In several fields including environmental monitoring, food manufacturing, and biomedical research, the ability to perform accurate measurements is key to a variety of studies.
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Whilst it is sufficient to make only a single measurement in some instances, such as glucose monitoring in a diabetic patient, some studies require measurements of multiple analytes.
Over the years, sophisticated technologies capable of performing multiplex measurements have been developed for this reason including gas chromatographs, HPLCs, and mass spectrometers.
A powerful new technology which can make the complex set of multiple measurements required by several different fields is the fiber optic microarray.
Fiber Optic Microarrays – An Overview of the Technology
There are limitations to contemporary measurement methods when faced with the need for multiple accurate measurements of a complex system. Both spectroscopic and chromatographic show limitations due to the fact that a complex mixture may contain analytes that overlap in their spectroscopic and separation properties.
Microarrays do not have such limitations. A typical microarray, or “lab-on-a-chip”, comprises a substrate with several different binding sites (features) deposited on it. The substrate used can be glass, silicon, nylon, or a variety of plastics.
Each feature has a unique binding specificity which allows multiple analytes in a mixture to be separated from each other and analyzed sequentially. Upon binding, a signal change occurs at the feature, which is detected via a transduction mechanism. The signal can be optical, electrochemical, thermal, or a change in mass.
In a fiber-optic microarray, optical fibers are used as the microarray substrate, as well as a detection method. Optical fibers are made of two different types of glass; a core glass surrounded by a glass cladding that has a lower refraction index.
This allows the fiber to transmit light over long distances with little attenuation. The sample is immobilized on one end of an optical fiber, then several fibers, each with a different immobilized sample probe on its tip, are bundled together.
When a ligand binds to the probe, fluorescence emission is triggered and detected by a CCD camera.
Applications of fiber optic microarrays
Fiber optic microarrays have been applied to many different research projects with multiple diagnostic aims. Some applications of the technology include the detection of harmful algal bloom species, analysis of proteins, cell migration, and DNA analysis.
Protein analysis
A protein detection assay based on enzyme-linked immune sorbent assays (ELISA) can be adapted to a fiber optic microarray format by immobilizing a capture antibody on the surface of a microbead and placing the microbead at the tip of the optic fiber. The detection antibody carrying the fluorophore will then bind to the capture antibody, activating a fluorescent emission.
Cell migration
Fiber optic microarrays can be used for cell migration assays by immobilizing the target proteins (fibronectin and collagen) that enable cell adhesion. The probe tips are then washed with fibroblast cells labeled with a fluorescent dye. Emission of a fluorescent signal occurs when anti-migratory substances are present in the cells.
DNA analysis
Fiber optic microarray technology is commonly uses in the analysis of DNA. Single-stranded DNA probes are attached to microspheres and affixed to the ends of the optic fibers. Fluorescently labeled single-stranded DNA samples are then placed on the microarray, and the optic fibers are monitored for fluorescence. Complementary DNA strands will hybridize to each other, showing that the target DNA sequence is present in the sample.
Detection of harmful algal bloom species
Algal blooms release toxins that can threaten coastal resources including fish and other organisms. In one study, a fiber optic microarray was used to detect organisms causing harmful algal blooms (HABs) using ribosomal RNA from several target species immobilized on microspheres to create a capture probe and placed in a microarray. The researchers then developed a sandwich immunoassay that was applied to the microarray and used to detect HAB organisms.
Artificial nose
Based on the mammalian olfactory system which has different clusters of cells able to recognize different scents, this unique approach to optical sensing has been developed in recent years.
Electronic noses have been around for over three decades which employ an array of cross-reactive sensors. However, these systems have one significant drawback: reproducibility. As they have to be replaced regularly due to loss of sensitivity over time, detector systems have to, in effect, be re-trained each time as the microarray cannot be reproduced exactly each time.
Fiber optic microarray-based artificial noses employ a solvatochromic dye added to microspheres which fluoresces at different wavelengths when certain odors are detected. After an initial “training” period for the microarray which involves exposure to a range of vapor analytes, algorithms are used to build up a library (effectively a “memory”) of odors and their associate response in the microarray. Algorithms employed are of many different types, but broadly fall into two categories: supervised and unsupervised. Fiber-optic microarray-based artificial noses are self-encoding.
A library of microspheres with different compositions and profiles is randomly distributed across the etched end of an optical fiber to build up the artificial nose. Different temporal response profiles are recognized and used to map the position of the microspheres on the array and once known, the microarray is used for analytical purposes.
Decoding, whilst still necessary, is much simpler with a fiber-optic microarray-based artificial nose than more traditional methods, which makes this system a much more reliable and reproducible one.
In Conclusion
Fiber optic microarrays are a dynamic new frontier in the measurement of complex molecular, biological, and environmental systems which are providing ever-more reliable data for a variety of industries that more contemporary modes of analysis have shortcomings in providing.
It is likely that they will continue to be developed in the future, bringing new ways to gather vital information on complex mixes of analytes in biological and chemical systems for many years to come.
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