| Literature DB >> 34334850 |
Asifur Rahman1, Seju Kang1, Wei Wang1, Aditya Garg2, Ayella Maile-Moskowitz1, Peter J Vikesland1.
Abstract
The impacts of the ongoing coronavirus pandemic highlight the importance of environmental monitoring to inform public health safety. Wastewater based epidemiology (WBE) has drawn interest as a tool for analysis of biomarkers in wastewater networks. Wide scale implementation of WBE requires a variety of field deployable analytical tools for real-time monitoring. Nanobiotechnology enabled sensing platforms offer potential as biosensors capable of highly efficient and sensitive detection of target analytes. This review provides an overview of the design and working principles of nanobiotechnology enabled biosensors and recent progress on the use of biosensors in detection of biomarkers. In addition, applications of biosensors for analysis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus are highlighted as they relate to the potential expanded use of biosensors for WBE-based monitoring. Finally, we discuss the opportunities and challenges in future applications of biosensors in WBE for effective monitoring and investigation of public health threats.Entities:
Keywords: Biomarkers; Biosensors; COVID-19; Electrochemical sensing; Nanobiotechnology; Nucleic acid based diagnostic tools; SARS-CoV-2; SERS; Wastewater-based epidemiology
Year: 2021 PMID: 34334850 PMCID: PMC8317456 DOI: 10.1016/j.trac.2021.116400
Source DB: PubMed Journal: Trends Analyt Chem ISSN: 0165-9936 Impact factor: 14.908
Main classes and representatives of WBE targets.
| WBE targets | Representative contaminants | References |
|---|---|---|
| [ | ||
| Heavy metals ions | Cd, Cr, Cu, Hg, Ni, Pb, Zn | |
| Nonmetallic ions | sulfate, phosphate, chloride, perchlorate, nitrate, nitrite, fluoride, arsenate | |
| [ | ||
| Pesticides | atrazine, carbendazim, diazinon, diuron, glyphosate, isoproturon | |
| Pharmaceuticals and personal care products (PPCPs) | ibuprofen, caffeine, ciprofloxacin, metronidazole, musk ketone, triclosan, octocrylene | |
| Endocrine disruptors compounds (EDCs) | estrone, bisphenol A, progesterone, estriol, 17-β-estradiol | |
| Polycyclic aromatic hydrocarbons (PAHs) | anthracene, acenaphthene, fluoranthene, fluorene, naphthalene | |
| Surfactants | linear alkylbenzene, secondary alkane sulfonate, alkyl sulfate, perfluorooctanoic acid | |
| Industry emitted synthetic dyes | acridine orange, Sudan I, neutral red, methylene blue, rhodamine B, malachite green | |
| [ | ||
| Microorganisms | ||
| Viruses | coronavirus, adenovirus, noroviruses, hepatitis A virus, sapovirus | |
| Pathogenic genetic material | pathogenic DNA/RNA | |
| Antibiotic resistance genes | ||
| [ | ||
| Disinfection by products (DBPs) | trihalomethanes, haloacetic acids, haloacetonitriles, haloacetamides | |
| Microplastics | ||
Fig. 1Schematic illustration of the components involved when designing nanobiotechnology-enabled sensors. At first, the potential biomarker of interest is selected for detection. Next comes the sensor design step. The design of biosensor involves the selection of core materials, target specific recognition elements and one or more signal transduction methods. The nucleic acid based diagnostic tools can be applied for both indirect sensing using a separate instrument (e.g., amplification of target genes for subsequent detection), or direct sensing by incorporating the tools into the sensor platform. Finally, sensor is deployed using an implementation technique (image created with https://biorender.com).
Summary of previous studies on the application of biosensors.
| Type of biomarker | Recognition element | Output Signal | Sample Matrix | Limit of detection (LOD) | References |
|---|---|---|---|---|---|
| Bacterial (MRSA) DNA | Aptamer | Optical/magnetic | Clinical sample | 10 fg/μL | [ |
| Viral RNA (SARS-CoV-2) | Aptamer | Optical | Clinical sample | – | [ |
| Viral RNA (SARS-CoV-2) | Aptamer | Optical | Wastewater | 14.6, 2, and 2.18 copies/20 μL for SARS-CoV-2 N1, N2, and N3 | [ |
| Viral RNA (SARS-CoV-2) | Aptamer | Optical | Wastewater | 58 copies/100 mL | [ |
| DNA (ARGs) | Aptamer | Optical | Wastewater | – | [ |
| Viral RNA (SARS-CoV-2) | Aptamer | Optical | Clinical sample | 80 copies/mL | [ |
| DNA (mtDNA) | Aptamer | Optical | Wastewater | 40 copies/20 μL | [ |
| Viral RNA (SARS-CoV-2) | Aptamer | Optical | Wastewater | – | [ |
| Viral RNA (SARS-CoV-2) | Aptamer | Electrical | Clinical sample | – | [ |
| Bacteria ( | Aptamer | Optical | Cell medium extracts | 1 CFU/mL | [ |
| Viral RNA (SARS-CoV-2) | Aptamer | Optical | Clinical sample | 10 copies/10 μL | [ |
| Antibiotic Resistant Bacteria | Antibody, protein | Optical/magnetic | DI water | 101 CFU/mL | [ |
| Bacteria | Nanomaterial (Au nanorods) | Optical | DI water | – | [ |
| Virus (adenovirus, rhinovirus, and HIV) | Nanomaterial (Ag nanorod arrays) | Optical | DI water | 100 PFU/mL | [ |
| Viral RNA (SARS-CoV-2) | Aptamer | Optical | DI water | 5.5 × 104 TCID50/mL | [ |
| Viral protein (SARS-CoV-2) | Aptamer | Optical | DI water | 250 nM | [ |
| Virus (H1N1) | Aptamer | Optical | DI water | 97 PFU/mL | [ |
| Protein biomarker | Antibody | Optical | Blood plasma | 0.86 ng/mL | [ |
| Virus (H1N1, adenovirus) | Antibody | Optical/magnetic | PBS, blood, serum, and sputum | 50 PFU/mL (H1N1), | [ |
| Virus (H5N2, HPIV 3) | Aligned carbon nanotube | Optical | Clinical sample | 102 EID50/mL (50% egg infective dose per microliter) | [ |
| Human prostate cells | Wheat germ agglutinin | Optical | Cell medium | – | [ |
| Virus (Hep B) | Antibody | Optical | Human blood plasma | 0.01 IU/mL | [ |
| Virus (SARS-CoV-2) | Antibody | FET | Culture medium and clinical samples | 1.6 × 101 PFU/mL in culture medium, 2.42 × 102 copies/ml in clinical samples | [ |
| Viral RNA (SARS-CoV-2) | DNA probe | Electrochemical | Clinical sample | 6.9 copies/μL | [ |
| Viral RNA (Hep C) | Peptide | SEC | 10 mM PBS | 264.5 IU/mL | [ |
| Viral protein (H5N1) | Primary and secondary antibodies | SEC | Clinical samples | 4 ng/mL, or 77 pM | [ |
Fig. 2(A) The workflow of extraction and detection of the genomic population biomarker, mtDNA, in wastewater using LAMP and lateral flow device (Reprinted with permission from Ref. [28]); (B) The illustration of the highly scalable detection of SARS-CoV-2 in the swab samples using Illumina sequencing of combinatorial RT-LAMP-PCR barcoded amplicons (Reprinted with permission from Ref. [31]); (C) Four-channel multiplexed CRISPR-Cas system for detection of nucleic acids with orthogonal CRISPR enzymes: PsmCas13b, LwaCas13a, CcaCas13b, and AsCas12a for dsDNA target (Reprinted with permission from Ref. [34]).
Fig. 3(A) Detection of bacteria using a liquid SERS platform (Reprinted with permission from Ref. [38]); (B) Illustration showing the detection of the protein biomarker, neuron specific enolase (NSE) in blood plasma using a paper based lateral flow strip (PLFS) immunoassay (Reprinted with permission from Ref. [45]); (C) a microfluidic platform for the capture of avian influenza A viruses from clinical samples and rapid label-free SERS identification (Reprinted with permission from Ref. [47]); (D) The captured viruses on the chip are (i) immunostained, then (ii) propagated via cell culture and are finally (iii) genome sequenced for identification of subtypes (Reprinted with permission from Ref. [47]); (E) Application of a SERS based lateral flow immunoassay (LFIA) for detection of Influenza A H1N1 virus and human adenovirus (Reprinted with permission from Ref. [46]).
Fig. 4(A) The illustration of the detection of SARS-CoV-2 via FET nanobiosensors with graphene transducers modified with an antibody specific for the SARS-CoV-2 spike protein (Reprinted with permission from Ref. [54]); (B) The illustration of the rapid detection of SARS-CoV-2 viral RNA using an electrochemical sensor made of graphene and gold nanoparticles modified with antisense oligonucleotides (Reprinted with permission from Ref. [56]).
Summarized key information on the applicability of different sensing platforms.
| Technique | Advantages | Disadvantages | Potential for WBE Applications | Challenges in implementation | References |
|---|---|---|---|---|---|
| Indirect sensing (PCR, LAMP, genome sequencing and CRISPR) | Most commonly used for detecting nucleic acids; Precise and sensitive detection; Established protocols and standards. | Require centralized facilities, specialized equipment, and trained personnel; High cost; Time consuming. | Established methods for nucleic acid detection; Detection of SARS-CoV-2 RNA; Analysis of complex matrices (e.g., wastewater, biofluids). | False negatives; Interpretation of findings in terms of disease propagation and human health risks; Variability of strains in samples vs reference strains. | [ |
| SERS based sensing (liquid SERS, paper-based SERS, microfluidic SERS, magnetic SERS) | Rapid, highly sensitive and low-cost detection; Wide range of SERS nanotags are already available; Great potential for field deployment. | Requires plasmonic substrates; Nanomaterial and SERS tag orientation induce large variability in scattering response. | Single molecule detection capability; Detection at environmentally relevant concentrations; Low-cost SERS active substrates for wastewater monitoring; Field diagnosis using handheld Raman systems. | Heterogeneity of SERS substrates; Weak SERS signals and similarity of SERS profiles of biomolecules require additional data analysis; Reproducibility; Detection at sub nanomolar concentrations in complex media (e.g., wastewater, biofluids). | [ |
| Electrical approaches (FET sensing, electrochemical sensing) | Rapid, highly sensitive, low cost and real-time detection; Simple and portable instrumentation; Electrical signals unaffected by factors such as sample turbidity or interference from fluorescing compounds. | Low stability and reproducibility in physiological environments; Reduced sensitivity and specificity due to non-specific adsorption of interfering species. | Detection at environmentally relevant concentrations; Easy lab on a chip integration due to low power requirements; Portable instrumentation and compatibility with microfabrication technology for on-site analysis; Real-time detection with simple operation. | Operation in complex media (e.g., wastewater, biofluids) has several challenges including non-specific adsorption of interfering molecules, Debye screening effect in FET nanosensors, and stability of electrochemical signals under changing physiological conditions. | [ |
| Combined approaches (SEC sensing) | Highly sensitive and selective due to simultaneous acquisition of complementary electrochemical and spectroscopic data; Improved spectroscopic modality (e.g., SERS). | Requires advanced understanding of SEC mechanisms for accurate data interpretation; Incident light beam can affect the electrochemical results. | Single molecule detection capability; Overlapping signals of interfering molecules can be resolved using complementary data allowing detection in complex media (e.g., wastewater, biofluids). | Reproducibility of devices (e.g., EC-SERS substrates); Complex data interpretation and analysis; Improvement and miniaturization of instrumentation for on-site analysis | [ |