Polyethylenimine Modified Graphene-Oxide Electrochemical

Mar 8, 2018 - Department of Clinical Neurosciences, Hotchkiss Brain Institute, Alberta Children Hospital Research Institute for Child and Maternal Hea...
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Polyethylenimine Modified Graphene-oxide Electrochemical Immunosensor for the Detection of Glial Fibrillary Acidic Protein in Central Nervous System Injury Sultan Khetani, Vinayaraj Ozhukil Kollath, Varun Kundra, Minh Nguyen, Chantel Debert, Arindom Sen, Kunal Karan, and Amir Sanati-Nezhad ACS Sens., Just Accepted Manuscript • DOI: 10.1021/acssensors.8b00076 • Publication Date (Web): 08 Mar 2018 Downloaded from http://pubs.acs.org on March 10, 2018

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Polyethylenimine Modified Graphene-oxide Electrochemical Immunosensor for the Detection of Glial Fibrillary Acidic Protein in Central Nervous System Injury Sultan Khetania,c, Vinayaraj Ozhukil Kollathe, Varun Kundraa, Minh Dang Nguyenf, Chantel Debertg, Arindom Senb,c,d,e, Kunal Karane, Amir Sanati-Nezhada,b,c* a

BioMEMS and Bioinspired Microfluidic Laboratory, Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta T2N 1N4, Canada b Center for Bioengineering Research and Education, Schulich School of Engineering, University of Calgary, Calgary, Alberta T2N 1N4, Canada c Biomedical Engineering Graduate Program, University of Calgary, Calgary, Alberta T2N 1N4, Canada d Pharmaceutical Production Research Facility, Schulich School of Engineering, University of Calgary, Alberta T2N 1N4, Canada e Department of Chemical and Petroleum Engineering, University of Calgary, Calgary, Alberta T2N 1N4, Canada f Department of Clinical Neurosciences, Hotchkiss Brain Institute, Alberta Children Hospital Research Institute for Child and Maternal Health, University of Calgary, Calgary, Alberta T2N 1N4, Canada g Department of Clinical Neurosciences, Division of Physical Medicine and Rehabilitation, Foothills Medical Centre, University of Calgary, Calgary, Alberta T2H 2T9, Canada ∗ Corresponding author at: Department of Mechanical and Manufacturing Engineering, 2500 University Drive NW, Calgary, Alberta, Canada T2N 1N4 E-mail address: [email protected]

ABSTRACT: Glial fibrillary acidic protein (GFAP) is as an intermediate filament protein expressed by certain cells in the central nervous system (CNS). GFAP has been recognized as a reliable biomarker of CNS injury. However, due to the absence of rapid and easy-to-use assays for the detection of CNS injury biomarkers, measuring GFAP levels to identify CNS injury has not attained widespread clinical implementation. In the present work, we developed a polyethylenimine (PEI) coated graphene screenprinted electrode and used it for highly sensitive immunosensing of GFAP. Covalent binding of GFAP antibody to the PEImodified electrode surface along with electrochemical impedance spectroscopy were used for detecting the change in the electrical conductivity of the electrodes. A highly linear response was recorded for various GFAP concentrations. Quantitative, selective, and label-free detection was achieved in the dynamic range of 1 pg mL−1 – 100 ng mL−1 for GFAP spiked in phosphate buffer saline, artificial cerebrospinal fluid, and human blood serum. The performance of the immunosensor was further validated and correlated by testing samples with the commercially available enzyme-linked immunosorbent assay method. This functionalized electrode could be used clinically for rapid detection and monitoring of CNS injury. Keywords: Central nervous system (CNS) injury; Glial fibrillary acidic protein (GFAP); Biomarkers; Graphene electrode; Polyethylenimine; Immunosensor; Electrochemical impedance spectroscopy (EIS) Abbreviations: fg: Femtogram, pg: Picogram, ng: Nanogram, mL: millilitre, SI: Supplementary Information Central nervous system (CNS) injuries affect over 20 million individuals globally.1-3 The pathophysiology of these complicated injuries can be categorized as primary and secondary. Direct mechanical impact loading causes primary contusions, lacerations, and damage to the tissue due to shearing. In response to a primary injury, a series of biochemical, cellular and physiological processes can subsequently trigger a secondary injury process that can contribute to additional tissue damage, and even cell death.4-5 A delay in diagnosis and treatment may contribute to injury progression and eventually lead to debilitating outcomes. Thus, it is recommended that wounded individuals reach an acute care facility within two hours of being injured, and undergo screening processes designed to identify secondary injuries. However, even in the best care facilities, there is a limited availability of reliable tools for rapid and continuous monitoring of brain injuries, and an absence of sensor technology for secondary injury detection.6-7 Thus, there is an urgent need to identify and develop new ways to detect, monitor and treat CNS injuries.1, 8-9 One alternative approach to conventional techniques for the diagnosis of brain injury is the detection of injury-related biomarkers released by different cells of the CNS.10 Changes in the concentrations of released proteins and nucleic acids in biofluids such as blood, urine and cerebrospinal fluid after the CNS injury have brought enormous understanding of the 1

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pathophysiology of CNS injury.4, 10-14 It is well known that the concentration of glial fibrillary acidic protein (GFAP), an intermediate filament (IF) protein expressed by astrocytes in the brain, increases after CNS injuries.6 Conventional methods for the detection of GFAP are enzyme-linked immunosorbent assays (ELISA) and western blot techniques.4, 15 However, these techniques rely on fluorescent labels, with laborious and time-consuming processes in sample preparation and detection, and thus, are not preferred for rapid and continuous detection of changes in biomarkers.16 To address these issues, electrochemical immunosensors offer faster analysis with a linear response proportional to the concentration of biomarkers.17-21 Detection of brain injuries using biosensors capable of monitoring injury biomarkers has recently generated a great deal of interest.22-23 Biosensors capable of detecting CNS injury biomarkers require a highly conductive substrate functionalized with a highly sensitive, but a simple manufacturing protocol. A variety of different metallic and non-metallic substrates such as gold, carbon nanotubes, graphene and cellulose papers have been employed for electrochemical sensing.24-28 Graphene, in particular, has become highly popular because of its excellent material properties. The interesting properties of graphene sheet such as high surface area, high carrier-density dependent electron mobility, and superior electrical conductivity, are some of the key attractions for developing graphene-based biosensors.24, 29-33 However, the existing graphene modification techniques such as creation of self-assembled monolayers (SAM), electro-polymerization, plasma-polymerization, and salts with functional groups, have complex protocols with several time-consuming functionalization steps. This makes the use of biosensors challenging for routine clinical detection of patient samples. Also the modification of the graphene surface has been difficult due to the reaction occurring at the edges, and defects are introduced only by functionalizing the surfaces such that it allows binding of biomolecules.34-35 These challenges can be addressed through the development of faster, yet still reliable, graphene electrode functionalization techniques.36-37 In this work, we created branched polyethylenimine (PEI) with numerous primary and secondary amine functional groups over an easy to handle form of graphene screen-printed electrodes (GSPE) for highly sensitive and selective detection of GFAP in different biofluids. PEI showed stability at room temperature, easily adsorbed onto graphene surfaces, and rapidly rendered reduction to Schiff’s base reaction by glutaraldehyde, thereby making it a superior candidate for rapid functionalization of graphene. GFAP samples were prepared with varying concentration in phosphate buffer saline (PBS), artificial cerebrospinal fluid (aCSF), and human blood serum. Using an [Fe(CN)6]3/-4 redox probe as the detection assay, electrochemical impedance spectroscopy (EIS) was performed on the modified electrode surface of the immunosensor for the detection of GFAP (Figure. 1). Owing to the sensitive material and simple functionalization technique, the immunosensor was found to be functional within the physiologically-relevant concentration of 0.03 ng mL−1 prior the injury, and 1.5 ng mL−1 detected after trauma brain injury (TBI) and 20 ng mL−1 after SCI injury in serum.38-40 This rapid and highly sensitive and selective GFAP immunosensor can serve as an effective tool for rapid detection, diagnosis and monitoring of CNS injuries.

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Figure 1. The schematic representation of the modification of a graphene electrode surface, sample collection, and electrochemical detection of glial fibrillary acidic protein (GFAP): (A) Blood collected from central nervous system (CNS) injury patient, or samples are prepared in artificial cerebrospinal fluid and in blood serum, (B) Stages of surface modification for binding the GFAP antibody to the functionalized graphene electrode. (i) Bare graphene electrode, (ii) Sodium hydroxide (NaOH) treatment for creating hydrophilic surface, (iii) Functionalization of polyethylenimine (PEI), (iv) Activation of the surface with glutaraldehyde, (v) Schiff base, (vi) immobilization of GFAP antibody, (vii) Blocking unbounded sites, and (viii) Immunosensor ready for the detection, (C) Detection of electrochemical impedance spectroscopy (EIS) response of the immunosensor for GFAP detection.

EXPERIMENTAL SECTION Methods GSPE Surface modification The materials and instruments used for modifying the GSPEs to an immunosensor are listed in S1 A and B. All abbreviated terms related to the materials used in this work are defined in the Supplementary section. The hydrophobic surface of a GSPE electrode was treated with 100 µL of 1 M NaOH and incubated for 30 min to render it hydrophilic. The electrode surface was cleaned with DI water to remove residual unbound ions. To determine the concentration of PEI for functionalization of the electrode, four electrodes were treated with 100 µL of 0.5%, 1%, 2%, and 5% PEI concentrations (vol %) dissolved in DI water and incubated on the GSPE surface for 30 min. The coated GSPE was then incubated followed by rinsing with DI water three times to clean and remove unbound PEI from the surface. The electrode was further activated by adding 100 µL of 2.5% glutaraldehyde in DI water and incubated for 30 min as previously described.26 The activated surface forms Schiff base which allowed the immobilization of 50 µL of 50 µg mL−1 antibody diluted in PBS. After incubating antibody for 45 min at room temperature and cleaning with PBS, the electrode surface was incubated for 30 min with 100 µL of 1% BSA prepared in PBS to block unspecific binding on the surface. The immunosensor was then rinsed with PBS and subjected to testing with different concentrations of GFAP in biofluids. GFAP Binding GFAP binding onto the immunosensor was achieved by adding 50 µL of GFAP antigen solution over the working electrode. Concentrations of GFAP ranging from 100 fg mL −1 – 1 µg mL−1 were prepared by serially diluting GFAP in PBS, aCSF or human blood serum. About 50 µL of the solution was incubated for 30 min to allow binding with the immunosensor. The surface of the immunosensor was then rinsed with PBS before measuring EIS in the presence of a redox probe. Protocols for separation of serum from blood and preparation of aCSF Blood from healthy human donors was used for preparing GFAP solutions in human serum. Blood samples were acquired under University of Calgary ethics number #REB15-2138. Whole blood was allowed to clot in a 5 mL Eppendorf tube at room temperature for 30 min and then centrifuged at 1000 relative centrifugal force (RCF) for 5 min. Clots settled at the bottom of the tube after centrifugation, allowing the separation of serum. Serum was collected in a tube and stored at -80 oC. The protocol described in our previous work26 was used to prepare aCSF, followed by adding 128 mM sodium chloride (NaCl), 4 mM potassium chloride (KCl), 1.5 mM calcium chloride (CaCl 2), 1 mM magnesium sulphate (MgSO4), 0.5 mM disodium phosphate (Na2HPO4), 21 mM sodium hydrogen carbonate (NaHCO 3), and 30 mM d-glucose in DI water at room temperature. The solution was then stirred at 200 rpm using a magnetic stirrer for 15 min and gassed with carbogen (95% O 2, 5% CO2) for 30 min to allow for saturation of gases. pH of the solution was adjusted to 7.4 by adding NaOH or HCl. Electrochemical measurements EIS analysis was performed in triplicate on each sample in the presence of 5.0 mM K[Fe(CN)6]3/-4 prepared using 5.0 mM of K[Fe(CN)6]3 and 5.0 mM of K[Fe(CN)6]4 in PBS of pH 7.4. For measuring impedance response, EIS scan with a standard potential of +0.1V using a sinusoidal perturbation of amplitude 100 mV was applied. Each scan was performed between the frequency range 0.05 Hz – 500 KHz. The total impedance value is a combination of the redox impedance (R1) and the impedance due to the surface modification resulting in a double layer capacitor (C2) and polarization resistance (R2). Data was fitted to a [R1 + (C2/R2)] equivalent circuit, using the EC-Lab Software. Response of the immunosensor for varying concentrations of GFAP was assessed by EIS measurements. The Limit of Detection (LOD) of the immunosensor was obtained for the concentration of GFAP at which the signal recorded for the negative control or BSA did not overlap. Validation of the GFAP immunosensor Standard ELISA technique was selected for evaluating the performance of the immunosensor. Eight samples with unknown or blind concentrations, four of each in aCSF and blood serum, were prepared by drawing out unknown volumes of GFAP from a 100 ng mL−1 GFAP stock and adding it to 1 mL of aCSF and serum. A 96 well ELISA plate was coated with GFAP antibody according to the vendor’s protocol. Solutions of seven standard concentrations: 0 ng mL−1, 0.3125 ng mL−1, 0.625 ng mL−1, 3

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1.25 ng mL−1, 2.5 ng mL−1, 5 ng mL−1, 10 ng mL−1, and 25 ng mL−1 were prepared by serially diluting standard solution in the dilution buffer. 100 µL of each dilution buffer used as a blank, standard solutions, quality controls, and blind samples were incubated for 2 hrs on an orbital microplate shaker at room temperature. A 96-well plate was washed three times with washing buffer. 100 µL of biotin labelled monoclonal anti-human GFAP antibody was added into each well. After incubating the ELISA plate for 1 hr and washing all the wells, 100 µL of streptavidin-HRP conjugate was added to each well and incubated for 30 min. 100 µL substrate solution was added to react the streptavidin-HRP conjugate. The reaction was stopped by adding 100 µL acidic stop solution and measuring the optical absorbance of the reaction at 450 nm and 570 nm under the plate reader. Vibrational spectroscopy The FTIR spectra of the working electrode and the respective surface modifications were recorded using an attenuated total reflectance (ATR) module equipped with a Germanium crystal. The details of the measurement are given elsewhere.41 Briefly, ATR-FTIR spectra were recorded in the range 4000 – 600 cm-1 using a mid-IR KBr-DTGS detector operating at room temperature. A new background spectrum was recorded before running each sample. Spectra were signal averaged from 32 scans at 4 cm-1 resolution. Raman spectra were recorded from 0 to 3700 cm−1 on a Witec alpha 300 R Confocal Raman Microscope using a 532-nm laser. The typical integration time of acquisition was 30 – 60 s. Measurement of surface morphology and contact angle The morphology of the working electrode before and after coating with PEI and modifying with GFAP were recorded using acoustic mode AFM. In acoustic mode scanning, the surface topography is recorded in a non-contact mode while the cantilever is vibrated using a sinusoidal wave with a frequency near the resonance frequency of the cantilever. The Si 3N4 cantilever with a resonance frequency of 132 kHz was scanned over the surface when its actual amplitude of vibration is dampened to 90% of the initial value. Topography, amplitude and phase channels were recorded at 256 points/line at a scan rate of 0.4 line/s. All samples reported were scanned using the same cantilever to avoid tip shape artefacts. Post-measurement image analyses were performed using WSxM 5.0 software.42 Water (MilliQ, 18.2 MΩ at 25 °C) contact angles of pre- and post-treated graphene electrodes were measured using a goniometer equipped with a video camera and a light source. Contact angles of both left and right sides of the sessile drop were calculated by the software (DROPimage v2.7.03) and averaged from 10 measurements at 1 second intervals. On the hydrophilic surface, the image capture interval was also shortened to capture the temporal behaviour of the water drop.

RESULTS AND DISCUSSION Characterization of the GFAP immunosensor Modification on the graphene surface was determined by characterizing the change in the electron transfer properties in the presence of a [Fe(CN)6]3/-4 redox probe. The response of the electrode/electrolyte system was recorded as Nyquist plots with an area plot of the imaginary component (Z″) of the impedance against the real component (Z′) (Figure. 2A). Interface properties are represented as the overall impedance offered by the immunosensor or the charge transfer resistance (Rct) after modification stages and due to binding between GFAP antibody and GFAP. This is shown as semi-circular output obtained from the EIS of the immunosensor (Figure. 2A) EIS spectra were recorded after the following stages of the immunosensor development: (a) cleaned bare graphene electrode; (b) 1% PEI immobilized electrode; (c) the electrode surface activated by 2.5% GA; (e) immobilization of GFAP antibody; (f) blocking the surface with BSA; and finally (g) incubation with GFAP protein. Bare graphene surface showed a rapid electron transfer with Rct = 837.33 Ω. The increase in Rct indicated the binding on the electrode surface and the conductive nature of the material. PEI offered a slightly higher Rct than that of the bare graphene at 937.95 Ω which indicates that the lower electrical conductivity of PEI than that of graphene impeding the electron transfer process. Antibody immobilized post activation of the electrode surface with GA showed further increase of the Rct to 1088.5 Ω which also confirms the successful covalent binding of GFAP antibody to the surface. Rct increases to 1831.82 Ω after adding BSA onto the graphene surface modified with PEI and antibody. This increase in Rct is related to relatively less conductive nature of BSA compared to PEI, which further blocks the electron transfer to the immunosensor. Addition of GFAP further increases Rct due to the binding between the anti-GFAP antibody and GFAP resulting in formation of a dense layer on the immunosensor. The increase in the Rct suggests further blocking of the electron exchange between the redox probe and the electrode, leading to a decreased electron transfer rate. It is evident from the characterization plots that Rct increases with the modification of the surface and continues increasing the concentration of GFAP as it affects the electrode resistance – which is likely a combination of chargetransfer and mass transport resistances. The EIS spectra also validates the completion of surface modification and demonstrates the reliability of the graphene immunosensor for detecting GFAP.

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Figure 2. Characterization of the GSPE after functionalization stages. (A) EIS Spectra after each stage of the electrode surface modification and in the presence of [Fe(CN)6]3/-4 redox probe. Nyquist plot is shown in increasing order for (a) blank electrode, and after adding (b) PEI, (c) antibody, (d) bovine serum albumin (BSA) and (e) GFAP. (B) Attenuated total reflectance (ATR)-FTIR spectra of the blank electrode and 1% and 5% PEI-treated electrode.

Qualitative analysis of the immunosensor by Raman and FTIR spectroscopy Vibrational spectra obtained from Raman spectroscopy helped in confirming the functionalization of the electrode. Figure. S2 shows the Raman spectra of the working electrode and the consecutive modifications. The major bands of graphene with peaks at 1353, 1585 and 2723 cm-1 are known as the D-band, G-band, and 2D-band (first overtone of D-band), respectively (Figure. S2: A & B).43 The G band corresponds to the vibration of sp2 bonded carbon atoms in the graphene hexagonal lattice and the D band arises from the disorder induced by sp3 bonded carbon atoms. The ratio of intensities of D to G band (ID/IG) shows the degree of disorder on the graphene with various surface treatments. Compared to the bare working graphene electrode, each modification steps resulted in a progressively higher value for the ID/IG ratio, which indicates modification not only of the surface but also of the bulk graphene material. The NaOH treatment did not cause a significant peak shift to the major bands as expected.44 After PEI modification, Raman spectrum showed distinct bands of PEI which overlaps the characteristic bands of bare graphene working electrode.45 This confirmed the presence of PEI after the deposition process. FTIR spectra of bare and PEI modified working electrode are shown in Figure. 2B. FTIR performed on the coated GSPE showed that 0.5% PEI concentration was not detectable. However, 1%, 2% and 5% PEI concentrations were detectable, although the latter two concentrations (2% and 5%) remained in a viscous form. Therefore, 1% PEI concentration was deemed optimal for functionalizing the GSPE. Due to the roughness of the graphene electrode, the noise on the ATR-FTIR spectrum was high. However, some characteristic bands were visible in the range 1800 – 1300 cm-1. These bands are an indication for the stretching vibrations of C-O and C=O as well as the –OH vibrations. After PEI modification, typical bands of primary and secondary amide vibrations appear in the spectrum.46 In addition, the symmetrical and asymmetrical stretching vibrations of CH are visible in the PEI/G spectrum. Higher intensity vibrational bands of PEI are visible in the spectrum recorded from a 5% PEI gel treated electrode. The FTIR results complement the Raman spectra, confirming the PEI modification of the GSPE electrodes. Atomic Force Microscopy and Contact angle measurements Change in the topography due to functionalization of the electrode surface was measured by AFM. Figure. 3 shows the AFM topography images of bare graphene working electrode (Figure. 3A) as compared to the PEI modified (Figure. 3B) and with GFAP antibody adsorbed (Figure. 3C) - recorded in acoustic mode. The bare working electrode shows the presence of graphene sheets of several layers in thickness with sharp edges. NaOH-treated electrodes do not show any significant difference in the morphology. However, the water contact angle results showed the conversion of hydrophobic graphene surface (81.39 ± 0.09) to hydrophilic (14.25 ± 0.28) through NaOH treatment (Figure. S1). After PEI treatment, the boundaries of the graphene grains diminish in sharpness, indicating the PEI blanket covering the surface. GFAP antibody-treated samples show a complete 5

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coverage of the electrode with a rougher morphology due to the binding of GFAP antibody to the surface. The RMS roughness values of the GSPE, PEI modified GSPE and after antibody adsorption are 4.61 nm, 11.04 nm, and 20.87 nm, respectively.

Figure 3. Atomic force microscopy (AFM) images of the electrodes. (A) Bare working electrode, (B) PEI-modified, and (C) GFAP antibody adsorbed. Electrochemical detection of GFAP Limit of detection of the immunosensor To test the operational limits of the immunosensor, GFAP concentrations of 0.1 pg mL−1 to 106 pg mL−1 were spiked in PBS. For GFAP concentration of 0.1 pg mL−1, Rct of the BSA immobilized surface or the negative control, and Rct of 1 fg mL−1 coincided with each other and were observed to be 1831.82 ± 5.73 Ω and 1839.45 ± 6.73 Ω, respectively. (Figure. 4). However, a distinctive EIS response was detected for GFAP concentrations between 1 pg mL−1 to 105 pg mL−1. ∆Rct for the concentrations tested were as follows: for 1 pg mL−1, ∆Rct 159.22 ± 4.77 Ω; 101 pg mL−1, ∆Rct 242.15 ± 7.26 Ω; 102 pg mL−1, ∆Rct 332.87 ± 9.98 Ω; 103 pg, ∆Rct 443.95 ± 13.32 Ω; 104 pg, ∆Rct 508.63 ± 11.26 Ω; 105 pg, ∆Rct 550.67 ± 13.51 Ω. ∆Rct of 106 pg mL−1 (1 µg mL−1) was determined to be 551.73 ± 17.42 Ω, overlapping with the signal of 100 ng mL−1. Therefore, the maximum detectable concentration limit of the immunosensor was considered to be 105 pg mL−1. These lower and upper detection thresholds of 1 pg mL−1 and 105 pg mL−1 were considered as the detection limits of the immunosensor. This detection range was used as the reference for testing the concentrations of GFAP spiked in aCSF and serum. Given the fact that the physiologically-relevant range of GFAP before and after the CNS injury is within the range of 0.03 ng mL−1 to 1.5 ng mL−1, the immunosensor is practical for screening GFAP released after CNS injury. A

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Figure 4. Electrochemical sensing of GFAP. (A) Electrochemical impedance spectroscopy (EIS) of the immunosensor with different concentrations of GFAP in the increasing order of concentrations: (a) BSA / 0 pg mL−1 (negative control), (b) 0.1 pg mL−1, (c) 1 pg mL−1, (d) 10 pg mL−1, (e) 102 pg mL−1, (f) 103 pg mL−1, (g) 104 pg mL−1, (h) 105 pg mL−1, and (i) 106 pg mL−1. (B) Linear relationship is derived by taking the difference between the Rct of BSA and Rct of each concentration tested (∆Rct). Detection of GFAP 6

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The detection limit of the immunosensor from 1 pg mL−1 to 105 pg mL−1 was used to measure the response of the sensor to GFAP prepared in different test biofluids. GFAP samples were prepared with concentrations of 1 pg mL−1 to 105 pg mL−1 in PBS, aCSF and serum, and followed by EIS measurements in the presence of [Fe(CN)6]3/-4 redox probe (Figure. 5). With the increase in GFAP concentration, the corresponding increase in the impedance was detected by the immunosensor. To assess the relationship between the concentration of GFAP and the impedance, the difference between Rct 0 due to the negative control (Rct after BSA immobilization) and the Rct' due to the GFAP concentration was determined. A linear regression relationship of Y= 90.094 (X) – 42.164 with the R² of 0.97 was obtained where ‘Y’ represents ∆Rct and ‘X’ represents the logarithm of concentration of GFAP present in the sample (Figure. 5A). For the GFAP samples prepared in serum, a linear relationship of Y= 117.76 (X) + 21.929 was obtained with the R² of 0.987 (Figure. 5B). Finally, an equally sensitive response compared to PBS and serum was detected for GFAP samples prepared in aCSF, in which a linear relation of Y= 136.24 (X) + 23.84 and R2 of 0.974 (Figure. 5C) was detected. Every point in the linear relationship plot represents an average of three independent measurements and the error bar represents the standard error of the mean. The error of the mean for all measurements was between 3.693Ω – 19.64 Ω and correlation coefficients (R2) ranged between 0.97-0.96, which demonstrates the stable performance of the immunosensor. A

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Figure 5. The response of the immunosensor for label-free detection of different concentrations of GFAP prepared in (A) PBS (B) serum, and (C) aCSF. A linear response of the immunosensor was recorded for GFAP concentration between 1 pg mL −1 to 105 pg mL−1 in these three different biofluids. Selectivity performance of the immunosensor Selectivity tests were performed to ascertain the response of the immunosensor in the presence of several other cellular and enzymatic biomarkers overexpressed simultaneously along with GFAP after the CNS injury.4 The immunosensor was tested for selective performance in the presence of GABA (GA), Glutamate (Glu), NMDA (NM), and S100β along with GFAP (Figure. 6). The selective performance of the immunosensor was examined by measuring the difference between Rct due to the sample tested (Rct’’) and Rct due to the negative control (Rct0). The GFAP concentration of 1 ng mL−1 in PBS resulted in a mean Rct of 1824.89 Ω (n=3), and the GFAP concentration tested along with abovementioned biomarkers was 1833.61 Ω (n=3). The difference between Rct’’ and Rct0 was 477. 85 Ω with 3% standard error of the mean (n=3) for GFAP alone, and 486.57 Ω with 4.26% standard error of the mean (n=3) for GFAP with other biomarkers. This difference was nearly 5 times higher than the test for the mix of all biomarkers together except GFAP, and nearly 8 times higher for samples spiked with NM, GA, Glu, and S100β in PBS (Figure. 6A). The immunosensor performance was also highly selective in similar tests performed with samples prepared in human aCSF and serum. The difference between Rct'’ and Rct0 for GFAP samples tested in serum is 634.97 Ω with 5.04% standard error of the mean (n=3), and in aCSF is 629.28 Ω with 5.97% standard error of the mean (n=3). This detection was at least 6 times higher than the nearest detection due to a mix of biomarkers without GFAP in human serum and 7 times higher in aCSF (n=3) (Figure. 6B, C).

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Figure 6. Selectivity of the immunosensor tested in the presence of different biochemicals found after CNS injury. ΔRct detected after immobilization of biochemicals NDMA, GABA, Glutamate, S100β, and GFAP prepared in (A) PBS, (B) serum, and (C) aCSF, tested in the presence of [Fe(CN)6]3/-4 redox probe. Reproducibility of the Immunosensor Immunosensor was tested for inter-electrode reproducibility by performing five independent measurements of 10 3 pg mL−1 GFAP spiked in PBS. Response of the electrodes was found consistent and showed a relative standard deviation of 4.5% (n=3). This indicates stable surface chemistry and the reproducibility of the immunosensor for the detection of GFAP. Performance of the immunosensor versus ELISA The performance of the immunosensor was compared to the ELISA method for testing triplets of four samples of unknown GFAP concentration prepared in aCSF and serum. The results obtained from the immunosensor and ELISA are shown in Table 1, confirming the existence of a correlation between the performances of the immunosensor and the ELISA technique (SI 1 in Tables S1, and S2). The results suggest that the immunosensor is equally sensitive and selective as ELISA, and could be used as an alternative to the existing ELISA method for the detection of GFAP. Overall, the development of this immunosensor technology represents an important step toward the establishment of biosensors for diagnosis and treatment of CNS trauma. Table 1. Comparison between the performance of ELISA and the immunosensor for the detection of GFAP in aCSF and serum. Immunosensor (pg mL−1) 22,551 ± 1,108.51 603 ± 5.77 Immunosensor (pg mL−1) 41,913 ± 717.64 1,537.50± 124.09

Blind Samples in aCSF Sample 1 Sample 2 Blind samples in serum Sample 1 Sample 2

ELISA (pg mL−1) 23,620 ± 1,376.98 620 ± 8.66 ELISA (pg mL−1) 42,455 ± 1,091.192 1,405 ± 2,05.061

CONCLUSIONS The GSPE electrode functionalized with PEI reported in this work is an alternative to overcome the label-free diagnostic bottleneck for developing a sensitive and reliable immunosensor. We were able to successfully immobilize the GFAP antibody on the GSPE functionalized electrode for detecting GFAP antigens in complex biofluids. The GFAP immunosensor, validated by ELISA, offers a detection limit well positioned within the physiological concentration of GFAP found in serum before and after the CNS injury. This development represents a greater possibility to offer a diagnostic solution for the increasing number of CNS injuries. The present work also demonstrates the development of a simpler and faster electrode functionalization protocol compared to the previously reported works without compromising the detection limit and analytic range of detection. Moreover, the immunosensor could also detect GFAP spiked in three different media within 45 min compared to an ELISA assay which takes about 3-5 hrs for assay preparation and detection time. The immunosensor developed by a simple functionalization protocol can be further used for detecting other clinically relevant biomarkers to meet the clinical detection needs. Such an immunosensor can address the unmet diagnostic needs in resource-limited clinics, rural healthcare setups, emergency vehicles, and on war fields. It can also be used for priority-based injury diagnosis in clinics and hospitals, providing primary interventions, injury assessment and prognosis. This simple-to-use, fast acting sensor for detecting GFAP is another step closer to contributing to the growing field of the use of fluid biomarkers A

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for determining CNS injury and prognosis. To provide an accurate diagnosis and follow the progression of a specific CNS injury over time, the detection of a cohort of biomarkers in body fluids will be required. Future direction of this work will be to develop a biosensor capable of detecting the cohort of biomarkers.

ASSOCIATED CONTENT Supporting Information The supporting information is available free of charge on the ACS publication website at DOI: 00.000./acssensors.0000. Materials (chemical, reagents, and instruments), water contact angle of the blank and NaOH treated electrode, Raman spectra and ID/IG ratios of the working electrode after surface modification steps, detection of GFAP biomarker with ELISA and immunosensors, and comparison between the performances of different immunosensors developed for detecting GFAP are listed in the supporting information file.

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]. Tel.: +01(403) 220-7708. Notes The authors declare no competing financial interest.

ACKNOWLEDGEMENTS The authors acknowledge Natural Sciences and Engineering Research of Canada (NSERC); Alberta Prion Research Institute (APRI), CMC – Microsystems, Canada; and Alberta Innovates BioSolution (AIBS) for supporting this research. Vinayaraj Ozhukil Kollath acknowledges University of Calgary for Eyes High Postdoctoral Scholarship. We would also like to thank Farbod Sharif, Ehsan Hosseini and Udit Shrivastava for inputs and suggestions for this work.

REFERENCES 1. 2.

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41. Kollath, V. O.; Chen, Q.; Mullens, S.; Luyten, J.; Traina, K.; Boccaccini, A. R.; Cloots, R., Electrophoretic deposition of hydroxyapatite and hydroxyapatite–alginate on rapid prototyped 3D Ti6Al4V scaffolds. Journal of Materials Science 2016, 51 (5), 2338-2346. 42. Horcas, I.; Fernández, R.; Gomez-Rodriguez, J.; Colchero, J.; Gómez-Herrero, J.; Baro, A., WSXM: a software for scanning probe microscopy and a tool for nanotechnology. Review of Scientific Instruments 2007, 78 (1), 013705. 43. Elias, D. C.; Nair, R. R.; Mohiuddin, T.; Morozov, S.; Blake, P.; Halsall, M.; Ferrari, A.; Boukhvalov, D.; Katsnelson, M.; Geim, A., Control of graphene's properties by reversible hydrogenation: evidence for graphane. Science 2009, 323 (5914), 610-613. 44. Wang, Y.; Alsmeyer, D. C.; McCreery, R. L., Raman spectroscopy of carbon materials: structural basis of observed spectra. Chemistry of Materials 1990, 2 (5), 557-563. 45. Lu, H.; Zhang, A.; Zhang, Y.; Ding, L.; Zheng, Y., The effect of polymer polarity on the microwave absorbing properties of MWNTs. RSC Advances 2015, 5 (80), 64925-64931. 46. Ozhukil Kollath, V.; De Geest, B. G.; Mullens, S.; De Koker, S.; Luyten, J.; Persoons, R.; Traina, K.; Remon, J. P.; Cloots, R., Systematic processing of β‐ Tricalcium phosphate for efficient protein loading and in vitro analysis of antigen uptake. Advanced Engineering Materials 2013, 15 (4), 295-301.

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(A)

(B) NH₂

N

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NH

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NH

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H

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1% PEI

NaOH

H O

Cross linking PEI

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2.5% glutaraldehyde

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N C CH₂ CH₂ CH₂ C N C CH₂ CH₂ CH₂ C N OH N

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GFAP binding

OH N

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CH₂ CH₂ CH₂ C N

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GFAP antibody immobilization 50µg mL-1

CNS Injury Patient Sample

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