Toward Label-Free SERS Detection of Proteins through Their Disulfide Bond Structure

Abstract

The molecular structure of many proteins contains disulfide bonds between their cysteine residues. In this work we demonstrate the utilization of the disulfide bond structure of proteins for their label-free determination by surface-enhanced Raman spectroscopy (SERS). The new approach for label-free SERS detection of proteins is demonstrated for human insulin. The protein was selectively extracted from spiked plasma samples using target-specific functionalized nanomaterial. Enzyme-linked immune assay (ELISA) was used to detect insulin in the blood plasma and cross-validate the SERS method. The disulfide bonds in the molecular structure of the protein were chemically reduced and used for their chemisorption onto the gold-coated copper oxide substrate in a unified orientation at a very short distance from the hotspots. The oriented chemisorption of the protein caused significant enhancement to the signal intensity of its Raman vibration modes. This is attributed to the strong short-range electromagnetic and chemical enhancement effects that are experienced by the immobilized protein. Using this approach, label-free and reproducible SERS detection of insulin, down to 10 zM (relative standard deviation [RSD] = 5.52%), was achieved. Sixty-five percent of proteins contain disulfide bonds in their molecular structure. Therefore, the new label-free SERS detection method has strong potential for the determination of ultralow concentrations of proteins at pathology labs and in biology research.

Keywords

disulfide bonds oriented immobilization label-free SERS insulin gold-coated copper oxide

Introduction

The rapid and sensitive screening of proteins is critical for the diagnosis of diseases and monitoring of therapeutic efficacy, as well as the discovery of new protein biomarkers in biomedical research. Analytical methods such as immunoassay, mass spectroscopy, and turbidimetric analysis are utilized for the detection of proteins. However, these methods are slow and complex and use error-prone protocols.^1–4 The analysis of proteins by label-free methods offers the advantages of low cost, minimum sample preparation time, and the absence of the potential side effects of chemical labeling.^5–7

Within the last decade, surface-enhanced Raman spectroscopy (SERS) has emerged as one of the most sensitive bioanalytical assay techniques. The Raman signal enhancement in SERS is attributed to the electromagnetic (EM) field that is experienced by the analyte molecules when they become trapped within the gaps between the closely spaced nanostructures of a metallic substrate, and the formation of a charge transfer complex between a chemisorbed analyte and the substrate.⁸ Park et al. demonstrated that a combined charge transfer and EM enhancement factor (EF) of 10⁶ to 10⁸ is sufficient for the detection of a single molecule of the analyte by SERS.⁹

The determination of biomolecules by SERS is carried out by either label or label-free methods. In the label-based methods, a Raman probe that is attached to a metallic SERS substrate is used for the indirect detection of the biomolecule where the Raman vibration modes of the probe are monitored rather than those of the biomolecules themselves. In contrast, the label-free methods do not use a Raman probe and directly detect the Raman vibrations of the target analyte. Label-free SERS detection of proteins requires that the biomolecule structure contain a chromophore moiety that provides a strong Raman signal due to surface-enhanced resonance Raman scattering (SERRS).¹⁰ However, many proteins lack the presence of a chromophore moiety in their molecular structure and have a relatively low Raman scattering cross section. In addition, the weak physical adsorption of the protein leads to random orientation of the biomolecules onto the substrate, which undermines the chemical enhancement in the SERS measurement of the protein.^11,12

The EM and charge transfer enhancements in SERS can be maximized by the oriented immobilization of analyte molecules at a very close distance from the nanostructured surface of the SERS substrate.^8,11 Many proteins, such as insulin, contain a disulfide bond structure to maintain their stability.¹³ These bonds can be chemically reduced to provide free sulfhydryl (SH) groups that form stable Au–S bonds with a gold surface.¹⁴ Therefore, in this work, we reduced the disulfide bond structure of human insulin to provide free SH terminal groups and assemble the biomolecules, in a unified orientation, at a very short distance from the nanostructures of gold-coated copper oxide SERS substrate.

Insulin is a naturally occurring hormone that is responsible for keeping blood sugar within its normal level of ~79 pM.¹⁵ An abnormally high insulin concentration in blood leads to diseases such as hyperinsulinemia and increases the risk of Alzheimer disease.^16,17 Low insulin levels are mainly associated with developing a diabetic medical condition due to the functional damage of the pancreatic beta cells.¹⁸ Therefore, a simple and sensitive method for the determination of insulin is valuable for the clinical diagnosis of insulin-related diseases and assessing the quality of pancreatic islets for the treatment of diabetes.¹⁹ In addition, it can also support the ongoing research on insulin-derived amyloidosis.¹³ In this work, human insulin was selectively extracted from a spiked blood plasma using extractor magnetic gold nanoparticles that are functionalized with an anti-insulin antibody. The protein was recovered from the extractor nanoparticles, reduced, and detected by SERS down to 10 zM. The SERS quantification of the protein was cross-validated against enzyme-linked immune assay (ELISA).

Materials and Methods

Chemicals and Reagents

Magnetic gold nanoparticles (particle size = 51.8 ± 6.1 nm) were purchased from Nanoimmunotech (Zaragoza, Spain). Anti-insulin antibody was purchased from Abcam (Cambridge, UK). Human insulin, phosphate-buffered saline (PBS), an insulin ELISA kit, glycine, and potassium hydroxide were purchased from Sigma Aldrich (St. Louis, MO). Neutral tris(2-carboxyethyl)phosphine (TCEP) solution was purchased from Thermo Fischer Scientific (Waltham, MA). LoBind tubes were purchased from Eppendorf AG (Hamburg, Germany). Gravity flow size-exclusion columns (Illustra NAP-5) were purchased from GE Healthcare Life Sciences (Sydney, Australia). Deionized water (ultrapure Millipore, 18.2 MΩ cm at 25 °C) was used in all preparations. Gold-coated copper oxide substrates (substrate diameter = 4 mm) were obtained from FLEW Solutions (Brisbane, QLD, Australia) and used for the SERS measurements. Blood plasma samples were provided under Queensland University of Technology’s research ethics clearance exemption 1800001209.

Preparation of Human Insulin Standard Solutions

Insulin standard stock solution (10.5 mg/mL) was used to prepare 20 zM, 20 fM, 100 pM, 160 pM, 300 pM, 450 pM, and 600 pM insulin working solutions by serial dilution using 1× PBS buffer (pH 7.4).

Preparation of Extractor Magnetic Gold Nanoparticles

Magnetic gold nanoparticles were used for the development of the extractor nanoparticles due to their magnetic property, which allows for their collection from solutions using an external magnet. Target-specific antibody fragments were prepared by reducing the disulfide bonds in the hinge region of the insulin antibody using TCEP.³ Briefly, 90 µL of 0.4 mM neutral TCEP solution was mixed with 90 µL of the antibody (0.2 mg/mL) in LoBind Eppendorf tubes and incubated for 30 min at 37 °C for the formation of the antibody fragments. Antibody fragments (180 µL) were mixed with 200 µL of magnetic gold nanoparticles and left to stand for 1 h to form Au–S bonds between the fragments and the nanoparticles. To avoid nonspecific binding from interfering molecules, the remaining bare sites on the nanoparticle surface were blocked by adding 38 µL of 1-butanethiol (1 × 10⁻⁶ M in 1× PBS, pH 7.4) and allowing the mixture to stand for 1 h to the complete attachment of the alkane thiol onto the gold surface of the nanoparticles via Au–S bonds. The functionalized and backfilled nanoparticles were then collected from solution using an external magnet, washed three times with 100 µL of 1× PBS buffer (pH 7.4), redispersed into 100 µL of 1× PBS buffer (pH 7.4), and stored at 4 °C for future use.

Selective Extraction of Insulin from Blood Plasma

Human insulin (250 pM) was spiked into a blood plasma sample and the antibody-functionalized nanoparticles were used to extract the protein from the spiked sample. Spiked blood plasma (100 µL) was mixed with 100 µL of the antibody-functionalized nanoparticles and left to stand for 15 min at room temperature with occasional shacking to bind the protein. The nanoparticles were then collected from the plasma matrix using an external magnet and washed five times with 100 µL of 1× PBS buffer (pH 7.4) to remove any weakly adsorbed interfering molecules. To recover the bound protein, the nanoparticles were reconstituted into 100 µL of 0.1 M glycine HCL buffer (pH 2.5) and left to stand for 5 min at room temperature. The nanoparticles were collected using an external magnet, and the buffer solution containing the released protein was loaded onto a size-exclusion column to remove the glycine buffer. The purified protein was eluted from the column using 500 µL of 1× PBS.

ELISA Measurements

To confirm the identity of the extracted protein, an aliquot of the eluted sample was screened using an insulin-specific ELISA kit and a linear calibration curve was constructed in the concentration range of 0–4 ng/mL, by recording the average optical density (OD) at 450 nm against the concentration of the protein standard. The regression equation was found to be y = 0.6691x − 0.036 (R² = 0.9991) ( Suppl. Fig. S1 ). All ELISA measurements were carried out using GloMax Explorer System (Promega, Madison, WI).

Rapid Reduction of Human Insulin

Different concentrations of standard human insulin (in PBS, pH = 7.4) were mixed with equal volumes of 20 mM TCEP solution (in PBS, pH = 7.4) into LoBind Eppendorf tubes in the presence of gold-coated copper oxide substrate. The mixtures were left for 15 min to allow for the reduction of the disulfide bonds within human insulin and the binding of the biomolecules to the metallic substrate through Au–S bond formation. The solution was then removed and the substrate washed with 1× PBS buffer to remove the excess TCEP. Finally, the protein-bearing substrate was dried under N₂ stream and scanned with a handheld Raman spectrometer.

Fabrication of Gold-Coated Copper Oxide Substrates

Gold-coated copper oxide sensors, which had been reported earlier by Balčytis et al.,²⁰ were used as SERS substrates. Briefly, an aqueous solution that consisted of 1.25 M NaOH and 66 mM Na₂S₂O₈ was used for the wet chemical etching of polished Cu foil, for 5 min at 65 °C, and the development of nanostructured cupric oxide layers. Magnetron sputtering was then used for the plasma vapor deposition (PVD) of atomic gold onto the developed copper oxide surface layers.²⁰

SERS Measurements

The SERS measurements were carried out using a handheld Raman spectrometer (spectral resolution = 12 cm⁻¹, spot size = 2.5 mm; Ocean Optics, Largo, FL) in the raster orbital scanning (ROS) mode over the wavelength range 700–1700 cm⁻¹.³ A 785 nm laser source (laser power = 5 mW) was used for excitation. Ten accumulations with a total acquisition time of 1 s were used for the SERS measurements. The software algorithm of the instrument (OceanView Spectroscopy 1.5.07) automatically averages and corrects the background noise and fluorescence within the acquired spectra.^3,21

Results and Discussion

Synthesis of Extractor Nanoparticles and Extraction of Human Insulin

Insulin-specific extractor nanoparticles were synthesized by functionalizing gold-coated magnetic nanoparticles with anti-insulin antibody fragments. The antibody fragments were synthesized by simple chemical reduction of the disulfide bond structure within the antibody hinge region. The reduction process generates free terminal SH groups within the molecular structure of the antibody fragments. The SH terminals were used to attach the antibody fragments onto the gold surface of magnetic nanoparticles in a unified orientation through the formation of stable Au–S bonds. The remaining empty gaps on the surface of the nanoparticles were blocked with inert alkane thiol molecules to prevent the nonspecific adsorption of interfering molecules from the sample matrix.

The extractor nanoparticles were used to selectively bind insulin from blood plasma ( Fig. 1 ).^3,21 After binding the target protein, the extractor nanoparticles were then removed from the blood plasma matrix and the bound protein recovered by adjusting the pH of the nanoparticles to break the weak hydrogen bonds between the antibody and the antigen ( Fig. 1 ). ELISA detects insulin in the blood plasma extract (Table 1, Suppl. Fig. S1), thus confirming the successful isolation of the protein by the extractor nanoparticles.

Figure 1.

Schematic representation of the selective extraction of human insulin from spiked blood plasma by antibody-functionalized magnetic nanoparticles.

Table 1.

Determination of Insulin in a Spiked Blood Plasma Sample.

Spiked Concentration	ELISA Quantification	% Recovery (n = 3)	% Coefficient of Variation
250 pM	255 pM	102%	10%

Fabrication of Gold-Coated Copper Oxide Substrates

The scanning electron microscopy (SEM) image and energy-dispersive x-ray (EDX) measurement of the gold-coated copper oxide SERS substrate are depicted in Figure 2 and show numerous gold copper oxide nanoflacks. The high degree of the surface roughness provides multiple nanogaps that act as plasmonic hotpots for sensitive SERS measurements.²⁰

Figure 2.

(a) SEM and (b) EDX images of gold-coated copper oxide substrate.

SERS Detection of Unreduced and Reduced Human Insulin

Unreduced human insulin (80 pM) was loaded onto the gold-coated copper oxide substrate and screened by SERS. The Raman spectrum of the physically adsorbed protein is depicted in Figure 3 . The Raman band at 962 cm⁻¹ is attributed to C–C skeletal vibrations (random coil). The Raman band at 1027 cm⁻¹ is attributed to the phenylalanine residue in the protein structure.²² The bands at 1086, 1305, and 1360 cm⁻¹ are attributed to C–N and C–H vibrations, respectively.^22,23 The band at 1522 cm⁻¹ is attributed to histidine residue in the protein structure.²⁴ As indicated by Figure 3a , the Raman spectrum of the unreduced protein was very weak and could not be reliably used for the determination of the protein. Similar weak Raman spectra of physically adsorbed human insulin on gold substrate were also observed by other research groups.²⁵ The weak Raman signal of the unreduced protein is attributed in part to the random and physical adsorption of the biomolecule onto the substrate surface and the lack of chemical enhancement. To overcome this problem, the disulfide bond structure of insulin was chemically reduced to generate free SH terminal groups that immobilize the biomolecules onto the substrate through the formation of Au–S bonds.^9,11

Figure 3.

SERS spectra of (a) 80 pM unreduced human insulin (red spectrum) and (b) 80 pM reduced human insulin (blue spectrum) after chemisorption onto gold-coated copper oxide substrate. The green line depicts the blank substrate.

The Raman spectrum of reduced insulin is depicted in Figure 3b (blue spectrum) and shows vibration modes at 1395/1281 cm⁻¹ (C–H, amide III vibrations),^26–28 1206/1024 cm⁻¹ (C–C₆H₅ stretching, phenylalanine/tryptophan residues),^26,27 939 cm⁻¹ (C–C stretching, α-helix conformation),^26,27 842 cm⁻¹ (ring breathing, tyrosine residue),²⁹ and 737 cm⁻¹ (C–S vibration).²⁴ As indicated by Figure 3b , a significant enhancement in the SERS signal intensity of the chemisorbed biomolecules was observed. The high Raman signal intensity of the reduced insulin is attributed to the formation of a charge transfer complex between the biomolecule and the gold-coated substrate. In addition, the chemisorption of the biomolecule through the formation of Au–S bonds influences it to assume a unified orientation onto the plasmonic surface of the substrate. This maximizes the short-range chemical enhancement effect in the SERS measurement of the reduced insulin due to the amplification of the molecular polarization tensor of the chemisorbed biomolecules.^8,9,11

Effect of Reduction Time on the Raman Signal Intensity

To investigate the effect of the reduction time on the Raman signal intensity of the insulin, 80 pM insulin was reduced with TCEP for 15, 30, 60, and 120 min, respectively. As indicated by Figure 4a , the signal intensity of the reduced insulin Raman bands did not significantly increase by increasing the reduction time. Therefore, a reduction time of 15 min was found to be optimum for breaking the disulfide bonds of the insulin molecules by TCEP.

Figure 4.

(a) SERS spectra of 80 pM human insulin after chemical reduction at different time intervals. (b) SERS calibration curve of reduced insulin within the concentration range 10 zM to 300 pM. The inset shows the corresponding Raman spectra within the screened concentration range.

Label-Free SERS Quantification of Insulin

For the label-free SERS quantification of the protein, the intensity of the Raman band at 939 cm⁻¹ was monitored at different concentrations of the reduced insulin ( Fig. 4b ). The inset of Figure 4b depicts the change in the SERS signal intensity at 939 cm⁻¹ with the concentration of reduced insulin. A linear relationship between the SERS signal intensity and the concentration range of 10 zM to 300 pM was developed and it followed the regression equation y = 2.956x + 396.33 (R² = 0.9883). ( Fig. 4b ). Supplemental Figure S2 depicts the SERS spectrum of 10 zM of reduced insulin. The RSD in the SERS measurements was found to be 5.52% (n = 3). The regression quality control (QC) was 6.84%. The 95% confidence interval and standard error of the slope were 0.3697 and 0.1438, respectively. The wide working range of the SERS quantification indicates its potential for the detection of insulin at low and high concentrations.

The reproducibility of the SERS measurements of the protein was investigated by comparing the Raman spectra of nine different concentrations of the protein (on nine independent substrates). As indicated by Figure 5 , the Raman spectra were highly reproducible. Supplemental Figure S3a depicts the reproducible Raman spectra of three independent measurements of 300 pM reduced insulin on a gold-coated copper oxide substrate (RSD = 1.69%, n = 3). Supplemental Figure S3b depicts the reproducible Raman spectra of three independent measurements of 50 pM reduced insulin on 3 independent substrates (RSD = 5.21%, n = 3). The high reproducibility in the Raman spectra of reduced insulin is attributed to the chemisorption of the protein molecules in a unified orientation onto the substrate, the presence of numerous hotspots on the substrate surface due to its high roughness, and the ability of the handheld Raman spectrometer to acquire average Raman spectra from all sites on the SERS substrate when operated in ROS mode.^3,20,21

Figure 5.

SERS spectra of reduced human insulin at different concentrations. The spectra were collected on nine independent gold-coated copper oxide substrates.

Recently, Cho et al. reported a method for the Raman detection of insulin where a gold-coated ZnO substrate was synthesized and utilized for the SERS screening of the protein.²⁵ The substrate was prepared using a hydrothermal method to grow ZnO nanowires on a Si wafer. The ZnO nanowires were then coated with gold nanostructures. The process was repeated five times to form dense Au–nanoparticle stacks in pillar forms and increase the uniformity and SERS activity of the substrate. Therefore, the substrate fabrication required several hours and multiple chemical processes, and the SERS measurement relied mainly on the EM enhancement provided by the substrate geometry. In the present work, we utilized an inexpensive and easy method to manufacture gold-coated copper oxide substrate and, instead of relying on the geometry of the substrate, used the protein’s own disulfide bond structure to achieve highly sensitive SERS measurements of insulin down to 10 zM (approximately ninefold lower than that demonstrated by Cho et al.). The chemisorption and oriented immobilization of the protein onto the gold-coated copper oxide substrate maximized the chemical and EM enhancement effects in the SERS measurement.

We have demonstrated functionalized gold nanomaterials for the selective extraction of proteins from blood plasma.^30,31 Therefore, by combining selective extractor nanomaterials with the new method for biomolecules, selective and label-free SERS screening of many proteins and disease biomarkers can be achieved for molecular diagnosis applications and biology research.

In conclusion, we demonstrated a proof of concept on a simple, reproducible, and ultrasensitive label-free SERS detection of insulin by using the protein’s own disulfide bond structure. The reduction of the disulfide bond structure of the protein allowed for its rapid chemisorption in a unified orientation onto a gold-coated copper oxide substrate via Au–S bond formation. This causes the biomolecules to form a charge transfer complex with the SERS substrate at a very short distance from the hotspots on the plasmonic surface of the substrate. Therefore, the Raman vibration modes of the immobilized protein experience maximum EM and chemical enhancement effects, and a dramatic increase in the protein Raman signal intensity is observed. Using this approach, reproducible SERS detection of insulin, down to 10 zM, was achieved. Since 65% of proteins have a disulfide bond molecular structure, the demonstrated method can be utilized for their label-free SERS determination at pathology labs, at points of care, and in biology research, especially when combined with a selective extraction method for the target protein.

Supplemental Material

DS_DISC875102 – Supplemental material for Toward Label-Free SERS Detection of Proteins through Their Disulfide Bond Structure

Supplemental material, DS_DISC875102 for Toward Label-Free SERS Detection of Proteins through Their Disulfide Bond Structure by Waleed A. Hassanain and Emad L. Izake in SLAS Discovery

Footnotes

Acknowledgements

The authors thank FLEW Solutions Pty Ltd Australia for donating gold-coated copper oxide substrates for this work.

Supplemental material is available online with this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Emad L. Izake

References

Aydin

A Short History, Principles, and Types of ELISA, and Our Laboratory Experience with Peptide/Protein Analyses Using ELISA. Peptides 2015, 72, 4–15.

Aebersold

Mann

Mass Spectrometry-Based Proteomics. Nature 2003, 422, 198–207.

Hassanain

W. A.

Izake

E. L.

Schmidt

M. S.

; et al. Gold Nanomaterials for the Selective Capturing and SERS Diagnosis of Toxins in Aqueous and Biological Fluids. Biosens. Bioelectron. 2017, 91, 664–672.

Yılmaz

F. M.

Çelebi

Yücel

Automated Turbidimetric Benzalkonium Chloride Method for Measurement of Protein in Urine and Cerebrospinal Fluid. Clin. Chem. 2004, 50, 1450–1452.

Daniels

J. S.

Pourmand

Label-Free Impedance Biosensors: Opportunities and Challenges. Electroanalysis 2007, 19, 1239–1257.

Ramachandran

Larson

D. N.

Stark

P. R. H.

; et al. Emerging Tools for Real-Time Label-Free Detection of Interactions on Functional Protein Microarrays. FEBS J. 2005, 272, 5412–5425.

Stern

Vacic

Rajan

N. K.

; et al. Label-Free Biomarker Detection from Whole Blood. Nat. Nanotechnol. 2010, 5, 138–142.

Demirel

Usta

Yilmaz

; et al. Surface-Enhanced Raman Spectroscopy (SERS): An Adventure from Plasmonic Metals to Organic Semiconductors as SERS Platforms. J. Mater. Chem. C 2018, 6, 5314–5335.

Park

W.-H.

Kim

Z. H.

Charge Transfer Enhancement in the SERS of a Single Molecule. Nano Lett. 2010, 10, 4040–4048.

10.

L.-J.

Zong

Zheng

X.-S.

; et al. Label-Free Detection of Native Proteins by Surface-Enhanced Raman Spectroscopy Using Iodide-Modified Nanoparticles. Anal. Chem. 2014, 86, 2238–2245.

11.

Freeman

L. M.

Pang

Fainman

Maximizing the Electromagnetic and Chemical Resonances of Surface-Enhanced Raman Scattering for Nucleic Acids. ACS Nano 2014, 8, 8383–8391.

12.

Ling

Xiao

; et al. Surface Enhanced Raman Spectroscopy on a Flat Graphene Surface. Proc. Natl. Acad. Sci. U.S.A. 2012, 109, 9281–9286.

13.

Kurouski

Washington

Ozbil

; et al. Disulfide Bridges Remain Intact While Native Insulin Converts into Amyloid Fibrils. PLoS One 2012, 7, e36989.

14.

Grönbeck

Curioni

Andreoni

Thiols and Disulfides on the Au(111) Surface: The Headgroup−Gold Interaction. J. Am. Chem. Soc. 2000, 122, 3839–3842.

15.

Iwase

Kobayashi

Nakajima

; et al. The Ratio of Insulin to C-Peptide Can Be Used to Make a Forensic Diagnosis of Exogenous Insulin Overdosage. Forensic Sci. Int. 2001, 115, 123–127.

16.

Goh

S.-Y.

Hussein

Rudijanto

Review of Insulin-Associated Hypoglycemia and Its Impact on the Management of Diabetes in Southeast Asian Countries. J. Diabetes Investig. 2017, 8, 635–645.

17.

Luchsinger

J. A.

Tang

M.-X.

Shea

; et al. Hyperinsulinemia and Risk of Alzheimer Disease. Neurology 2004, 63, 1187–1192.

18.

Shapiro

A. M.

Lakey

J. R.

Ryan

E. A.

; et al. Islet Transplantation in Seven Patients with Type 1 Diabetes Mellitus Using a Glucocorticoid-Free Immunosuppressive Regimen. N. Engl. J. Med. 2000, 343, 230–238.

19.

Papas

K. K.

Suszynski

T. M.

Colton

C. K.

Islet Assessment for Transplantation. Curr. Opin. Organ. Transplant. 2009, 14, 674–682.

20.

Balčytis

Ryu

Seniutinas

; et al. Black-CuO: Surface-Enhanced Raman Scattering and Infrared Properties. Nanoscale 2015, 7, 18299–18304.

21.

Hassanain

W. A.

Izake

E. L.

Ayoko

G. A.

Spectroelectrochemical Nanosensor for the Determination of Cystatin C in Human Blood. Anal. Chem. 2018, 90, 10843–10850.

22.

Drachev

V. P.

Thoreson

M. D.

Khaliullin

E. N.

; et al. Surface-Enhanced Raman Difference Between Human Insulin and Insulin Lispro Detected with Adaptive Nanostructures. J. Phys. Chem. B 2004, 108, 18046–18052.

23.

Kurouski

Postiglione

Deckert-Gaudig

; et al. Amide I Vibrational Mode Suppression in Surface (SERS) and Tip (TERS) Enhanced Raman Spectra of Protein Specimens. Analyst 2013, 138, 1665–1673.

24.

Podstawka

Ozaki

Proniewicz

L. M.

Adsorption of S–S Containing Proteins on a Colloidal Silver Surface Studied by Surface-Enhanced Raman Spectroscopy. Appl. Spectrosc. 2004, 58, 1147–1156.

25.

Cho

Kumar

Yang

; et al. Surface-Enhanced Raman Spectroscopy-Based Label-Free Insulin Detection at Physiological Concentrations for Analysis of Islet Performance. ACS Sens. 2018, 3, 65–71.

26.

Poon

K. W.

Lyng

F. M.

Knief

; et al. Quantitative Reagent-Free Detection of Fibrinogen Levels in Human Blood Plasma Using Raman Spectroscopy. Analyst 2012, 137, 1807–1814.

27.

Wang

Lin

; et al. Label-Free Detection of Serum Proteins Using Surface-Enhanced Raman Spectroscopy for Colorectal Cancer Screening. J. Biomed. Opt. 2014, 19, 087003.

28.

Kessler

Yamamoto

Bouř

Establishing the Link between Fibril Formation and Raman Optical Activity Spectra of Insulin. Phys. Chem. Chem. Phys. 2017, 19, 13614–13621.

29.

Stewart

Fredericks

P. M.

Surface-Enhanced Raman Spectroscopy of Amino Acids Adsorbed on an Electrochemically Prepared Silver Surface. Spectrochim. Acta A 1999, 55, 1641–1660.

30.

Agoston

Izake

E. L.

Sivanesan

; et al. Rapid Isolation and Detection of Erythropoietin in Blood Plasma by Magnetic Core Gold Nanoparticles and Portable Raman Spectroscopy. Nanomedicine 2016, 12, 633–641.

31.

Hassanain

W. A.

Izake

E. L.

Arumugam

; et al. An Electrochemical Biosensor for the Rapid Detection of Erythropoietin in Blood. Talanta 2018, 189, 636–640.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.34 MB