially decays. The wave
vector and electric field polarization of the incident light was
set to be perpendicular and parallel to the orientation of the
AuNR, respectively. This excited the longitudinal resonant mode of
the AuNR in the simulation. The mesh size was set to be 1 nm on the
AuNR surface and no larger than 1/10 of the studied wavelength
elsewhere (FIG. 9A).
[0106] The spatial distribution of the electromagnetic field on the
far-field plane was calculated at varying frequencies with and
without the presence of the AuNR to determine the intensity of
scattering wave from the AuNR, IAuNR, and the background signal
intensity, Ibackgound. The scattering cross section Cscs of the
AuNR is determined by integrating the intensity of scattering wave
over the surface of the far-field plane .OMEGA. as
C SCS = .intg. I AuNR I background .times. d .times. .times.
.OMEGA. ( 1 ) ##EQU00001##
and is also used for calculation of the limit of detection.
[0107] Next, a simulation was performed to predict how protein
binding would enhance LSPR by mapping the spatial distribution of
the normalized local electric field intensity
(|Ey|.sup.2/|E0|.sup.2) near the surface of a bare AuNR (FIGS. 9B
and 9C), where |Ey|.sup.2 is the intensity of the y-component of
the local field and |E0|.sup.2 is the field intensity of the
incident light. The spectral shift of light scattered from the AuNR
due to protein binding was simulated. The simulation modeled
protein binding as formation of a uniform dielectric layer on an
antibody-functionalized AuNR surface, which was assumed to cause
the near-surface refractive index value to change from 1.33 (water)
to 1.5 (hydrated protein) (Voros, J. Biophys. J. 87, 553-561
(2004)). The protein attached to the AuNR surface can be either the
analyte or the probe antibody used in the study. The simulation was
performed with the thickness of the protein layer ranging from 0 to
10 nm with a 2 nm increment. Comparing FIG. 9B and FIG. 9C, it is
shown that coating the AuNR with a 10 nm-thick protein layer is
predicted to yield a notable enhancement of |Ey|.sup.2/|E0|.sup.2.
FIG. 9D shows a set of the scattering light spectra of the AuNR
coated with the protein layer of varying thickness.
[0108] Theoretical prediction of the detection limit of the LSPRmi
measurement. The simulation described above predicts a noticeable
spectral red-shift as well as an intensity enhancement for
scattering light from the AuNR at a larger protein coating
thickness. (FIG. 9D) Here, the scattering light intensity is the
LSPR signal that is directly observed in the measurements. Using
the simulation approach above, the quantitative values of the
spectral shift and intensity variation of the LSPR signal induced
by analyte binding on a single AuNR were calculated. The antibody
conjugation of the AuNR in the assay was assumed to form a uniform
layer of closely packed antibody molecules with a thickness of 7 nm
(Erickson et al., Biol. Proced. Online. 15, 32-51 (2009) and a
refractive index of 1.5. Furthermore, a theoretical volume called
the "sensing volume" on top of the antibody layer was assumed
(inset of FIG. 10). The thickness of the sensing volume is
equivalent to the effective diameter of the analyte molecule
(typically 3.4 nm for cytokines; Erickson et al., Biol. Proced.
Online. 15, 32-51 (2009)). In the model, the refractive index of
the sensing volume layer was also set to be 1.5 when the volume was
fully occupied by the analyte molecules. The LSPR signal variation
.DELTA.I due to surface binding of a single analyte molecule is
then given by:
.DELTA. .times. .times. I = .DELTA. .times. .times. S V s * .DELTA.
.times. .times. RI * V a ( 2 ) ##EQU00002##
where .DELTA.RI is the refractive index change in the volume of the
sensing volume Vs, which was described above, Va is the volume of
the single analyte molecule, and .DELTA.S is the experimentally
observed signal difference between before and after loading the
analyte molecules onto the AuNR surface. More specifically,
.DELTA.S is the analyte adsorption induced LSPR peak wavelength
shift, given by
.DELTA. .times. .times. S = .DELTA. .times. .times. .lamda. p RIU
##EQU00003##
for spectrum-shift measurement, where .DELTA..lamda.p is the
resonance peak shift, and RIU is the refractive index unit (=1).
.DELTA.S is the analyte adsorption-induced LSPR intensity (e.g.,
scattering intensity) shift, given by
.DELTA. .times. .times. S = .intg. 610 680 .times. .DELTA. .times.
.times. C SCS .times. d .times. .times. .lamda. RIU
##EQU00004##
for the intensity-based imaging measurement, where
.intg..sub.610.sup.680.DELTA.C.sub.SCSd.lamda. is the integration
of the change in the scattering cross section .DELTA.C.sub.scs
after the analyte loading over .lamda.=610-680 nm, which is the
optical filter band used in this study (grey area in FIG. 9D).
Here, .DELTA.C.sub.scs is derived from Eq. (1) above. For a given
analyte concentration of [A] in the flow channel, the probability
of the analyte binding event on the single AuNR surface .theta. can
be estimated using Hill-Langmuir isotherm as (De Boer, J. H. The
dynamical character of adsorption, second ed. (Oxford University
Press, London, 1968)):
.theta. = [ A ] n K d + [ A ] n = 1 1 + ( K A [ A ] ) n ( 3 )
##EQU00005##
where Kd is the binding constant determined at the equilibrium
dissociation state between the antibody and its engaging antigen,
KA is the ligand concentration producing half occupation, and n is
the Hill coefficient. Alternatively, .theta. represents the ratio
of the number of occupied binding sites over the total number of
sites available for analyte binding.
[0109] Assuming the AuNR deposition density per unit area within
the detection channel to be D and the total binding sites on one
single AuNR to be N.sub.s, the overall signal intensity change
.DELTA.I.sub.A collected from the microarray sensing area can be
calculated by:
.DELTA. .times. .times. I A = .DELTA. .times. .times. I D * D * N s
* ( 1 1 + ( K A [ A ] ) n ) ( 4 ) ##EQU00006##
[0110] The LOD of the analyte for LSPRmi can then be determined
when the signal change equals to the system signal uncertainty, U=
{square root over (U.sub.sys.sup.2+U.sub.fit.sup.2)}, where
U.sub.sys is the uncertainty due to the detection system and U!''#
is the uncertainty due to the peak fitting when gathering the
scattering spectrum. Therefore, one obtains:
U = .DELTA. .times. .times. I * N s * ( 1 1 + ( K A [ A ] ) n ) ( 5
) ##EQU00007##
Combining Eq. (2) and (5) allows one to analytically estimate the
LOD of LSPRmi as:
LOD .function. [ A ] = K A * ( S .function. ( r ) V s * .DELTA.
.times. .times. RI * V a * N s U sys 2 + U fit 2 - 1 ) - 1 / n ( 6
) ##EQU00008##
To estimate the sensitivity improvement of the LSPRmi over the
conventional spectrum-based LSPR measurement, the signal-to-noise
ratio upon an analyte binding event is quantitated using first
order Langmuir equation in Eq. (6). The total available binding
sites on one single AuNR (40 nm (W).times.80 nm (L)) can be
calculated to be .about.361. In an extreme case where AuNR surface
is fully occupied, the spectrum shift (.DELTA..lamda.=5.1 nm) and
scattering cross section change integrated from 610 nm to 680 nm
(.DELTA.Cscs=7.2%) as shown in FIG. 10. According to the most
recent study using a spectrum-based nanorod LSPR biosensor (Nusz et
al., ACS Nano 3, 795-806 (2009)), the researchers' experimental
setup (incandescent white light source, CCD detection of
scattering) yielded a signal variance of U.sub.spectrum=0.3 nm. The
uncertainty due to the sensor and signal processing unit in the
system is U.sub.intensity=0.11% by measuring blank samples.
Substituting these numbers into Eq. (6) allows one to calculate the
ratio of the LOD of the intensity-based LSPRmi platform,
LOD.sub.intensity, to that of the conventional spectrum-shift
measurement technique, LOD.sub.spectrum, as
LOD intensity LOD spectrum = [ ( .DELTA. .times. .times. I spectrum
* N s U spectrum - 1 ) / ( .DELTA. .times. .times. I intensity * N
s U intensity - 1 ) ] = .about. .times. 1 10 ( 7 ) ##EQU00009##
Thus, it is estimated that the technique reduces the LOD by a
factor of .about.10 as compared to the conventional LSPR detection
scheme.
[0111] AuNR microarray intensity and LSPRmi signal variance. The
structural variance across the AuNR microarrays deposited on a
common glass substrate from scanned dark-field images taken for
their calibration measurements were characterized (FIG. 11A). The
upper panel in FIG. 11A shows the line intensity profile of 24
consecutive AuNR microarrays on the same chip. The image data
indicate an average intensity of .about.21,000 with a coefficient
of variance (CV) around 8% across all the microarrays. It reveals
the consistency of the fabrication technique in producing
microarray stripes with good array-to-array structural uniformity.
Such uniformity provided a CV of .about.7% or lower across
calibration data points taken for 10 microarray stripes on the same
chip at a given analyte (TNF-.alpha.) concentration (FIG. 11B). The
result verified the high reproducibility and accuracy of the LSPRmi
measurements using these microarrays.
[0112] System uncertainty and limit of detection of LSPRmi. In
order to characterize the uncertainty and limit of detection of the
LSPRmi system, a control experiment measuring the variance of the
background signal with antibody-conjugated AuNR microarrays with no
cytokines loaded was performed. The average system uncertainty was
calculated to be .about.0.11%, which was determined by the minimum
distinguishable signal equivalent to a confidence factor set to be
3 times the standard deviation of the background noise (a). The
detection limits of the target cytokines were thus obtained from
3.sigma./k.sub.slope, where k.sub.slope is the slope of the
regression of the calibration curves using sigmoidal
curve-fitting.
Results
[0113] LSPR microarray chip preparation. The LSPRmi biochip
includes eight parallel microfluidic channels of 250 nL in volume
and six meandering stripes of antibody-functionalized AuNR
(characteristic properties of the AuNRs are shown in FIG. 5)
ensembles with ten turns on a glass substrate, which run orthogonal
to the channels (FIG. 1a). Each microfluidic channel has inlet and
outlet ports for reagent loading and washing. This chip design
gives rise to an array of 480 stripe shaped LSPR biosensing spots
of 25 .mu.m wide and 200 .mu.m long each on the entire chip. The
AuNR stripes were conjugated with antibodies against six different
cytokines: interleukin-2 (IL-2); interleukin-4 (IL-4);
interleukin-6 (IL-6); interleukin-10 (IL-10); interferon-gamma
(IFN-.gamma.); and tumor-necrosis-factor alpha (TNF-.alpha.) using
a one-step microfluidic patterning technique (FIG. 6). The
microfluidic patterning technique allowed for construction of ten
segments of six collocating parallel multiplex immunoassay spots in
each channel without cumbersome manual reagent dispensation on the
large number of locations (FIG. 1a).
[0114] The scanning electron microscopy images show that the LSPR
sensing spots are coated with a disordered monolayer at a surface
number density of .about.1 particles per 2.56 um2 (FIG. 1a and FIG.
7), which corresponds to an average particle-to-particle
distance>200 nm (FIG. 1b). The theoretical calculation predicts
a much shorter (65 nm) decay length of the highly localized
photo-excited EM field surrounding each nanoparticle (Inserted
panel of FIG. 1b). The disperse distribution of the nanoparticles
eliminates complicated electromagnetic couplings between
neighboring nanoparticles in the ensembles. This critically makes
the multi-arrayed LSPR sensor performance uninfluenced by the
disordered nanoparticle arrangement. The ensemble of 2,000
plasmonically uncoupled AuNRs on each sensor spot yields a
scattering spectrum with a distinct resonance (FIG. 1c). Thus, the
principle of the LSPRmi platform relies on the scattering light
intensity change in a particular plasma resonance range caused by
the target analyte binding onto the AuNR
[0115] Real-time LSPR multiplex immunoassay. Characterizing the
dynamic performance of the LSPR biosensors allows one to assess the
total assay time. To this end, the real-time sensor signal
variations associated with analyte surface binding were measured in
the multiplex scheme. This measurement used a mixture of the six
target cytokines suspended in phosphate buffered saline (PBS)
solution. Here, a different concentration level was set for each
analyte such that IL-2, IL-4, IL-6, IL-10, TNF-.alpha., and
IFN.gamma. were at 10,000 pg/mL, 5,000 pg/mL, 3,000 pg/mL, 1000
pg/mL, 500 pg/mL and 250 pg/mL, respectively. The cytokine mixture
was loaded into one of the microfluidic channels of the device and
the time-course signal variation from the sensor spots (FIG. 2) was
observed. From this measurement, it was found that the
analyte-binding event reached the equilibrium within 30 min after
the introduction of the cytokine mixture. This rapid analyte
binding kinetics allows the assay to be performed with a very short
incubation time as compared to conventional fluorescence sandwich
immunoassays. After the equilibrium was reached, the loaded samples
were washed to remove non-specifically bound serum constituents
from the sensor surfaces. This resulted in a sensor signal
intensity reduction by .about.8%.
[0116] High-throughput LSPR microarray biosensing and calibration.
A significant feature of LSPRmi chip assay is its ability to
analyze the multiple analytes at high throughput. This capability
was demonstrated by performing massively parallel data-intensive
sensor calibration using the device within a short period of time.
The obtained calibration data for each analyte subsequently allowed
for a determination of the dynamic range and detection limit of the
assay. At first, eight PBS samples were prepared, each containing a
mixture of the six purified cytokine species (i.e., IL-2, IL-4,
IL-6, IL-10, IFN-.gamma., and TNF-.alpha.) and they were manually
pipetted into the inlets of the eight channels of the device (FIG.
3a). Each sample introduced to one of the channels contained the
cytokines all at the same concentration, which was one of the eight
levels between 50 to 10,000 pg/mL. The sensor response was recorded
over 480 individual AuNR microarray sensing spots on a single chip
at a scanning rate of 180 spots/min before sample loading and after
washing when the analyte surface binding reached equilibrium at
.about.30 min. Thus the total assay time including sample loading
and washing (5 min), incubation and equilibration (30 min), and
image scanning (5 min) was around 40 min. FIG. 3b shows a result of
mapping the local intensity variation (.DELTA.I/I.sub.0) after
loading and washing cytokine molecules over 480 sensor spots, where
I0 is the original sensor signal intensity prior to the assay and
.DELTA.I is the intensity shift after the assay. Sensor calibration
curves were then obtained for the six cytokines by plotting the
normalized intensity shift .DELTA.I/I0 spatially averaged over 10
sensor spots as a function of analyte concentration (FIG. 3c). It
was additionally verified that these measurements were consistent
across ten sensor spot replicates with an averaged coefficient of
variance around 7% as described above. The calibration curves
indicate that the assay achieves a large dynamic range from 10 to
10,000 pg/mL for the cytokine biomarkers. The dashed lines in the
plots represent sigmoidal curves fitted to data points (Hill type).
The limit of detection (LOD) was determined for each analyte as
defined by 3.sigma./kslope, where .sigma. and kslope are the
standard deviation of background signal obtained from blank control
and the slope of the regression of each calibration curve,
respectively. The determined LOD's were 11.43 pg/mL (TNF-.alpha.),
6.46 pg/mL (IFN-.gamma.), (IL-2), 20.56 pg/mL (IL-4), 11.29 pg/mL
(IL-6), and 10.97 pg/mL (IL-10) as summarized in Table 1.
[0117] Multiplex LSPR microarray immunoassay of serum cytokines. To
test the multiplex immunoassay capability of the device, sets of
serum samples were prepared using heat inactivated and charcoal
absorbed human serum and spiked with different mixtures of
cytokines. Using these samples, post-assay signal images were
obtained for the panel of the six striped sensing spots integrated
within the same microfluidic channel, where a sample of particular
cytokine mixture pattern was loaded. It was observed that the
signal intensity of each sensor array was dependent on the target
cytokine and independent of the presence of off-target cytokines in
the serum solution (FIG. 4a). The intensity shift was translated
into the analyte concentration detected at each sensor from the
calibration curves obtained above (FIG. 4b). No statistically
significant difference was found between the measured cytokine
concentrations and the expected value of 500 pg/mL. Furthermore,
the sensors targeting cytokines absent from the serum matrix
yielded signals below their LOD as expected. The percent recovery,
which is defined to be the amount of analyte detected as the
fraction of the amount of known analyte in a sample, was
calculated. The percent recovery for all cytokines fell within an
acceptable range of 85-115% (Guidance for Industry: Bioanalytical
Method Validation. Rockville, Md.: Food and Drug Administration,
U.S. Department of Health and Human Services, 2001). Thus, the
multiplex assay exhibits minimum cross-reactivity amongst the six
cytokines biosensors.
[0118] Assay validation with the gold standard method. Wide
acceptance of a new multiplex immunoassay method utilizes its full
validation with the existing "gold-standard" assay--ELISA.
Healthy-donor serum samples spiked with a mixture of six cytokines
at concentrations ranging across the entire dynamic range of the
assay were prepared and used to perform multiplex immunoassay using
the LSPRmi chip. Together with this assay, ELISA-based measurements
of the analytes for the same samples as above were performed. The
ELISA-based measurements were based on the singleplex scheme. In
other words, the assay targeted only one of the six cytokines in
each measurement to avoid any potential crosstalk between different
probe molecules. The singleplex ELISA measurements were repeated
for all the six cytokines across the serum samples prepared above.
Finally, the LSPRmi immunoassay measurements were compared with the
ELISA measurements and an excellent correlation (R2=0.9726) was
observed, resulting in a nearly one-to-one linear regression
between the both assay methods (FIG. 4c).
[0119] Immune status monitoring of pediatric patients with
cardiopulmonary bypass surgery. Leveraging the strengths of the
LSPRmi immunoassay, the utility of the technology to allow
monitoring of the inflammatory response of neonates following
cardiothoracic surgery necessitating cardiopulmonary bypass (CPB)
was demonstrated. Repair of congenital heart defects necessitates
open heart surgery using CPB to supplant heart-lung function during
surgery, and is the most common birth defect in the United States
(Agus, M. S. D., et al. N. Engl. J. Med. 367, 1208-19 (2012)).
Blood contact with the artificial surfaces of the CPB circuit is
known to elicit a substantial inflammatory response in the
immediate post-operative period that is normally restored to
pre-operative levels within 48 hours (Mahle, W. T., et al. Ann.
Thorac. Surg. 97, 950-6 (2014)). Serum samples were collected prior
to surgery (Pre), and on post-operative days one (D1), two (D2),
three (D3), and four (D4) and the LSPRmi immunoassay was used to
quantify circulating serum cytokine levels on these days in two
neonates undergoing congenital heart surgery with CPB (FIG. 4d).
Increased levels of both IL-6 and IL-10 were observed on
post-operative day one following CPB in both patients, followed by
a return to pre-operative levels of all cytokines on postoperative
days D2, D3, and D4. The LSPRmi assay demonstrates a capacity of
detecting variable degrees of cytokine expression.
TABLE-US-00001 TABLE 1 The LOD's of target cytokines were
determined from the minimum distinguishable analytical signal
defined by 3.sigma./kslope., where .sigma. is the standard
derivation of the LSPRmi signals from blank samples, and kslope is
the regression slope obtained from the calibration curves using
sigmoidal curve-fitting. Blank S.D. U.sub.system K .sub.slope LOD =
3.sigma./k.sub.slope Cytokine (.sigma.) (%) (3.sigma.)(%)
(%)*(pg/mL).sup.-1 (pg/mL) IFN-.gamma. 0.022 0.065 0.010 6.46
TNF-.alpha. 0.034 0.103 0.009 11.43 IL-2 0.069 0.206 0.010 20.56
IL-4 0.031 0.092 0.020 4.6 IL-6 0.038 0.113 0.010 11.29 IL-10 0.030
0.088 0.008 10.97
Example 2
[0120] The LSPR cytokine assay described in Example 1 was used to
determine cytokine levels in leukemia patients undergoing
treatment. Results are shown in FIG. 12. The two patients were
patients with relapsed acute lymphoblastic leukemia (ALL) who had
under gone chimeric antigen receptor T-cell therapy (CAR T-cell).
This therapy results in the release of inflammatory mediators
(cytokines) that result in a systemic inflammatory response
syndrome leading to hemodynamic instability and shock. Two
therapies are available to block the action of two of these
cytokines; etanercept blocks tissue necrosis factor-alpha (TNF-a)
and tocilizumab blocks interleukin 6 (IL-6). These therapies work
if cytokine levels are elevated and over use of the therapies have
the potential to immune suppress the patient putting them at risk
for development of sepsis (overwhelming infection). Currently, the
standard turnaround time for measuring cytokines is days so
patients are typically treated without knowing cytokine levels.
[0121] Both of these patients presented to the PICU with the
systemic inflammatory response syndrome that progressed to shock.
The measurements were provided to the treating clinicians on
patient 1 to help guide the tocilizumab therapy. No clinical
decisions were made on the data from patient 2 due to the patient's
clinical condition.
Example 3
[0122] This example describes AC electroosmosis (ACEO)
incorporation into exemplary devices.
Fabrication & Functionalization
[0123] Device Fabrication:
[0124] The standard photolithographic liftoff, bulk micromachining
and sputtering processes are utilized to deposit parallel coplanar
Cr/Pt (50 nm) plate microelectrodes on glass substrates, as shown
in FIG. 14a. Briefly, the glass wafers was treated with Piranha
solution ((HOSO.sub.4:H.sub.2O.sub.2=3:1 v/v), rinsed thoroughly
with D.I. water and air dried before use. The electrode pattern was
first transferred onto a pre-coated positive resist layer (AZ726)
using a darkfield photomask and contact lithography. After removing
the exposed photoresist with developer, an E-beam evaporation
method (EnerJet Evaporator) was used to deposit a 10 nm of chrome
as adhesion layer and then 50-nm of platinum on top of it. The
electrodes coated glass substrates was soaked in pure acetone
solution to remove the photoresist residue and grease, and then
treated with nitric acid solution (HNO.sub.3:H.sub.2O=1:2 v/v),
thoroughly rinsed with D.I. water, kept in ultrasonic bath with
D.I. water, and air dried for further surface function.
[0125] Device Functionalization:
[0126] The surfaces of the glass substrates and the PDMS
microfluidic mask layer were treated with 02 plasma. Immediately
after plasma treating, the PDMS mask and the electrodes on the
glass substrate were aligned under a microscope to ensure that the
PDMS patterning channels fall in between the adjacent electrodes
(FIG. 2b). O.sub.2 plasma treating can generate a negatively
charged glass surface owing to the dissociated hydroxyl groups
existing on the glass, which enables the glass substrate to attract
the positively charged, CTAB stabilized AuNRs onto its surface. A
colloidal solution containing AuNRs was loaded through the
microfluidic patterning channel at a flow rate of 1.5 .mu.l/min for
2 min in both direction. The chip was then stored in a petri dish
for 2 hours with inlets and outlets sealed by a cover glass to
prevent evaporation and avoid dry-out of the AuNR solution in the
channels.
[0127] The microfluidic channels was then washed with DI water
(around 5-6 .mu.l) to remove the unbounded AuNRs in the solution
and loaded with 1 mM Biotin PEG (polyethylene glycol, 10 kDa) Thiol
water solution (NANOCS). The stronger affinity of the thiol anchor
group with the gold surface enables the thiolated PEG Biotin to
replace the CTAB coating and serve as a linker to probe
streptavidin. The PEG-Biotin functionalized AuNRs was incubated
overnight with wet tissues in the Petri dish to construct a
moisture environment and avoid dry-out.
[0128] Biosensing Platform
[0129] General Sensing Set Up
[0130] Dark-field microscopy with an electron multiplying charge
coupled device (EMCCD) was used in the signal detection for the
ACEO coupled LSPR nanobiosensor described above, as shown in FIG.
15a. The LSPR-based detection measures the absorbance spectrum
shift (local refractive index change) of a nanostructured metal
surface due to the binding of analyte molecules. Here, this
spectrum shift signal is converted into optical intensity change by
using a proper band-pass filter (680/13) coupled with EMCCD
detector. The optical intensity signal is analyzed across a large
number of nanoparticle biosensors in the micro-array, which
contains statistically and biologically meaningful information. The
theoretical model predicts that this approach result in a LOD value
more than 10 times lower than that of spectrum-shift detection
schemes commonly used in conventional label-free LSPR
biosensing.
[0131] Assay Detail
[0132] The PDMS mask with loading channel was peeled off and
immediately replaced with parallel straight channels (400 .mu.m
(W).times.2.5 cm (L).times.50 .mu.m (H)) perpendicular to the
electrode barcode, shown in FIG. 14c. To generate a proper ions
concentration environment, 1000-time diluted xl PBS solution was
used as rinsing buffer to wash away the unbounded Biotin PEG Thiol
molecules. The chip was then mounted on a motorized X-Y darkfield
microscope stage (ProScanIII, Prior Scientific, Rockland, Mass.)
with electrodes connected to two AC function generator (180 phase
difference) and ready for measurements. Streptavidin was dissolved
in 1000-time diluted.times.1 PBS with concentration range from 50
fg/ml (0.67fM) to 100 pg/ml (1.33 pM) and was injected by syringe
pump at a flow rate of 2 .mu.l/min. The AuNRs microarray was
detected and imaged based on darkfield LSPR imaging technique
mentioned above. A band-pass filter (680/13 nm) was used to capture
the maximum intensity increase of the microarrays due to
Biotin-streptavidin binding on gold surface. The microarray image
was real-time recorded by EMCCD camera using NIS-Element BR
analysis software and was analyzed and quantified the scattering
intensity change by a customized MATLAB code developed in our
lab.
[0133] Results
[0134] Results show that the ACEO coupled LSPR nanobiosensor
detected streptavidin down to 50fg/ml (.apprxeq.0.67 fM), as
indicated in FIG. 16a. The limit of detection (LOD) for ACEO
coupled biosensor is calculated to be 36.3 fg/ml (based on 3.sigma.
of the control signal, where .sigma. is the standard derivation of
signal when measuring the blank sample) which is approximately 1000
times lower than the LOD of that without ACEO (29.4 pg/ml), shown
in FIG. 16b. Moreover, the assay time was shortened to 15 min twice
as fast as previous assay with the same sample volume (5 .mu.l).
The shear-flow on sensing surface can also help eliminate
non-specific binding, as shown in FIG. 16d.
Example 4
[0135] Early attempts to target cytokines, a key biologic component
of the inflammatory response, in sepsis resulted in mixed results
for more than 100 phase II/III clinical trials. The varied results
from these studies are a direct result of the heterogeneous nature
of this complex patient population, fundamental differences in
genetics, as well as diverse disease etiologies (bacterial/viral
infections, trauma) resulting in disparate classes of immune
dysregulation. It was contemplated that integration of prospective
biomarker risk-stratification and precision targeted anti-cytokine
therapies in clinical trial design will greatly increase the
likely-hood of the ability of these trials to show significant
benefit.
[0136] The present example tests a validated biomarker
risk-stratification algorithm and precision targeted anti-cytokine
therapy using currently FDA-approved anti-cytokine biologics in
clinical trial design.
[0137] Design/Methods: Briefly, the microfluidic immunoassay
platform described herein that enables rapid (<30 min),
multiplex cytokine (>6 analytes) quantification from small blood
volumes (<1 drop of blood) was used.
[0138] Results: Five serum biomarkers, which together have a
negative predictive value for 28-day mortality of 97%, when
measured within the first 24 hours of PICU admission, were
measured. This panel allows risk stratification of pediatric sepsis
patients into low-risk of mortality (<3% probability) and
high-risk of mortality (>25% probability) groups, with nearly
2/3 of patients being classified as `low-risk`. Results (FIG. 17)
showed a significant increase of two serum cytokines, tumor
necrosis factor alpha (TNF-.alpha.) and interleukin-6 (IL-6) in
patients identified as high-risk compared to those identified as
low-risk (FIG. 17).
[0139] Conclusion: The large variability of serum cytokine values
within the high-risk group supports the need for rapid cytokine
determination to guide precision-targeted anti-cytokine therapy in
only those patients with elevated cytokines.
Example 5
[0140] This Example describes additional methods of fabricating
surfaces.
Chemical Vapor Deposition of Aminated Silanes on Substrate Surface
to Facilitate AuNR Deposition.
[0141] Aminated silanes (eg., (3-Aminopropyl)triethoxysilane,
(3-Aminopropyl)dimethylmethoxysilane, or
(3-Aminopropyl)dimethylethoxysilane) were deposited onto the
substrate surface (glass, or thermoplastic polymer (e.g., COP, COC,
PMMA) by chemical vapor deposition (CVD) (vacuum, 15-20 in Hg for
18-24 hours). Following CVD AuNRs were patterned on the amine
functionalized substrate using a microfluidic patterning technique
through dative bonding between the AuNR and the amine
functionalized substrate. The constructed AuNR barcode patterns
were functioned with thiolated alkane 10-Carboxy-1-decanethiol
(HS--(CH.sub.2).sub.10--COOH) through ligand exchange and
subsequently activated using standard EDC/NHS coupling chemistry.
The probe cytokine antibodies were then loaded into individual
patterning channels forming a barcode array consisting of six
parallel stripes each functioned with distinct antibodies to afford
multiplexed detection of 6 different cytokines at one time.
[0142] All publications and patents mentioned in the present
application are herein incorporated by reference. Various
modification and variation of the described methods and
compositions of the disclosure will be apparent to those skilled in
the art without departing from the scope and spirit of the
disclosure. Although the disclosure has been described in
connection with specific preferred embodiments, it should be
understood that the disclosure as claimed should not be unduly
limited to such specific embodiments. Indeed, various modifications
of the described modes for carrying out the disclosure that are
obvious to those skilled in the relevant fields are intended to be
within the scope of the following claims.
* * * * *