Editorial Feature

Nanobiotechnology and Disease Detection

Acute kidney injury (AKI) results from a rise in serum creatinine levels, which is diagnosed using data from blood tests. Under normal conditions, the creatinine produced by the muscle tissue is filtered by the kidneys.

However, during excessive concentrations of creatinine in the blood, the kidneys fail to function causing harmful secondary conditions.

According to the Renal Association, an increase in serum creatinine over 354 μmol/L is regarded as a stage 3 classification of AKI. Serum creatinine serves as one of the main biomarkers for diagnosis of this medical condition and current efforts by researchers in the nanotechnology and sensor industry are working to improve ways on helping to improve methods for detection of an AKI.

Professor Srikanth Singamaneni made a major breakthrough with research which involves the use of metal nanoparticles to build a new biosensor for detecting an AKI. According to the research team, they had demonstrated a biosensor for detecting neutrophil gelatinase-associated lipocalin (NGAL) in urine, which is a biomarker for acute kidney injury.

Basic Principle

As medical diagnostics continue to develop, further enhancements will be made to devices used to detect disease. Surface-stress mechanical biosensors are designed to record a quasi-static deflection of a cantilever; i.e. in response to the binding of a biomolecule to a functional binding site to a target molecule on the device.

The deflection is measured by a laser beam and this gives an indication on the binding of a target molecule to the functional group on the device.

Use of Nanoparticles

Researchers are continuously looking for ways to improve the selectivity and sensitivity of biosensors. The application of nanorods with a cavity that takes the shape of desired function groups to a template molecule, is a significant step forward to achieve this goal. Under exposure to target molecules, the nanorod with the complementary functional groups to the molecule and will change its optical properties.

The biosensor was based on molecularly imprinted gold nanorods.  The detection limit of the plasmonic biosensor based on gold nanorods with built-in artificial antibodies was nearly 300 ng/ml, which was not quite sufficient for real-world applications.

Professor Srikanth Singamaneni, School of Engineering & Applied Science, Washington University

Molecularly Imprinted Gold Nanorods.

Molecularly Imprinted Gold Nanorods. Image Credit: Professor Srikanth Singamaneni, School of Engineering & Applied Science at Washington University.

This novel concept involves clusters of nanoparticles imprinted with antibodies that compliment a biomarker. By creating this biosensor, the research team aimed to understand the nature of the antibody–antigen interaction taking place in greater depth; and to use this information to fabricate optical sensors with high sensitivity levels for the target molecule.

We are aiming to improve the sensitivity of this biosensor to detect NGAL at a concentration of 50 ng per ml urine or lower by altering the plasmonic nanostructures or their state of assembly. Future efforts will also involve improving selectivity of the artificial antibodies by optimizing the non-covalent interactions between artificial antibodies and target proteins.  Progress on these goals will be followed by testing samples from patients with AKI and comparing it against current gold standard.

Professor Srikanth Singamaneni, School of Engineering & Applied Science, Washington University

It is quite apparent that nano-inspired biosensors offer a promising solution for greater sensitivity and selectivity in medical care. The issue of natural antibodies having a shorter shelf life also means that being able to overcome this challenge by introducing artificial antibodies is a major breakthrough and an important step in in the field of diagnostics.

What Does this Mean for Patients?

A highly sensitive and selective biosensor for the purpose of diagnostics may help reduce the length of time it takes to generate test results which could mean less waiting time for patients and practitioners. Of course, this means that prescriptions will not take as long to issue which is likely to reduce costs. The future of this technology is likely to involve using this diagnostic technique to help develop personalized medical treatment.

Sources and Further Reading

This article was updated on 14th February, 2020.

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