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. 2021 Jun 11;6(24):16076–16085. doi: 10.1021/acsomega.1c01959

In Silico and Electrochemical Studies for a ZnO–CuO-Based Immunosensor for Sensitive and Selective Detection of E. coli

Summaiyya Khan †, Akrema †, Sahar Qazi §, Rafiq Ahmad ‡, Khalid Raza §, Rahisuddin †,*
PMCID: PMC8223399  PMID: 34179653

Abstract

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Escherichia coli is a harmful Gram-negative bacterium commonly found in the gut of warm-blooded organisms and affects millions of people annually worldwide. In this study, we have synthesized a ZnO–CuO nanocomposite (NC) by a co-precipitation method and characterized the as-synthesized NC using FTIR spectroscopy, XRD, Raman spectroscopy, and FESEM techniques. To fabricate the immunosensor, the ZnO–CuO NC composite was screen-printed on gold-plated electrodes followed by physisorption of the anti-LPS E. coli antibody. The biosensor was optimized for higher specificity and sensitivity. The immunosensor exhibited a high sensitivity (11.04 μA CFU mL–1) with a low detection limit of 2 CFU mL–1 with a redox couple. The improved performance of the immunosensor is attributed to the synergistic effect of the NC and the antilipopolysaccharide antibody against E. coli. The selectivity studies were also carried out with Staphylococcus aureus to assess the specificity of the immunosensor. Testing in milk samples was done by spiking the milk samples with different concentrations of E. coli to check the potential of this immunosensor. We further checked the affinity between ZnO–CuO NC with E. coli LPS and the anti-LPS antibody using molecular docking studies. Atomic charge computation and interaction analyses were performed to support our hypothesis. Our results discern that there is a strong correlation between molecular docking studies and electrochemical characterization. The interaction analysis further displays the strong affinity between the antibody–LPS complex when immobilized with a nanoparticle composite (ZnO–CuO).

1. Introduction

Harmful pathogenic bacteria cause a variety of diseases in humans and may be naturally present in food and water. E. coli causes urinary tract infections, diarrhea, neonatal meningitis, and bacteremia and affects millions of people worldwide.1 The consumption of contaminated food products primarily causes intestinal infection in which a person suffers from abdominal pain, fever, and diarrhea. Sometimes, it leads to renal failure or severe dehydration. Food safety and public health issues require rapid, specific, and selective detection of pathogens. There are known methods for the detection of bacteria such as the polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA), which are slow, expensive, and cannot be used on site.2 Thus, there is a need for biosensors that are simple, sensitive, low cost, and can be used by untrained personnel. An impedance-based biosensor for the detection of E. coli (O157:H7) using dose and time response was studied.3 A linear detection range of 2.5 × 104 to 2.5 × 107 CFU mL–1 was reported. Antimicrobial peptides were also exploited in the impedance-based biosensor for the detection of E. coli.4 Later on, the DNA-based sensor based on surface-enhanced fluorescence was reported for the detection of E. coli (O157:H7) using Au@Ag nanorods.5 The DNA-based sensor performed in a linear range of 10–17–10–11 M and with a 3.33 × 10–18 M detection limit. Another research group reported6 a novel and cheap amperometric immunosensor based on functionalized four-layer magnetic nanoparticles. The linear range of heat-killed E. coli (O157:H7) was found from 3.6 × 103 to 3.6 × 106 CFU mL–1. Fang et al. reported an effective way to prepare a reagent-less electrochemical biosensor based on thionine-wrapped E. coli and a chitosan-trapped carbon nanodot film modified by a glassy carbon electrode.7

In the past two decades, electrochemical-based biosensors have shown great promise in the development of rapid methods for the detection of food-borne pathogens. Immobilization of biomolecules on the transducer surface is considered necessary for the fabrication of biosensors. A recent study reported NC of well-dispersed gold nanoparticles (Au NPs) on the surface of polypyrrole-reduced graphene oxide for the enzyme-free detection of E. coli K12.8 The enzyme-free sandwiched immunosensor showed excellent analytical performance. The linear range of detection was found to be 1.0 × 101 to 1.0 × 107 CFU mL–1, and the limit of detection was 10 CFU mL–1. Reduced graphene oxide/polyethylenimine functionalized with antifimbrial E. coli antibodies was used for selective and sensitive detection of uropathogenic E. coli (UPEC) in serum samples using gold electrode (Au–SPE) modifications.9 Impedimetric biosensor fabrication was based on using nanomaterials to modify the electrode surfaces to enhance the electrode properties, which received considerable attention.10,11

Au NPs opened new prospects for impedance-based biosensors due to their unique properties as a nanomaterial.12,13 Later on, Au NPs deposited on a paper electrode, modified with graphene oxide, for physisorption of a polyclonal antibody were reported for the detection of E. coli with an LOD of 150 CFU mL–1.14 An impedimetric E. coli sensor using a biotinylated antibody tethered to a neutravidin self-assembled monolayer (SAM) on a planar gold surface with 107 CFU mL–1 of LOD was also reported. An LOD of 1–2 CFU mL–1 using an E. coli antibody bound to 11-mercaptoundecanoic acid SAM on a planar gold electrode and a methoxysilane-modified planar ITO electrode was also reported.15−17 An LOD of 10 CFU mL–1 for E. coli O157:H7 using a methoxysilane-modified alumina nanoporous membrane for antibody immobilization was reported.17 A fluorescent magnetic biosensor based on DNAzyme was fabricated for the detection of E. coli O157:H7. The biosensor indicated a good linear range from 10 to 1000 CFU mL–1. This sensor is feasible for the detection of E. coli in drinking water and apple juice.18 A dual-walker-strategy-based electrochemical sensor for the detection of E. coli O157:H7 DNA was also reported. This fabricated sensor exhibits a broad linear range and also allows detection of E. coli in real food samples.19 Recently, silica microspheres were used for the fabrication of a DNA-based impedimetric biosensor for the detection of E. coli. The linear range of detection was found to be 1 × 10–10 to 1 × 10–5 μM.20

Numerous metal oxide nanoparticles have been exploited for developing an efficient electrochemical-based biosensor. ZnO nanoparticles exhibited excellent antibacterial activity due to their photocatalytic activity. Thus, ZnO produced a radical compound that shows antibacterial activity.21 CuO nanoparticles are proved to be highly reactive due to their high surface-to-volume ratio, which enhances the antibacterial activity.22 CuO and ZnO combine to form ZnO–CuO NC. The higher the concentration of CuO in composites, the smaller the band-gap energy can be obtained.23

Herein, we have synthesized and characterized a ZnO–CuO NC via a co-precipitation method. The as-synthesized NC was screen-printed on a Au electrode (SPE) for the detection of E. coli. A specific monoclonal antibody was physisorbed on the SPE for electrochemical characterization. The fabricated immunosensor was characterized using CV and DPV. Interference studies were carried out using S. aureus to check for the specificity of the immunosensor. Testing in milk samples was also done by spiking the milk samples with different concentrations of E. coli to check the potential of this immunosensor.

2. Experimental Section

2.1. Chemicals and Materials

Cupric chloride (CuCl2·2H2O, 99%), zinc chloride (ZnCl2, 99%), disodium hydrogen phosphate (Na2HPO4, 99%), and sodium hydrogen phosphate (NaHPO4·2H2O, 99%) were purchased from Fisher Scientific. The nutrient broth was obtained from HiMedia, ethyl cellulose from CDH, and butylcarbitol acetate (BCA) from Sigma-Aldrich Chemicals Pvt. Ltd. The anti-E. coli antibody was obtained from Abcam (ab35654). The structures of zinc oxide and copper oxide were taken from PubChem (https://pubchem.ncbi.nlm.nih.gov/) while the structures of lipopolysaccharide (LPS) and main receptor protein (PDB Id: 1CFV) of E. coli strain O157 were taken from RCSB PDB (https://www.rcsb.org/).

The ligand files that were in the .sdf file format were first converted into SMILES format for further analyses using an online web-based converter named Online SMILES converter (https://cactus.nci.nih.gov/translate/). Molecular docking analysis was executed using AutoDock Vina.24

2.2. Instruments and Characterization Details

A three-electrode system was obtained from Metrohm, DropSens (DS 220BT). An X-ray diffractometer (Rigaku Ultima IV) was used for phase analysis, Bruker’s Tensor 37 spectrometer was used for FTIR measurements, a surface tension/contact angle SEO instrument was used for contact angle measurements, and an IVIUM potentiostat was used for electrochemical characterization. The structural studies were carried out using XRD patterns from 20 to 80° 2θ scanning range with Cu Kα radiation (λ = 1.54184 Å). An FESEM study at an accelerated voltage of 10 kV was used to find out the shape and surface morphology of ZnO–CuO NC. The FTIR spectrum was recorded in an ATR mode from 4000 to 590 cm–1, and Raman spectroscopy characterization was carried out from 0 to 1000 cm–1 range.

The electrochemical characterization was carried out using CV and DPV. For CV measurements, 60 μL of a serially diluted sample was purged on SPE to record the spectrum at a 50 mV s–1 scan rate and from −1 to +1 V voltage. The anti-E. coli antibody (1:40 dilution) was physically immobilized via the drop-casting method and dried at 4 °C for 1 h. Physisorption/physical absorption (bioconjugation process) of an antibody is the simplest method of antibody immobilization, which does not require additional reagents or linkers. The presence of linkers might lead to cross-reactivity with the antibody and interference with specificity as well and may also affect the functionality of the antibody. The CV measurements were recorded in a solution of a ferri/ferrocyanide redox couple (1:1) in PBS (0.1 M, pH 7) as a background electrolyte at room temperature. Similarly, DPV studies were carried out at potential from −1 to +1 V, pulse time 10 ms, and pulse amplitude 10 mV. For selectivity studies, S. aureus was used as an interfering agent. The fabricated immunosensor was also tested in milk samples.

For molecular docking studies, the LPS of strain O157 was selected as the main receptor for the study. The target structures are not used directly for docking as they may contain heavy atoms, co-crystallized ligands, water molecules, metal ions, co-factors, etc. Therefore, they first need to be preprocessed. The preprocessing was done by the addition of hydrogen atoms and addition of polar charges and Gasteiger charges. Once the preprocessing was done, the target receptors were converted and saved in the .pdbqt format. Nanocomposites of zinc and copper oxides were selected as the ligand for the molecular docking study. The energy minimization was executed using mmff94 force field, optimization was done using steepest descent (SD) algorithm in a total of 200 steps, and the terminating criteria was updated in case the energy difference was less than 0.1. The ligand was later on converted from the .sdf to the .pdbqt format for docking purposes. Receptor optimization: The 2POF structure was optimized by first removing water molecules, any bound co-factors, metal ions, and co-bounded ligands and later on screened for a post-translational modification (PTM) check using the Vienna PTM tool.25

Docking was executed on AutoDock Vina on a Windows 64-bit platform.24 The same initial procedure of preprocessing was carried out for each target separately. The synthesized ligand was uploaded after the prepared target using predefined parameters. The binding pocket was set to the original ligand referred to all of the atoms within 10 Å distance. The Broyden–Fletcher–Goldfarb–Shanno run (BFGS run) was used as the main optimization algorithm for docking. After docking, atomic charges were computed using the Atomic Charge Calculator II webserver.26 The electronegativity equalization method (EEM) was used to calculate the atomic charges of the two complexes.27 Further, the interactions formed between the antibody–nanocomposite formulated structures were identified using a protein ligand interaction profiler.28

2.3. Synthesis of ZnO–CuO NC

ZnO–CuO NC was synthesized using CuCl2·2H2O and ZnCl2 in distilled water. A solution (0.05 M) of ZnCl2 was added to 0.1 M solution of CuCl2·2H2O with continuous stirring. The mixture solution obtained was then precipitated with an ammonia solution at pH 11. The precipitate was washed with distilled water and dried at 80 °C and finally calcined in a muffle furnace at 600 °C for 4 h.

2.4. Fabrication of the ZnO–CuO-Modified Electrode

For the fabrication of the immunosensor, the SPE (three-electrode system) was first used, which consisted of a working electrode (WE) and a counter electrode (CE) made up of gold and silver as a reference electrode (RE). The WE of 4 mm in diameter was coated with NC using a screen-printing technique. The SPE was dried at 60 °C for 1 h.

2.5. Bacterial Cultivation

The bacterial culture was prepared by inoculating a 10 μL loop of E. coli in nutrient broth for about 18–20 h at 37 °C. The culture obtained was centrifuged three times, and the pellet obtained was suspended in phosphate buffer saline (PBS, pH 7.2). The absorbance was recorded at 600 nm to find out the initial cell count using the McFarland standard method (it is the method used to estimate the concentration of different bacteria based on the turbidity of the bacterial suspensions). For this study, this method was used to find out the concentration of bacteria in CFU mL–1 29 and to prepare the serially diluted samples of the bacterial culture (1 × 103 to 1 × 106 CFU mL–1).

3. Results and Discussion

3.1. Characterization of NC

The results of the XRD analysis (Figure 1a) showed that CuO diffraction patterns appear in the peak 2θ at 35.56, 38.8, 48.46, and 68.03, which match well with the JCPDS card number 895899. The 2θ values of 36.32, 56.64, and 62.96 correspond to ZnO, which also match well with the JCPDS card number 891397. The peak at 31.63 corresponds to CuO.95ZnO.05, which matches well with the JCPDS card number 880268 and confirms the formation of ZnO–CuO NC. An FESEM study at an accelerated voltage of 10 kV was used to find out the shape and surface morphology of ZnO–CuO NC, and the corresponding images are shown in Figure 1b (low resolution) and Figure 1c (high resolution). The shape cannot be properly identified due to the agglomeration of the particles, though the particle size obtained was about 25 nm.

Figure 1.

Figure 1

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(a) XRD profile for ZnO–CuO NC, (b) FESEM image of ZnO–CuO NC at low resolution, (c) FESEM image of ZnO–CuO NC at high resolution, (d) FTIR spectra of ZnO–CuO NC, and (e) Raman plot for ZnO–CuO NC.

The absorption band of each specific chemical bond has unique energy; therefore, FTIR spectroscopy can be employed to obtain structural and bond information of a complex as well as the strength and type of bonding.30 For elemental characterization (Figure 1d) using FTIR, the O–H stretching band was observed at 3491 cm–1, which was due to water used as a solvent during the synthesis of the NC. A peak at 906 cm–1 corresponds to Cu–OH. Similarly, the peaks at 723 and 669 cm–1 correspond to Cu–O and Zn–O bonds, respectively. Raman spectroscopy is a versatile technique to study vibrational properties. The three major peaks were observed at 94, 271, and 597 cm–1 (Figure 1e). The major peak in the Raman spectrum, at 271 cm–1, corresponds to CuO, whereas two other peaks at 94 and 597 cm–1 correspond to ZnO.

3.2. Contact Angle Studies

The hydrophilicity and surface wettability of an electrode depend on surface chemistry. Contact angle measurements were carried out for both NC-SPE (without antibody immobilization) and NC-SPE/Anti-LPS (after antibody immobilization) immunoelectrodes (Figure 2). A buffer droplet (PBS buffer with a ferri/ferro redox couple) was produced over both the electrodes using a micropipette, and the contact angle was measured at the interface of water and the electrode surface. The contact angle for NC-SPE was 70.41° (Figure 2a) and for NC-SPE/Anti-LPS was 61.4° (Figure 2b). Due to the excess availability of −COOH groups in the NC-SPE/Anti-LPS immunoelectrode, the surface hydrophilicity was increased compared to that of NC-SPE. This indicates that antibody immobilization increases the surface hydrophilicity and thus increases the interaction between the antibody and antigen. Apart from this increase, hydrophilicity resulted in stronger adhesion of biomolecules on the surface of the NC.

Figure 2.

Figure 2

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Contact angle images of (a) NC-SPE and (b) NC-SPE/Anti-LPS.

3.3. Electrochemical Characterization of the Fabricated Immunosensor

Electrochemical characterization was carried out at room temperature. The electrochemical behavior of (ii) NC-SPE and (iii) NC-SPE/Anti-LPS was studied using CV at a scan rate of 50 mV s–1 with a voltage scan from −1 to +1 V. All of the studies were carried out in a PBS solution containing K3[Fe(CN)6]/K4[Fe(CN)6]. A well-defined redox peak was observed for both the electrodes (Figure 3). A drastic increase in anodic current was observed after antibody immobilization (NC-SPE/Anti-LPS). This may be due to formation of the antigen–antibody complex on the surface of the electrode, and because of increased antigen binding sites, the complex behaves as an accelerating layer for the transfer of electrons.31 The Ipa/Ipc ratio for NC-SPE electrode was found to be 0.8 which indicates the quasi-reversible nature of the electrode, whereas the Ipa/Ipc ratio for NC-SPE/Anti-LPS electrode was found to be 1.16 which shows the reversible nature of the fabricated electrode.

Figure 3.

Figure 3

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CV response of (i) buffer, (ii) NC-SPE and (iii) NC-SPE/Anti-LPS at fixed E. coli concentrations.

3.4. Effect of Scan Rate and Immunosensor Response Studies

The charge transfer characteristics of the immunosensor were measured using kinetic studies from 10 to 100 mV s–1 scan rates on NC-SPE as well as the NC-SPE/Anti-LPS immunoelectrode (Figure 4). The peak current (a, b) of the anode and the cathode increases with scan rate, indicating the continuous and homogenous electron transfer on the electrode.32 The anodic and cathodic peak currents were plotted against the square root of scan rate (c, d), which indicates a linear relation (>30 mV s–1) with R2 values close to 0.99.

Figure 4.

Figure 4

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(a, b) Cyclic voltammograms of NC-SPE at fixed concentrations (8 × 104 CFU mL–1) from 10 to 100 mV s–1 scan rate for NC-SPE and NC-SPE/Anti-LPS immunoelectrodes, respectively. (c, d) Variation in redox current with the square root of scan rate for NC-SPE and NC-SPE/Anti-LPS, respectively. (e, f) Variation in redox current with the log of scan rate at fixed concentrations (8 × 104 CFU mL–1) at a scan rate ranging from 10 to 100 mV s–1 for NC-SPE and NC-SPE/Anti-LPS, respectively.

This linearity suggests that the mobility of the charge carriers was a diffusion-controlled process.33 Variations in redox current with the log of scan rate were also plotted to understand the diffusion-controlled process (Figure 4e,f). The value of the slope, intercept and the linear regression of linear behavior of the peak current were calculated by linear fitting, eqs 1–4.

For the NC-SPE immunoelectrode:

3.4. 1
3.4. 2

For the NC-SPE/Anti-LPS immunoelectrode:

3.4. 3
3.4. 4

The diffusion coefficient, effective electrode surface area, and surface concentration of electroactive species for both NC-SPE and NC-SPE/Anti-LPS immunoelectrodes were calculated.

The value of the diffusion coefficient was calculated from the Randles–Sevcik equation31

3.4. 5

D is the diffusion coefficient (cm2 s–1), Ip is the maximum peak current (ampere), A is the electrode surface area (0.12 cm2), n is the number of electrons (1), C is the concentration of PBS buffer (0.1 M), and υ is the scan rate (V s–1). The diffusion coefficients for NC-SPE and NC-SPE/Anti-LPS were found to be 1.1 × 10–14 and 7.05 × 10–14 cm2 s–1, respectively. A high diffusion coefficient for NC-SPE/Anti-LPS was due to higher transfer of electrons after antibody immobilization, which confirms that the antibody was successfully immobilized on NC-SPE.

The surface concentration of ionic species for NC-SPE and NC-SPE/Anti-LPS was obtained from the Brown–Anson model34

3.4. 6

Υ* is the surface concentration of ionic species, R is the universal gas constant (8.314 J mol–1 K–1), T is room temperature (25 °C), Ip is the maximum peak current in ampere, F is the Faraday constant (96 485 C mol–1), A is the area of the electrode (0.12 cm2), n is the number of electrons (1), and υ is the scan rate (V s–1). The surface concentrations of ionic species for NC-SPE and NC-SPE/Anti-LPS were found to be 1.3 × 10–8 and 3.3 × 10–8 mol cm–2, respectively. The higher surface concentration of NC-SPE/Anti-LPS indicates more binding sites available for antigen/E. coli binding.

Similarly, differential pulse voltammetry studies of (i) NC-SPE and (ii) NC-SPE/Anti-LPS were carried out to understand the electrochemical process further. During DPV measurements, the change in current was plotted as a function of potential. It was evidenced from Figure 5a that current increases (31.7 μA) significantly for the NC-SPE/Anti-LPS immunoelectrode, which confirms the binding of the anti-LPS antibody in the electrode. After immobilization of anti-LPS, a slight left shift in peak potential was observed, indicating facile electron transfer at the surface of the electrode. The peak current increases with the increasing concentration of E. coli (in CFU mL–1), which indicates that the surface of the electrode is covered with antigen–antibody complexes (Figure 5b).

Figure 5.

Figure 5

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(a) DPV response of (i) NC-SPE and (ii) NC-SPE/Anti-LPS and (b) DPV curve for various concentrations of E. coli.

A calibration curve shows a sharp increase in peak current, which was due to the interaction of E. coli with more available binding sites on the anti-LPS antibody on NC-SPE/Anti-LPS (Figure 6a). A log10 (E. coli concentration) versus peak current (Figure 6b) was plotted to find the linear relationship. The calibration curve became almost linear in the concentration range of 1 × 103 to 8 × 104 CFU mL–1. The sensitivity of the electrode was estimated from the slope of the calibration curve (Figure 6b). The sensitivity was found to be 11.04 μA CFU–1 mL–1. The LOD was found to be 2 CFU mL–1 with a 1 × 103 to 8 × 104 CFU mL–1 linear range of detection. ZnO–CuO NC is reported for the first time for fabricating an immunosensor for E. coli based on electrochemical detection. The infectious dose for E. coli as low as 10 bacterial cells was reported.35,36 This was probably due to the large surface area of ZnO–CuO NC, which enhances the generation of reactive oxygen species and thus enhances the antibacterial effect.23

Figure 6.

Figure 6

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(a) Calibration plot of peak current versus E. coli concentration in CFU mL–1 for NC-SPE/Anti-LPS and (b) calibration plots for peak current versus E. coli concentration in log10 CFU mL–1.

3.5. Specificity Studies

Cross-reactivity for antibodies is an important concern for immunosensors. To assess the selectivity, interference studies were conducted with E. coli and S. aureus at a concentration of around 1 × 106 CFU mL–1 cells along with the control. The DPV curve was measured for all of the three samples. The results for an interfering agent were found close to those for the control, indicating the selectivity of the immunoelectrode for E. coli. It is also clear in Figure 7 that the maximum rise in the peak current was obtained for E. coli.

Figure 7.

Figure 7

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Selectivity bar graph of E. coli (Gram-negative) and S. aureus (Gram-positive).

3.6. Testing the Immunosensor with Real Samples

E. coli is often food-borne and can also be found in milk samples. To test the sensitivity of the fabricated immunosensor, various concentrations of E. coli were spiked in a milk sample to simulate the real-life milk sample. The DPV response obtained for milk samples spiked with E. coli shows a similar trend as in PBS, that is, the E. coli concentration is directly proportional to the peak current (Figure 8). This indicates the possible use of the immunosensor in the detection of E. coli in milk samples.

Figure 8.

Figure 8

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DPV response of milk samples spiked with E. coli having different concentrations.

3.7. Molecular Docking Studies

Our results showcase that the antibody (PDB ID: 1CFV) has a greater and better affinity for the nanocomposite ZnO–CuO when compared to LPS–ZnO–CuO NP. Table 1 summarizes the docking scores, binding affinity (kcal mol–1), and RMSD for both the complexes. Figure 9 showcases the docked complex. We observed a rigid surface binding of the nanoparticle composite to our target receptor LPS. This clearly proves why the binding affinity is low and the root-mean-square deviation (RMSD) scores are also not optimum.

Table 1. Binding Affinities between LPS and the Antibody with a Nanoparticle Complex.

target receptor binding affinity (kcal mol–1) distance from rmsd lb distance from rmsd ub
LPS (polysaccharide)_NP –3.9 0.78 1.24
(1CFV)_NP –1.9 0.0 0.0
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Figure 9.

Figure 9

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Docked nanoparticle composite (ZnO–CuO) with E. coli strain O157: (a) LPS and (b) antibody (PDB ID: 1CFV).

3.7.1. Atomic Charge Computation

The electronegativity equalization method (EEM) is a fast approach for charge calculations. We observed that LPS with NP had a maximum charge of 62.02745 and a minimum charge of −62.02745, while the antibody against the LPS of E. coli (PDB ID: 1CFV) with NP had a minimum charge of −1.94071 and a maximum charge of +1.94071.

3.7.2. Interaction Analysis

The antibody–NP complex was selected for an interaction analysis using PLIP. It is evident that the complex has formed two hydrogen bonds with residues lysine (50L) and glutamine (111H) and a strong side-chain metal ion interaction with serine (48L). Table 2 shows the number of interactions formed.

Table 2. Interactions Formed between the Antibody and NC Complex.
  types of interactions formed
hydrogen bonds
 metal ion interactions
receptor–ligand complex residue amino acid residue amino acid
antibody–ZnO–CuO 50L 111H LYS GLN 48L SER
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Figure 10a depicts how the antibody and NC are interacting with each other. The superimposition of the trio, i.e., the antibody (PDB ID: 1CFV), the nanocomposite (ZnO–CuO), and the LPS of E. coli, was further subjected to an interaction analysis. Two different interaction scenarios of the antibody (PDB ID: 1CFV) were observed, one was with ZnO–CuO and the other with the LPS. Figure 10b displays the superimposed structure of the antibody–NC–LPS, while Figure 10c displays the types of interactions formed separately between the antibody and NC and the antibody and the LPS. Only a single metal ion interaction was formed with the histamine residue (98L) of the NP with the antibody (PDB ID: 1CFV), while only a single hydrogen bond was formed with the leucine residue (101L), with seven hydrophobic interactions of the lipopolysaccharide of the E. coli showing strong affiliations (Table 3).

Figure 10.

Figure 10

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(a) Antibody–NC interactions. (a) Blue lines indicate two hydrogen bonds, while the pink lines indicate the formation of a metal ion interaction, (b) sandwiched antibody–NP–LPS superimposed structure and (c) interactions formed separately between the antibody and NP and the antibody and LPS of E. coli.

Table 3. Interactions Formed for the Sandwiched Structure: Antibody–NP–LPS of E. coli.
  types of interactions formed
hydrogen bonds
 metal ion interactions
receptor–ligand complex residue amino acid residue amino acid
antibody–ZnO–CuO     98L HIS
  hydrogen bonds hydrophobic interactions
antibody–LPS of E. coli 101L LEU 33H TYR
33H TYR
33H TYR
50H ALA
101H TYR
104H TYR
104H TYR
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The above interaction analysis indicates that the antibody (PDB ID: 1CFV) strongly binds with the LPS of E. coli when compared to the antibody with ZnO–CuO NP. The greater number of hydrophobic interactions is important for protein folding, which in turn is essential for keeping a protein complex stable and biologically active as it reduces surface tension in the protein, further reducing formation of interactions with water molecules present in the environment. Antibody–LPS interactions are stronger when immobilized with a nanoparticle composite (ZnO–CuO). This can also be correlated to electrochemical characterization results, where a higher peak current was observed after antibody immobilization.

4. Conclusions

We have reported a quick and efficient co-precipitation method for the synthesis of ZnO–CuO NC. The NC was successfully characterized using various techniques such as XRD, FESEM, FTIR spectroscopy, and Raman spectroscopy. The NC was coated on gold electrodes through the screen-printing technique, and then the anti-LPS antibody for E. coli was immobilized on the NC surface through physisorption. This platform was used to carry out the electrochemical characterization using CV and DPV. The electrochemical analysis showed the oxidation and reduction properties of ZnO–CuO NC, and the scan rate study confirmed that the process was diffusion controlled. The response studies were carried out using DPV in the concentration range of 1 × 103 to 1 × 106 CFU mL–1 with linearity up to 8 × 104 CFU mL–1. The high sensitivity and low LOD were obtained for the fabricated sensor. Therefore, it provides one of the best platforms for the electrochemical detection of E. coli with low detection limits and high sensitivity. The immunosensor showed selectivity toward E. coli and was also able to detect E. coli in real milk samples. Computational results revealed that there is a strong correlation between molecular docking studies and electrochemical characterization. The interaction analysis results revealed that antibody–LPS interactions are stronger when immobilized with a nanoparticle composite (ZnO–CuO).

Acknowledgments

S.K. thanks the Indian Council of Medical Research, New Delhi, for providing financial assistance as ICMR-SRF (45/49/2018-Nan/BMS) to carry out the research work. The authors also thank Prof. Shafeeque A. Ansari, in charge, Central Instrumentation Facility (CIF), Jamia Millia Islamia, New Delhi, for providing necessary technical facilities.

The authors declare no competing financial interest.

References

  1. Kaper J. B.; Nataro J. P.; Mobley H. L. T. Pathogenic Escherichia coli. Nat. Rev. Microbiol. 2004, 2, 123–140. 10.1038/nrmicro818. [DOI] [PubMed] [Google Scholar]
  2. Leach K. M.; Stroot J. M.; Lim D. V. Same-day detection of Escherichia coli O157:H7 from spinach by using electrochemiluminescent and cytometric bead array biosensors. Appl. Environ. Microbiol. 2010, 76, 8044–8052. 10.1128/AEM.01990-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Dweik M.; Stringer R. C.; Dastider S. G.; Wu Y.; Almasri M.; Barizuddin S. Specific and targeted detection of viable Escherichia coli O157:H7 using a sensitive and reusable impedance biosensor with dose and time response studies. Talanta 2012, 94, 84–89. 10.1016/j.talanta.2012.02.056. [DOI] [PubMed] [Google Scholar]
  4. Li Y.; Afrasiabi R.; Fathi F.; Wang N.; Xiang C.; Love R.; She Z.; Kraatz H. B. Impedance based detection of pathogenic E. coli O157:H7 using a ferrocene-antimicrobial peptide modified biosensor. Biosens. Bioelectron. 2014, 58, 193–199. 10.1016/j.bios.2014.02.045. [DOI] [PubMed] [Google Scholar]
  5. Sun J.; Ji J.; Sun Y.; Abdalhai M. H.; Zhang Y.; Sun X. DNA biosensor-based on fluorescence detection of E. coli O157:H7 by Au@Ag nanorods. Biosens. Bioelectron. 2015, 70, 239–245. 10.1016/j.bios.2015.03.009. [DOI] [PubMed] [Google Scholar]
  6. Cheng P.; Huang Z.-G.; Zhuang Y.; Fang L.-C.; Huang H.; Deng J.; Jiang L.-L.; Yu K.-K.; Li Y.; Zheng J.-S. A novel regeneration-free E. coli O157:H7 amperometric immunosensor based on functionalised four-layer magnetic nanoparticles. Sens. Actuators, B 2014, 204, 561–567. 10.1016/j.snb.2014.08.008. [DOI] [Google Scholar]
  7. Fang D.; Gao G.; Shen J.; Yu Y.; Zhi J. A reagentless electrochemical biosensor based on thionine wrapped E coli and chitosan-entrapped carbon nanodots film modified glassy carbon electrode for wastewater toxicity assessment. Electrochim. Acta 2016, 303–311. 10.1016/j.electacta.2016.10.174. [DOI] [Google Scholar]
  8. Zou Y.; Liang J.; She Z.; Kraatz H. B. Gold nanoparticles-based multifunctional nanoconjugates for highly sensitive and enzyme-free detection of E. coli K12. Talanta 2019, 193, 15–22. 10.1016/j.talanta.2018.09.068. [DOI] [PubMed] [Google Scholar]
  9. Jijie R.; Kahlouche K.; Barras A.; Yamakawa N.; Bouckaert J.; Gharbi T.; Szunerits S.; Boukherroub R. Reduced graphene oxide/polyethylenimine based immunosensor for the selective and sensitive electrochemical detection of uropathogenic Escherichia coli. Sens. Actuators, B 2018, 260, 255–263. 10.1016/j.snb.2017.12.169. [DOI] [Google Scholar]
  10. Zhu C.; Yang G.; Li H.; Du D.; Lin Y. Electrochemical Sensors and Biosensors Based on Nanomaterials and Nanostructures. Anal. Chem. 2015, 87, 230–249. 10.1021/ac5039863. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Tran T. B.; Son S. J.; Min J. Nanomaterials in label-free impedimetric biosensor: Current process and future perspectives. BioChip J. 2016, 10, 318–330. 10.1007/s13206-016-0408-0. [DOI] [Google Scholar]
  12. Jans H.; Huo Q. Gold nanoparticle-enabled biological and chemical detection and analysis. Chem. Soc. Rev. 2012, 41, 2849–2866. 10.1039/C1CS15280G. [DOI] [PubMed] [Google Scholar]
  13. Lin D.; Tang T.; Jed Harrison D.; Lee W. E.; Jemere A. B. A regenerating ultrasensitive electrochemical impedance immunosensor for the detection of adenovirus. Biosens. Bioelectron. 2015, 68, 129–134. 10.1016/j.bios.2014.12.032. [DOI] [PubMed] [Google Scholar]
  14. Zhou J.; Du L.; Zou L.; Zou Y.; Hu N.; Wang P. An ultrasensitive electrochemical immunosensor for carcinoembryonic antigen detection based on staphylococcal protein A—Au nanoparticle modified gold electrode. Sens. Actuators, B 2014, 197, 220–227. 10.1016/j.snb.2014.02.009. [DOI] [Google Scholar]
  15. Maalouf R.; Fournier-Wirth C.; Coste J.; Chebib H.; Saïkali Y.; Vittori O.; Errachid A.; Cloarec J.-P.; Martelet C.; Jaffrezic-Renault N. Label-Free Detection of Bacteria by Electrochemical Impedance Spectroscopy: Comparison to Surface Plasmon Resonance. Anal. Chem. 2007, 79, 4879–4886. 10.1021/ac070085n. [DOI] [PubMed] [Google Scholar]
  16. Barreiros dos Santos M.; Azevedo S.; Agusil J. P.; Prieto-Simón B.; Sporer C.; Torrents E.; Juárez A.; Teixeira V.; Samitier J. Label-free ITO-based immunosensor for the detection of very low concentrations of pathogenic bacteria. Bioelectrochemistry 2015, 101, 146–152. 10.1016/j.bioelechem.2014.09.002. [DOI] [PubMed] [Google Scholar]
  17. Joung C.-K.; Kim H.-N.; Lim M.-C.; Jeon T.-J.; Kim H.-Y.; Kim Y.-R. A nanoporous membrane-based impedimetric immunosensor for label-free detection of pathogenic bacteria in whole milk. Biosens. Bioelectron. 2013, 44, 210–215. 10.1016/j.bios.2013.01.024. [DOI] [PubMed] [Google Scholar]
  18. Zhou Z.; Zhang Y.; Guo M.; Huang K.; Xu W. Ultrasensitive magnetic DNAzyme-copper nanoclusters fluorescent biosensor with triple amplification for the visual detection of E. coli O157:H7. Biosens. Bioelectron. 2020, 167, 112475 10.1016/j.bios.2020.112475. [DOI] [PubMed] [Google Scholar]
  19. Zhang X.; Wu T.; Yang Y.; Wen Y.; Wang S.; Xu L.-P. Superwettable electrochemical biosensor based on a dual-DNA walker strategy for sensitive E. coli O157: H7 DNA detection. Sens. Actuators, B 2020, 321, 128472 10.1016/j.snb.2020.128472. [DOI] [Google Scholar]
  20. Ariffin E. Y.; Heng L. Y.; Tan L. L.; Karim N. H. A.; Hasbullah S. A. A highly sensitive impedimetric DNA biosensor based on hollow silica microspheres for label-free determination of E. coli. Sensors 2020, 20, 1279 10.3390/s20051279. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Padmavathy N.; Vijayaraghavan R. Enhanced bioactivity of ZnO nanoparticles-an antimicrobial study. Sci. Technol. Adv. Mater. 2008, 9, 035004 10.1088/1468-6996/9/3/035004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Rad M.; Taran M.; Alavi M. Effect of incubation time, CuSO4 and glucose concentrations on biosynthesis of copper oxide (CuO) nanoparticles with rectangular shape and antibacterial activity: Taguchi method approach. Nano Biomed. Eng. 2018, 10, 25–33. 10.5101/nbe.v10i1.p25-33. [DOI] [Google Scholar]
  23. Widiarti N.; Sae J. K.; Wahyuni S. Synthesis CuO-ZnO nanocomposite and its application as an antibacterial agent. IOP Conf. Ser.: Mater. Sci. Eng. 2017, 172, 012036 10.1088/1757-899X/172/1/012036. [DOI] [Google Scholar]
  24. Trott O.; Olson A. J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 2010, 31, 455–561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Margreitter C.; Petrov D.; Zagrovic B. Vienna-PTM web server: a toolkit for MD simulations of protein post-translational modifications. Nucleic Acids Res. 2013, 41, W422–W426. 10.1093/nar/gkt416. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Raček T.; Schindler O.; Toušek D.; Horský V.; Berka K.; Koča J.; Svobodová R. Atomic Charge Calculator II: web-based tool for the calculation of partial atomic charges. Nucleic Acids Res. 2020, 48, W591–W596. 10.1093/nar/gkaa367. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Varekova R. S.; Jirouskova Z.; Vanek J.; Suchomel S.; Koca J. Electronegativity Equalization Method: Parameterization and Validation for Large Sets of Organic, Organohalogene and Organometal Molecule. Int. J. Mol. Sci. 2007, 8, 572–582. 10.3390/i8070572. [DOI] [Google Scholar]
  28. Salentin S.; Schreiber S.; Haupt V. J.; Adasme M. F.; Schroeder M. PLIP: fully automated protein-ligand interaction profiler. Nucleic Acids Res. 2015, 43, W443–W447. 10.1093/nar/gkv315. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Zapata A.; Ramirez-Arcos S. A comparative study of McFarland turbidity standards and the Densimat photometer to determine bacterial cell density. Curr. Microbiol. 2015, 70, 907–909. 10.1007/s00284-015-0801-2. [DOI] [PubMed] [Google Scholar]
  30. Raul P. K.; Senapati S.; Sahoo A. K.; Umlong I. M.; Devi R. R.; Thakur A. J.; Veer V. CuO nanorods: A potential and efficient adsorbent in water purification. RSC Adv. 2014, 4, 40580–40587. 10.1039/C4RA04619F. [DOI] [Google Scholar]
  31. Gupta P. K.; Khan Z. H.; Solanki P. R. Improved electrochemical performance of metal doped Zirconia nanoparticles for detection of Ochratoxin-A. J. Electroanal. Chem. 2018, 829, 69–80. 10.1016/j.jelechem.2018.10.004. [DOI] [Google Scholar]
  32. Lakshmi G. B.; Sharma A.; Solanki P. R.; Avasthi D. K. Mesoporous polyaniline nanofiber decorated graphene micro-flowers for enzyme-less cholesterol biosensors. Nanotechnology 2016, 27, 345101 10.1088/0957-4484/27/34/345101. [DOI] [PubMed] [Google Scholar]
  33. Khan S.; Ansari Z. A.; Alothman O. Y.; Fouad H.; Ansari S. G. Application of Amine and Copper Doped Magnesium Oxide Nanoparticles in Electrochemical Immunosensors for Detecting Brucella abortus. Nanosci. Nanotechnol. Lett. 2017, 9, 1656–1664. 10.1166/nnl.2017.2544. [DOI] [Google Scholar]
  34. Bard A. J.Electrochemical Methods: Fundamentals and Applications/Allen J. Bard, Larry R. Faulkner; Wiley: New York, 1980. [Google Scholar]
  35. Tokarskyy O.; Marshall D. L. Immunosensors for rapid detection of Escherichia coli O157:H7 - perspectives for use in the meat processing industry. Food Microbiol. 2008, 25, 1–12. 10.1016/j.fm.2007.07.005. [DOI] [PubMed] [Google Scholar]
  36. Velusamy V.; Arshak K.; Korostynska O.; Oliwa K.; Adley C. An overview of foodborne pathogen detection: In the perspective of biosensors. Biotechnol. Adv. 2010, 28, 232–254. 10.1016/j.biotechadv.2009.12.004. [DOI] [PubMed] [Google Scholar]

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