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Aptamers and antibodies are compared as capture probes in a porous silicon-based optical biosensor for detection of a target protein.

This work describes the design of optical aptamer-based porous silicon (PSi) biosensors for the direct capture of Lactobacillus acidophilus. Aptamers are oligonucleotides (single-stranded DNA or RNA) that can bind their targets with high affinity and specificity, making them excellent recognition elements for biosensing applications. Herein, aptamer Hemag1P, which specifically targets the important probiotic L. acidophilus, was utilized for direct bacteria capture onto oxidized PSi Fabry-Pérot thin films. Monitoring changes in the reflectivity spectrum (using reflective interferometric Fourier transform spectroscopy) allows for bacteria detection in a label-free, simple and rapid manner. The performance of the biosensor was optimized by tuning the PSi nanostructure, its optical properties, as well as the immobilization density of the aptamer. We demonstrate the high selectivity and specificity of this simple "direct-capture" biosensing scheme and show its ability to distinguish between live and dead bacteria. The resulting biosensor presents a robust and rapid method for the specific detection of live L. acidophilus at concentrations relevant for probiotic products and as low as 10(6) cells per mL. Rapid monitoring of probiotic bacteria is crucial for quality, purity and safety control as the use of probiotics in functional foods and pharmaceuticals is becoming increasingly popular.

Porous silicon (PSi) nanomaterials have been widely studied as label-free optical biosensors for protein detection. However, these biosensors' performance, specifically in terms of their sensitivity (which is typically in the micromolar range), is insufficient for many applications. Herein, we present a proof-of-concept application of the electrokinetic isotachophoresis (ITP) technique for real-time preconcentration of a target protein on a PSi biosensor. With ITP, a highly concentrated target zone is delivered to the sensing area, where the protein target is captured by immobilized aptamers. The detection of the binding events is conducted in a label-free manner by reflective interferometric Fourier transformation spectroscopy (RIFTS). Up to 1000-fold enhancement in local concentration of the protein target and the biosensor's sensitivity are achieved, with a measured limit of detection of 7.5 nM. Furthermore, the assay is successfully performed in complex media, such as bacteria lysate samples, while the selectivity of the biosensor is retained. The presented assay could be further utilized for other protein targets, and to promote the development of clinically useful PSi biosensors.

Since the invention of the first biosensors 70 years ago, they have turned into valuable and versatile tools for various applications, ranging from disease diagnosis to environmental monitoring. Traditionally, antibodies have been employed as the capture probes in most biosensors, owing to their innate ability to bind their target with high affinity and specificity, and are still considered as the gold standard. Yet, the resulting immunosensors often suffer from considerable limitations, which are mainly ascribed to the antibody size, conjugation chemistry, stability, and costs. Over the past decade, aptamers have emerged as promising alternative capture probes presenting some advantages over existing constraints of immunosensors, as well as new biosensing concepts. Herein, we review the employment of antibodies and aptamers as capture probes in biosensing platforms, addressing the main aspects of biosensor design and mechanism. We also aim to compare both capture probe classes from theoretical and experimental perspectives. Yet, we highlight that such comparisons are not straightforward, and these two families of capture probes should not be necessarily perceived as competing but rather as complementary. We, thus, elaborate on their combined use in hybrid biosensing schemes benefiting from the advantages of each biorecognition element.

Microfluidic integration of biosensors enables improved biosensing performance and sophisticated lab-on-a-chip platform design for numerous applications. While soft lithography and polydimethylsiloxane (PDMS)-based microfluidics are still considered the gold standard, 3D-printing has emerged as a promising fabrication alternative for microfluidic systems. Herein, a 3D-printed polyacrylate-based microfluidic platform is integrated for the first time with a label-free porous silicon (PSi)–based optical aptasensor via a facile bonding method. The latter utilizes a UV-curable adhesive as an intermediate layer, while preserving the delicate nanostructure of the porous regions within the microchannels. As a proof-of-concept, a generic model aptasensor for label-free detection of his-tagged proteins is constructed, characterized, and compared to non-microfluidic and PDMS-based microfluidic setups. Detection of the target protein is carried out by real-time monitoring reflectivity changes of the PSi, induced by the target binding to the immobilized aptamers within the porous nanostructure. The microfluidic integrated aptasensor has been successfully used for detection of a model target protein, in the range 0.25 to 18 μM, with a good selectivity and an improved limit of detection, when compared to a non-microfluidic biosensing platform (0.04 μM vs. 2.7 μM, respectively). Furthermore, a superior performance of the 3D-printed microfluidic aptasensor is obtained, compared to a conventional PDMS-based microfluidic platform with similar dimensions. Graphical abstract

The ultimate detection limit of optical biosensors is often limited by various noise sources, including those introduced by the optical measurement setup. While sophisticated modifications to instrumentation may reduce noise, a simpler approach that can benefit all sensor platforms is the application of signal processing to minimize the deleterious effects of noise. In this work, we show that applying complex Morlet wavelet convolution to Fabry–Pérot interference fringes characteristic of thin film reflectometric biosensors effectively filters out white noise and low-frequency reflectance variations. Subsequent calculation of the average difference in extracted phase between the filtered analyte and reference signals enables a significant reduction in the limit of detection (LOD). This method is applied on experimental data sets of thin film porous silicon sensors (PSi) in buffered solution and complex media obtained from two different laboratories. The demonstrated improvement in the LOD achieved using wavelet convolution and average phase difference paves the way for PSi optical biosensors to operate with clinically relevant detection limits for medical diagnostics, environmental monitoring, and food safety.