Electrochemical Biosensors Based on Carbon Nanomaterials for Diagnosis of Human Respiratory Diseases
Abstract
:1. Introduction
2. Characteristics of Carbon Nanomaterials and Human Common Respiratory Diseases
3. Electrochemical Biosensors Based on Carbon Nanomaterials for Diagnosis of Human Respiratory Diseases
3.1. Electrochemical Biosensors for Influenza Diagnosis
3.2. Electrochemical Biosensors for COVID-19 Diagnosis
3.3. Electrochemical Biosensors for Pulmonary Fibrosis Diagnosis
3.4. Electrochemical Biosensors for Tuberculosis Diagnosis
3.5. Electrochemical Biosensors for Lung Cancer Diagnosis
3.6. Electrochemical Biosensors for Other Human Respiratory Diseases Diagnosis
4. Comparative Analysis with Conventional Approaches for the Diagnosis of Human Respiratory Diseases
5. Conclusions and Outlooks
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Carbon Nanomaterials | Mechanism of Detection | Target | Analytical Performances (LOD = Limit of Detection, R2 Refers to Determination Coefficient, Relative Standard Deviation Value = RSD) | Ref. |
---|---|---|---|---|
Graphene gold hybrid nanocomposite | EIS | Neuraminidase (a surface glycoproteins of H9N2 influenza virus A) activity | Linear range: 10−8 U/mL~10−1 U/mL with RSD 3.23%; LOD: 10−8 U/mL; Real sample analysis: detecting real H9N2 influenza type A virus with sensitivity and accuracy compared with the ELISA assay results | [71] |
Reduced graphene oxide | Cyclic voltammetry (CV) | Surface protein hemagglutinin of H5N1 and H1N1 influenza virus | Linear range: 25~300 nM; LOD: 2.29 nM in PBS and 2.39 nM in human blood plasma for H5N1, LOD: 3.09 nM in PBS and 3.63 nM in human blood plasma for H1N1; Real sample analysis: accuracy for real analysis with percentage of recoveries 89~101% for H5N1 and 86~103% for H1N1 via recovery studies by spiking human plasma with different concentrations of hemagglutinin of H5N1 and H1N1; Stability and selectivity | [70] |
graphene oxide | EIS | H1N1 Influenza A protein | Linear range: 0 ng/mL~10 μg/mL; LOD: 10 ng/mL; Stability and repeatability | [39] |
Multi-wall carbon nanotubes | Differential pulse voltammetry (DPV) | Avian influenza virus H5N1 gene sequence | Linear range: 5.0 × 10−12~1.0 × 10−9 M (R2 = 0.9863); LOD: 4.3 × 10−13 M; High recognition and selectivity for H5N1 specific sequence | [37] |
Carbon Nanomaterials | Mechanism of Detection | Target | Analytical Performances | Ref. |
---|---|---|---|---|
~20 nm diamond | EIS | SARS-CoV-2 nucleocapsid protein | Linear range: 1 fM~100 pM. (R2 = 0.9863); LOD: 0.389 fM; Selectivity, specificity, stability and reusability | [62] |
Laser-scribed graphene (LSG) | DPV | SARS-CoV-2 S1 spike protein | Linear range: 5.0~500 ng/mL. (R2 = 0.996); LOD: 2.9 ng/mL; Real sample analysis: successful COVID-19 diagnosis carried out on 23 patient blood serum samples; User-friendly diagnostic platform; Ease of operation; Accessibility and systematic data management; Faster results compared to commercial diagnostic tools | [46] |
Calixarene functionalized graphene oxide | DPV | RNA of SARS-CoV-2 | Linear range: 5.0~500 ng/mL. (R2 = 0.945); LOD: 3 aM; Real sample analysis: higher detectable ratios (85.5 % and 46.2 %) than those obtained using RT-qPCR (56.5 % and 7.7 %); High specificity and selectivity; Only two copies (10 μL) of SARS-CoV-2 were required for per assay | [64] |
Carbon nanotube | Field-effect transistor (FET) technology | SARS-CoV-2 S1 antigen | Linear range: 0.1~5000 fg/mL; LOD: 4.12 fg/mL; Good selectivity to SARS-CoV-2 S1, Able to discriminate SARS-CoV-2 S1, SARS-CoV-1 S1 and MERS-CoV S1 antigens; Rapidly testing people for SARS-CoV2 infection; Easy to handle | [79] |
Carbon Nanomaterials | Mechanism of Detection | Target | Analytical Performances (S/N refers to a Signal to Noise Ratio) | Ref. | |
---|---|---|---|---|---|
Fullerene | DPV | Biomarker miR-3675-3p for idiopathic pulmonary fibrosis | Linear range: 10 fM~10 nM (R2 = 0.9976); LOD: 2.99 fM calculated with M + 3δ (M: the average of DPV signal response; δ: the standard deviation of blank solution); Outstanding reproducibility and specificity; Good recovery (from 94.2% to 103.7%) in the spiked serum | [20] | |
Carbon nanodots | DPV | F508del mutation in the cystic fibrosis transmembrane regulator gene | Linear range: 0.001~20 µM (R2 = 0.998); LOD: 0.16 nM; High reproducibility and selectivity | [80] | |
Carbon nanofiber | Square wave voltammograms (SWV) | Survival motor neuron 1 | Linear range: 1 pg/mL~1 µg/mL (R2 =0.981); LOD: 0.74 pg/mL | Multiplexed immunosensor; Strong selectivity against non-specific proteins; High recovery percentage in spiked whole blood samples | [81] |
Cystic fibrosis transmembrane conductance regulator (CFTR) | Linear range: 1 pg/mL~1 µg/mL (R2 = 0. 989); LOD: 0.9 pg/mL | ||||
Duchenne muscular dystrophy proteins | Linear range: 1 pg/mL~10 ng/mL (R2 = 0.979); LOD: 0.7 pg/ml | ||||
Gold nanoparticles graphite-epoxy nanocomposite | EIS | Triple base mutation deletion in a cystic-fibrosis | Linear range: 0.3 fmol~30 pmol; LOD: 22.5 (S/N = 3) | [48] |
Carbon Nanomaterials | Mechanism of Detection | Target | Analytical Performances | Ref. |
---|---|---|---|---|
Nitrogen-doped carbon nanodots (NCNDs) | ECL | Mycobacterium tuberculosis DNA fragment | Linear range: 50 aM~1 nM. (R2 = 0.9974); LOD: 1.4 aM; Specificity and stability | [93] |
Graphene oxide | ECL | Interferon gamma (IFN-γ) | Linear range: 0.1~500 pg⋅mL−1 (R2 = 0.9913); LOD: 30 fg⋅mL−1; Real sample analysis: capacity for determining IFN-γ in real biological samples with 96~103% recoveries; Successfully used for sensitive monitoring IFN-γ levels in peripheral blood mononuclear cell | [95] |
Tufted carbon nanotubes (CNTs) | DPV | Specific IS6110 DNA sequence of Mycobacterium tuberculosis | Linear range: 1 fM~10 nM (R2 = 0.9910); LOD: 0.33 fM (S/N = 3); Real sample analysis: High specificity and sensitivity for Mycobacterium tuberculosis detection in clinical samples | [18] |
Reduced graphene oxide nanoribbon | CV | target DNA of Mycobacterium tuberculosis | Linear range: 0.1 fM~10−6 M; High detection efficiency (0.1 fM); Excellent specificity (92%) to Mycobacterium tuberculosis target DNA | [16] |
Carbon Nanomaterials | Mechanism of Detection | Target | Analytical Performances | Ref. |
---|---|---|---|---|
Nano-Au functionalized graphene sheets | CV | Progastrin releasing-peptide (ProGRP) | Linear range: 10.0~500 pg/mL, (R2 = 0.996); LOD: 3.0 pg/mL (S/N = 3); Real sample analysis: accuracy of ProGRP determination in 11 serum samples; High selectivity, reproducibility and stability | [52] |
Multi-wall carbon nanotubes | Organic electrochemical transistor (OECTs) | Sialic acid | Linear range: 0.1 to 7 mM (R2 = 0.999); Excellent specificity; Excellent performance for detection sialic acid in serum samples from lung cancer patients | [97] |
Reduced-graphene oxide | DPV | Cytokeratin 19 fragment 21-1 | Linear range: 1.0 × 10−14~1.0 × 10−6 M, (R2 = 0.996 and R2 = 0.9955); LOD: 2.4 fM; Good selectivity and reproducibility | [24] |
Carbon nanotubes | DPV | Lung cancer biomarkers (anti-MAGE A2 and anti-MAGE A11) | Linear range: 5 fg mL−1~50 ng mL−1, (R2 = 0.9939 for anti-MAGE A2 and R2 = 0.9879 for anti-MAGE A11); Detecting anti-MAGE A2 and anti-MAGE A11 simultaneously; Decreasing the time of experimental assessment and cost | [51] |
Human Respiratory Diseases | Carbon Nanomaterials | Mechanism of Detection | Target | Analytical Performances | Ref. |
---|---|---|---|---|---|
Allergic rhinitis | Reduced graphene oxide nanocomposites | SWV | tryptase | Linear range: 100 pg/mL~100 ng/mL, (R2 = 0.998); LOD: 50 pg/mL (S/N = 3); A sensitivity of 1.64 μA/(ng/mL); High selectivity, reproducibility (RSD 2.1%) and high stability over 1 month | [98] |
Middle East respiratory syndrome (MERS) | Graphene oxide | EIS and Surface enhanced Raman spectroscopy (SERS) | MERS nanovesicle | Linear range: 1 pg/mL~100 ng/mL, (R2 = 0.992 for SERS, R2 = 0.9905 for EIS); In PBS buffer, LOD: 0.176 pg/mL for SERS, LOD: 0.405 pg/mL for EIS; In diluted 10% saliva, LOD: 0.52 pg/mL for SERS, LOD: 0.645 pg/mL for EIS | [99] |
Deep vein thrombosis | Functionalized carbon nanotubes | EIS | D-dimer | Linear range: 0.1 pg/mL~2 μg/mL; LOD: 0.1 pg/mL; Good sensitivity (40.1 kΩμM−1); Short response time (10 min); Good reproducibility (RSD 8.2%, n = 4) | [100] |
Asthma/pneumonia | Single walled carbon nanotubes | EIS | Pathogenic microorganism | Linear range: 102~1010 CFU/mL; LOD: 102 CFU/mL; Speed response time (about 10 min); High specificity | [101] |
Type of Biosensing Platform | Core Materials | Target | Characteristics/Remarks | Ref. |
---|---|---|---|---|
Electrochemical biosensor | Carbon nanomaterials (carbon nanotubes) | SARS-CoV-2 S1 antigen | Linear range: 0.1~5000 fg/mL; LOD: 4.12 fg/mL; Good selectivity to SARS-CoV-2 S1, Able to discriminate SARS-CoV-2 S1, SARS-CoV-1 S1 and MERS-CoV S1 antigens; Rapidly testing people for SARS-CoV2 infection; Easy to handle | [79] |
Electrochemical biosensor | gold nanoparticles and coated with graphene | SARS-CoV-2 S1 antigen | Quantitatively detection at a concentration as low as picomole within 10~12 s in human plasma samples | [102] |
Biosensor based on frequency magnetic mixing technology | Superparamagnetic nanoparticles | SARS-CoV-2 S1 antigen | Giving qualitative and semiquantitative results of SARS-CoV-2-specific antibody levels in patient’s sera within 21 min of assay time with a sensitivity of 97% and a specificity of 92% | [103] |
Biosensor based on field-effect transistor | In2O3 nanoribbon transistors | SARS-CoV-2 S1 antigen | detection of SARS-CoV-2 spike protein in both phosphate-buffered saline (PBS) buffer and universal transport medium (LOD: 100 fg/mL) | [104] |
Biosensor based on organic field effect transistor | Semiconducting polymer | SARS-CoV-2 S1 antigen | a sensitivity of 32%/dec and a LOD of 76.61 pg/mL for SARS-CoV-2 antigen detection | [105] |
Biosensor based on surface plasmon resonance | Polydopamine Ag nanoparticle | SARS-CoV-2 S1 antigen | Wide linear range of 0.0001 to 1000 ng/mL with a LOD of 12 fg/mL (S/N = 3) | [106] |
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Li, C.; Che, B.; Deng, L. Electrochemical Biosensors Based on Carbon Nanomaterials for Diagnosis of Human Respiratory Diseases. Biosensors 2023, 13, 12. https://doi.org/10.3390/bios13010012
Li C, Che B, Deng L. Electrochemical Biosensors Based on Carbon Nanomaterials for Diagnosis of Human Respiratory Diseases. Biosensors. 2023; 13(1):12. https://doi.org/10.3390/bios13010012
Chicago/Turabian StyleLi, Chunmei, Bo Che, and Linhong Deng. 2023. "Electrochemical Biosensors Based on Carbon Nanomaterials for Diagnosis of Human Respiratory Diseases" Biosensors 13, no. 1: 12. https://doi.org/10.3390/bios13010012
APA StyleLi, C., Che, B., & Deng, L. (2023). Electrochemical Biosensors Based on Carbon Nanomaterials for Diagnosis of Human Respiratory Diseases. Biosensors, 13(1), 12. https://doi.org/10.3390/bios13010012