The development of new and improvement of existing biosensors has been at the forefront of biochemistry for the last decade. With the idealistic biosensor being one that is highly accurate, simple and inexpensive. The cost and ease of use are often determinable by the design and inclusion of components of the biosensor. Therefore, when evaluating biosensors, their effectiveness is a key area to focus on. Two of the most prominent aspects of effectiveness used to compare biosensors are the limit of detection (LoD) and the dynamic range (1).
When discussing biological assays, the dynamic range can be defined as the highest measurable output of the biosensor to the lowest measurable output. The dynamic range is limited at the lower end by the LoD, whilst at the higher end, it is limited by sensor saturation. The single-site binding characteristic of molecular recognition biosensors means that the sensor surface can become saturated and so no binding sites are remaining. This produces a hyperbolic response curve, highlighting the dynamic range (2) (3).
Expanding the Dynamic Range
Expanding the dynamic range of a biosensor to allow the broader sensing of a target analyte would be a highly advantageous attribute to the sensor, however, it must not come at the cost of selectivity and sensitivity. Often, biosensors with extensive dynamic ranges exhibit poor precision, whilst very precise biosensors often have a very narrow dynamic range (3).
The ability to lower the limit of detection allows for more sensitive testing with the most minute concentrations of the target analyte detectable. This is particularly important in the monitoring of infectious diseases. Detection of tiny amounts of viral RNA could allow for better management of treatment and isolation to help contain the spread of such viruses. Alternatively, expanding the upper limit of the dynamic range allows more accurate testing where there are much larger differences in the target analyte between patients. This can often be the case when analysing males and females with the same disease. Expanding the dynamic range in this way would help eliminate the need for pre-test screening.
Clinical example – HIV and HCV
Recently, antiretroviral treatments for HIV have become more readily available, however, there continues to be an issue with quantifying viral loads at the point of care, without complex laboratory equipment. It is imperative to quantify the RNA concentrations of HIV at regular intervals in positive patients so to stop the spread of antiviral resistance. Though clinically relevant viral loads of HIV can occur over a very broad dynamic range, often spanning 5 orders of magnitude from 50 to 106 molecules/ml in a single sample (4).
Additionally, Hepatitis C virus (HCV) is one of the most common co-infections associated with HIV, with roughly a third of all HIV positive individuals having the co-infection. Similarly, the viral loads of HCV also have a vast dynamic range. Spanning from 50,000 to 5 million IU/ml (international units per ml) in a single sample. An HCV co-infection can affect the management of HIV and produce much more serious effects than that of an HIV negative individual.
Currently, the gold standard for quantifying viral loads of HIV and HCV is RT-PCR, due to its capabilities to accurately measure across a large dynamic range. However, this process requires trained personnel, performing cumbersome protocols using expensive laboratory equipment. Therefore, there is a high demand for a point of care test with a dynamic range that has a low enough limit of detection to accurately quantify the lowest concentrations and an upper range that does not saturate. Without this, patients at the most extreme ends of the scales could be missed (5).
How 3D Graphene Foam improves dynamic range
The development of biosensors with high sensitivity and low-detection limits provides a new direction for medical and personal care. Graphene is the ideal sensing material to prepare various types of biosensors due to its excellent sensing performance (e.g., high specific surface area, extraordinary electronic properties, electron transport capabilities and ultrahigh flexibility). Gii-Sens is able to help improve the dynamic range as it has a highly responsive surface with no signal saturation at high concentrations (still proportional to the analyte) and also it is responsive to produce distinctive signals at very low concentrations of the analyte.
If you would like to develop a next-generation assay and break through limits of detection in human diagnostics, contact us today.
- Gamba, J M. Biosensors. 2012.
- Biosensor-based engineering of biosynthetic pathways. Rogers, J K, Taylor, N D and Church, G M. s.l. : Current Opinion in Biotechnology, 2016, Vol. 42.
- Engineering Biosensors with Dual Programmable Dynamic Ranges. Wei, B, et al. 3, s.l. : Analytical Chemistry, 2018, Vol. 90.
- Engineering biosensors with extended, narrowed, or arbitrarily edited dynamic range. Vallee-Belisle, A, Ricci, F and Plaxco, K W. 6, s.l. : Journal of the American Chemcial Society, 2012, Vol. 134.
- Multiplexed quantification of nucleic acids with large dynamic range using multivolume digital RT-PCR on a rotational SlipChip tested with HIV and Hepatitis C viral load. Shen, F, et al. 44, s.l. : Journal of the American Chemical Society, 2011, Vol. 133.