What is a biosensor?

A biosensor is a self-contained device with a chemical sensor where recognition occurs through a biochemical mechanism mediated which imparts a high degree of selectivity for the analyte.1

What is an electrochemical biosensor?

An electrochemical biosensor uses the recognition of the analyte in an electrochemical system capable of providing specific quantitative or semi-quantitative analytical information using a biological recognition element. This recognition induces an electrochemical change at the transducer surface.2,3 

Figure 1: Biosensor classification. This diagram was designed by Albert Longino, a wonderful and talented husband to the author shows the variety of analytes and recognition elements that can be mixed and matched in a variety of ways to create unique and versatile biosensors.

Classification of biosensors

Biosensors are commonly classified in two different ways: by the method of transduction or the biosensing interface. The biosensing element is classified into enzyme recognition 2,3,4 immunosensing (antibody/antigen)2,3,5 tissue6, ligand-protein receptors3, organelles7, whole cells3,9 aptamers or nucleic acid hybridization 3,10. Transducers are classified by the electrochemical mode implemented. The four categories of electrochemical detection are amperometric10, potentiometric11, voltammetric19, or impedimetric detection.2 Most transducers can work with most interfaces and vice versa, so it’s helpful to look at each separately to understand how the fundamentals of the biosensor can be adapted to the needs of the target analyte. See Figure 1

Method of transduction

In bioelectrochemistry, the investigated reaction either generates a measurable current (amperometry/voltammetry), a measurable change in potential or charge accumulation (potentiometry) or alters the conductivity of the medium (conductometry) between the working and reference electrodes. Additionally, impedimetric techniques measure the impedance (resistance and reactance) of the samples. 2,3,19 

Amperometric biosensors are known for their sensitivity and selectivity which are based on the unique recognition and redox reaction of the enzyme and its analyte. In amperometry and voltammetry techniques, the current is measured against an applied potential. The current is generated by the redox reaction occurring at the electrode surface and is limited by the mass transport of the analyte to the surface. In amperometry, the potential is stepped to the desired value and held throughout the experiment, either for single measurements or for flow analysis. In voltammetry, the potential is applied as a ramp and the current is monitored as the analyte is alternately reduced and then oxidized.12 These techniques are sensitive and have low limits of detection. Additionally, fixed potential techniques have low charging currents which lowers the background current. When tied to hydrodynamic experiments, mass transport to the electrode surface is enhanced, making amperometric flow techniques ideal for environmental monitoring.3 For more details on voltammetry, including the mathematics involved in these experiments, please see 12, 13, and 14.

Potentiometric methods are based on measuring the potential at low or null current. The potential responds to the changes in concentration of ions at a pH or ion-selective electrode surface. These become biosensors when enzymes change the pH or feed these ions to the electrode through their redox reactions. More in-depth discussions can be found in 11, 13, 15, and 16

Conductometry and electrochemical impedance spectroscopy (EIS) are two closely related techniques. Conductometometry measures the conductivity of solutions. Since enzymes change the local concentration of species close to the electrode surface, conductometry is ideal for enzyme-based sensors. Conductometry and EIS are both alternating current methods where small perturbations in the voltage are used. EIS is a much more layered technique. It can give information about the non-faradaic contributions to current, and also monitor degradative conditions in enzymatic biosensors. However, the theory and mathematics are detailed and complex. If the reader is interested, further discussions are held in 3, 17, 18, and 19.

Biosensing Interface

E-biosensors can also be divided into two groups based on their recognition mechanic. Biocatalysis is where the analyte recognition transforms the substrate into an electroactive, measurable bioproduct. Bioaffinity biosensors use selective and strong binding from antibodies, either receptor/agonist/antagonist (protein-based) or oligonucleotides (nucleic acid-based).1,3,29

Biocatalysis vs Bioaffinity

Biocatalytic sensors require a catalyzed reaction by a macromolecule. The macromolecule is either present in the original environment, previously isolated from its environment, or manufactured. The macromolecules alter the concentration of the analyte locally. The critical parameter of these sensors is the rate-limiting step, i.e. the mass-transport rate, versus the rate of analyte consumption. This means that continuous consumption of substrate is the primary mode of detection in steady-state conditions.2,3,29 The three most common biocatalysts incorporated into this system are enzymes,2,3 whole cells8, or tissues5.

Bioaffinity differs from biocatalysis in that it does not require catalysis to recognize the substrate and rather operates at equilibrium. Thus it is not subject to transport limitations. However, sensor response is related to the magnitude of their equilibrium constant and kinetics.  A bioaffinity sensor capable of rapid and reproducible regeneration, is referred to as a multi-use biosensor.2,3

There are two main designs for bioaffinity biosensors: Antibody/antigen interactions or receptor/antagonist/agonist interactions:

  • Antibody/antigen reactions are based on immunochemical responses (the binding of antigen, Ag to a specific antibody, Ab). Reaction conditions must be set where non-specific interactions are minimized. Because there is no change induced in the analyte, these recognition events occur at equilibrium. If the binding is irreversible then these are referred to as single-use sensors.1
  • Receptor/antagonist/agonist reactions are recognition events that occur outside the immune system, these can include immobilized ion channel receptors and agonists, membrane protein receptors, other binding proteins, and nucleic acid hybridization.2 For more information on DNA e-biosensors, please see reference9.

These bioaffinity biosensors are a promising avenue of research as they are cheaper than immunosensors, and could potentially recognize more analytes. They are not as well developed as immunosensors, in part because they are based on equilibrium reactions that have a narrow linear operating range. They frequently aren’t available for continuous monitoring of analyte concentration and also have difficulty operating in a complex biological matrix because the sensing layer must be in direct contact with the sample. This makes it vulnerable to sensor fouling from non-reactive components.1

Biosensing Design

Current biosensors use a wide variety of different strategies and different materials for the preparation of surfaces in biosensors. The most common surfaces are glass or other oxide surfaces as well as gold, microporous gold, graphite, glass carbon, and indium tin oxide (ITO).19

Immobilization of bioreceptors

Conducting polymers are frequently used to entrap enzymes or immobilize proteins, these include polyacrylonitrile20, agar21, polyurethane22, polypyrrole23, poly(vinyl) alcohol, sol-gels, or redox hydrogels. These polymers can be adsorbed to gold surfaces and provide good stability, redox recyclability, and ease of use. 19,24

Gold and other metallic surfaces are coated with Self-Assembled Monolayers (SAMs) of sulfides or disulfides (thiols or dithiols). The thiol end group is used for immobilization of the SAM. SAMs form highly ordered well-organized, and easily customizable structures that prevent nonspecific adsorption to the electrode surface, thereby lowering signal background and preventing sensor fouling. An exhaustive review is reference 25. Variable end groups (solution facing) are used as couplings for the biological recognition elements such as carboxyl groups for antibody immobilization, esters form amine couplings for proteins, biotin for streptavidin and other biomolecules as well as nucleic acids (NAs) for DNA, mRNA, or aptamers (for more details on aptamers see 26, 27, 28. A comprehensive review of DNA in electrochemical sensors review was written by Ferpertanova et al9. For more detailed information on e-biosensor architecture see reference 19.

Biosensing performance criteria

For any molecular recognition sensor, the operating parameters may indicate the rate-limiting steps (either transport or reaction) and optimization in a specific matrix. These parameters include the linear response or sensitivity, the linear concentration range, the response times, the sensor’s reproducibility, stability, as well as operational stability.2,25,31 For a review on the analytical figures of merit for biosensors please see reference 30

Biocatalytic biosensors are ultimately defined by their kinetics, i.e how quickly solution dynamics can deliver analyte to the immobilized enzyme, and how quickly reacted analyte is replaced by unreacted. 2,32

For bioaffinity sensors, a central issue is the capture capacity of the surface, the number or density of biologically active molecules on the surface. One method for assessing this parameter is the ratio of active molecules to total molecules when compared to the electrode’s surface area. This is very dependent on the mode of immobilization, orientation, number of recognition elements, etc. Capture capacity increases importance as the sensor size decreases, as with microfluidic applications.2,25 Improving the performance of these biosensors centers around improving signal gain, probe density, and probe flexibility. Kevin Plaxco’s research team has dedicated themselves to this issue and I encourage the reader to follow up with references 33 34, 35

The operational stability of a biosensor may vary due to the sensor’s geometry, preparation, receptor and transducer, and is strongly dependent upon the response rate-limiting factor. Operational stability requires the consideration of many different factors including analyte concentration, continuous or sequential contact of the biosensor with analyte solution, temperature, pH, buffer composition, presence of organic solvents, or sample matrix composition. Storage stability assessment requires the inclusion of parameters such as storage conditions, atmosphere conditions, pH, buffer composition, additives.2,25

Conclusion

Electrochemical biosensors are capable of providing selective and qualitative analytical information on a wide variety of analytes. They are sensitive, robust, and capable of being miniaturized into hand-held devices, bringing a diagnostics lab to the patient. They fall into two major categories depending on their recognition either biocatalyst or bio-affinity. Each category can be paired with different electrochemical techniques offering different advantages. The reader is encouraged to find more information in references 3–11, 15-17, 19, and 34.

References

  1. Nagel, B., H. Dellweg, and L. M. Gierasch. “Glossary for chemists of terms used in biotechnology (IUPAC Recommendations 1992).” Pure and Applied Chemistry 64.1 (1992): 143-168.
  2. Thevenot, Daniel R., et al. “Electrochemical biosensors: recommended definitions and classification.” Pure and applied chemistry 71.12 (1999): 2333-2348.
  3. Ronkainen, Niina J., H. Brian Halsall, and William R. Heineman. “Electrochemical biosensors.” Chemical Society Reviews 39.5 (2010): 1747-1763.
  4. Wang, Joseph. “Electrochemical glucose biosensors.” Chemical reviews 108.2 (2008): 814-825
  5. Ricci, Francesco, Gianluca Adornetto, and Giuseppe Palleschi. “A review of experimental aspects of electrochemical immunosensors.” Electrochimica Acta 84 (2012): 74-83.
  6. Wijesuriya, D. C., and G. A. Rechnitz. “Biosensors based on plant and animal tissues.” Biosensors and Bioelectronics 8.3-4 (1993): 155-160.
  7. Grattieri, Matteo, and Shelley D. Minteer. “Self-powered biosensors.” ACS sensors 3.1 (2018): 44-53.
  8. Lin, Baixue, and Yong Tao. “Whole-cell biocatalysts by design.” Microbial Cell Factories 16.1 (2017): 106.
  9. Ferapontova, Elena E. “DNA electrochemistry and electrochemical sensors for nucleic acids.” Annual Review of Analytical Chemistry 11 (2018): 197-218.
  10. Sadeghi, Jila. “Amperometric biosensors.” (2013): 61-67.
  11. Yunus, Sami, Alain M. Jonas, and Boris Lakard. “Potentiometric biosensors.” (2013).
  12. Elgrishi, Noémie, et al. “A practical beginner’s guide to cyclic voltammetry.” Journal of Chemical Education 95.2 (2018): 197-206.
  13. Bard, Allen J., and Larry R. Faulkner. “Fundamentals and applications.” Electrochemical Methods 2.482 (2001): 580-632.
  14. Stephens, Lisa I., and Janine Mauzeroll. “Demystifying Mathematical Modeling of Electrochemical Systems.” Journal of Chemical Education 96.10 (2019): 2217-2224.
  15. ANALYTICAL CHEMISTRY, VOL. 59, NO. 18, SEPTEMBER 15, 1987
  16. Pisoschi, Aurelia Magdalena. “Potentiometric biosensors: concept and analytical applications-an editorial.” Biochem Anal Biochem 5.3 (2016): 19-20.
  17. Smith, S., 2021. Lecture 3: Introduction To Electrochemical Biosensing. [online] Homepages.ed.ac.uk. Available at: <http://www.homepages.ed.ac.uk/ssmith13/course/lecture3_files/Lecture%203%20Notes.pdf> [Accessed 15 January 2021].
  18. Orazem, Mark E., and Bernard Tribollet. “Electrochemical impedance spectroscopy.” New Jersey (2008).
  19. Grieshaber, Dorothee, et al. “Electrochemical biosensors-sensor principles and architectures.” Sensors 8.3 (2008): 1400-1458.
  20. Xue, Huaiguo, Zhiquan Shen, and Chunmei Li. “Improved selectivity and stability of glucose biosensor based on in situ electropolymerized polyaniline–polyacrylonitrile composite film.” Biosensors and Bioelectronics 20.11 (2005): 2330-2334.
  21. Zucca, Paolo, Roberto Fernandez-Lafuente, and Enrico Sanjust. “Agarose and its derivatives as supports for enzyme immobilization.” Molecules 21.11 (2016): 1577.
  22. Sassolas, Audrey, Loïc J. Blum, and Béatrice D. Leca-Bouvier. “Immobilization strategies to develop enzymatic biosensors.” Biotechnology advances 30.3 (2012): 489-511.
  23. Geetha, S., et al. “Biosensing and drug delivery by polypyrrole.” Analytica Chimica Acta 568.1-2 (2006): 119-125.
  24. Ansari, Shakeel Ahmed, and Qayyum Husain. “Potential applications of enzymes immobilized on/in nano materials: A review.” Biotechnology advances 30.3 (2012): 512-523.
  25. Love, J. Christopher, et al. “Self-assembled monolayers of thiolates on metals as a form of nanotechnology.” Chemical reviews 105.4 (2005): 1103-1170.
  26. Ellington, Andrew D., and Jack W. Szostak. “In vitro selection of RNA molecules that bind specific ligands.” nature 346.6287 (1990): 818-822.
  27. Tuerk, Craig, and Larry Gold. “Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase.” science 249.4968 (1990): 505-510.
  28. Song, Shiping, et al. “Aptamer-based biosensors.” TrAC Trends in Analytical Chemistry 27.2 (2008): 108-117.
  29. Rocchitta, Gaia, et al. “Enzyme biosensors for biomedical applications: Strategies for safeguarding analytical performances in biological fluids.” Sensors 16.6 (2016): 780.
  30. Justino, Celine IL, Teresa A. Rocha-Santos, and Armando C. Duarte. “Review of analytical figures of merit of sensors and biosensors in clinical applications.” TrAC Trends in Analytical Chemistry 29.10 (2010): 1172-1183.
  31. Bhalla, Nikhil et al. “Introduction to biosensors.” Essays in biochemistry vol. 60,1 (2016): 1-8. doi:10.1042/EBC20150001
  32. Tang, L. X., and P. Vadgama. “Optimisation of enzyme electrodes.” Medical and Biological Engineering and Computing 28.3 (1990): B18.
  33. White, Ryan J., et al. “Optimization of electrochemical aptamer-based sensors via optimization of probe packing density and surface chemistry.” Langmuir 24.18 (2008): 10513-10518.
  34. Dauphin-Ducharme, Philippe, and Kevin W. Plaxco. “Maximizing the signal gain of electrochemical-DNA sensors.” Analytical chemistry 88.23 (2016): 11654-11662.
  35. Lubin, Arica A., and Kevin W. Plaxco. “Folding-based electrochemical biosensors: the case for responsive nucleic acid architectures.” Accounts of Chemical Research 43.4 (2010): 496-505.