Theory and applications of surface plasmon resonance, resonant mirror, resonant waveguide grating, and dual polarization interferometry biosensors

Topology Optimization Enables High-Q Metasurface for Color Selectivity

Nonlocal metasurfaces, exemplified by resonant waveguide gratings (RWGs), spatially and angularly configure optical wavefronts through narrow-band resonant modes, unlike the broad-band and broad-angle responses of local metasurfaces. However, forward design techniques for RWGs remain constrained at lower efficiency. Here, we present a topology-optimized metasurface resonant waveguide grating (MRWG) composed of titanium dioxide on a glass substrate capable of operating simultaneously at red, yellow, green, and blue wavelengths. Through adjoint-based topology optimization, while considering nonlocal effects, we significantly enhance its diffraction efficiency, achieving numerical efficiencies up to 78% and Q-factors as high as 1362. Experimentally, we demonstrated efficiencies of up to 59% with a Q-factor of 93. Additionally, we applied our topology-optimized metasurface to color selectivity, producing vivid colors at 4 narrow-band wavelengths. Our investigation represents a significant advancement in metasurface technology, with potential applications in see-through optical combiners and augmented reality platforms.

Grating Structures for Silver-Based Surface Plasmon Resonance Sensors with Adjustable Excitation Angle

Silver-based grating structures offer means for implementing low-cost, efficient grating couplers for use in surface plasmon resonance (SPR) sensors. One-dimensional grating structures with a fixed periodicity are confined to operate effectively within a single planar orientation. However, two-dimensional grating structures as well as grating structures with variable periodicity allow for the plasmon excitation angle to be seamlessly adjusted. This study demonstrates silver-based grating designs that allow for the plasmon excitation angle to be adjusted via rotation or beam position. The flexible angle adjustment opens up the possibility of developing SPR sensor designs with an expanded dynamic range and increased flexibility in sensing applications. The results demonstrate that efficient coupling into two diffraction orders is possible, which ultimately leads to an excitation angle range from 16° to 40° by rotating a single structure. The findings suggest a promising direction for the development of versatile and adaptable SPR sensing platforms with enhanced performance characteristics.

Bending of Lloyd's mirror to eliminate the period chirp in the fabrication of diffraction gratings

We present a new technique to prevent the detrimental period chirp that appears in optical gratings fabricated by laser interference lithography (LIL). The idea is to bend the Lloyd's mirror in the lithographic setup to eliminate the period chirp already at the step of the grating's exposure. A new mathematical model was developed to describe the required bending geometry of the mirror. It is shown that this geometry can be described by multiple cross-sections of the mirror, each obtained by the solution of an implicit first-order differential equation. The proposed approach is illustrated on the basis of a concrete example. By slightly bending the Lloyd's mirror (by ≈ 3.5 mm of maximum deflection over an area of 142 mm × 215 mm) the period chirp of the exposed grating can be eliminated completely.

Surface-Plasmon-Resonance Amplification of FMD Detection through Dendrimer Conjugation

The amplification of the surface plasmon resonance (SPR) sensitivity for the foot-and-mouth disease (FMD) detection was studied using Poly(amidoamine) (PAMAM) succinamic-acid dendrimers. The dendrimers were conjugated with the complementary annealed with the aptamers capable of binding specifically to FMD peptides. The tethered layer of the dendrimer-conjugated double-stranded(ds)-aptamers was formed on the SPR sensor Au surface via a thiol bond between the aptamers and Au. After the tethered layer was formed, the surface was taken out of the SPR equipment. Then, the ds-aptamers on the surface were denatured to collect the dendrimer-conjugated single-stranded(ss)-complementary. The surface with only the remaining ss-aptamers was transferred again to the equipment. Two types of the injections, the FMD peptide only and the dendrimer-conjugated ss-complementary followed by the FMD peptides, were performed on the surface. The sensitivity was increased 20 times with the conjugation of the dendrimers, but the binding rate of the peptides became more than two times slower.

Fenpicoxamid-Imprinted Surface Plasmon Resonance (SPR) Sensor Based on Sulfur-Doped Graphitic Carbon Nitride and Its Application to Rice Samples

This research attempt involved the development and utilization of a newly designed surface plasmon resonance (SPR) sensor which incorporated sulfur-doped graphitic carbon nitride (S-g-C3N4) as the molecular imprinting material. The primary objective was to employ this sensor for the quantitative analysis of Fenpicoxamid (FEN) in rice samples. The synthesis of S-g-C3N4 with excellent purity was achieved using the thermal poly-condensation approach, which adheres to the principles of green chemistry. Afterwards, UV polymerization was utilized to fabricate a surface plasmon resonance (SPR) chip imprinted with FEN, employing S-g-C3N4 as the substrate material. This process involved the inclusion of N,N'-azobisisobutyronitrile (AIBN) as the initiator, ethylene glycol dimethacrylate (EGDMA) as the cross-linker, methacryloylamidoglutamic acid (MAGA) as the monomer, and FEN as the analyte. After successful structural analysis investigations on a surface plasmon resonance (SPR) chip utilizing S-g-C3N4, which was imprinted with FEN, a comprehensive investigation was conducted using spectroscopic, microscopic, and electrochemical techniques. Subsequently, the kinetic analysis applications, namely the determination of the limit of quantification (LOQ) and the limit of detection (LOD), were carried out. For analytical results, the linearity of the FEN-imprinted SPR chip based on S-g-C3N4 was determined as 1.0-10.0 ng L-1 FEN, and LOQ and LOD values were obtained as 1.0 ng L-1 and 0.30 ng L-1, respectively. Finally, the prepared SPR sensor's high selectivity, repeatability, reproducibility, and stability will ensure safe food consumption worldwide.

Recent Developments in the Detection of Organic Contaminants Using Molecularly Imprinted Polymers Combined with Various Analytical Techniques

Molecularly imprinted polymers (MIPs) encompass a diverse array of polymeric matrices that exhibit the unique capacity to selectively identify a designated template molecule through specific chemical moieties. Thanks to their pivotal attributes, including exceptional selectivity, extended shelf stability, and other distinct characteristics, this class of compounds has garnered interest in the development of highly responsive sensor systems. As a result, the incorporation of MIPs in crafting distinctive sensors and analytical procedures tailored for specific analytes across various domains has increasingly become a common practice within contemporary analytical chemistry. Furthermore, the range of polymers amenable to MIP formulation significantly influences the potential utilization of both conventional and innovative analytical methodologies. This versatility expands the array of possibilities in which MIP-based sensing can be employed in recognition systems. The following review summarizes the notable progress achieved within the preceding seven-year period in employing MIP-based sensing techniques for analyte determination.

Observation of Coherent Perfect Absorption in Oil Film on Water Surface and Sensitive Detection of Refractive Index Anisotropy in the Film

Sharp reflection dips of 50% were observed when white light was incident from the side of a cell on a 1 μm thick film of silicone oil (polydimethylsiloxane, PDMS, nearly transparent in visible light, with the extinction coefficient κ ≈ 0.0001) above a water surface in the cell so that the total reflection condition was satisfied at the oil-air interface. This is the first observation of a coherent perfect absorption (CPA) phenomenon in liquid. The experimental results can be reproduced by the Fresnel reflectance of the monolayer film, but the wavelength positions at which the dip appears for s-polarized and p-polarized light are reversed if the refractive index of the oil film is assumed to be isotropic. The experimental results were correctly reproduced by assuming that the extraordinary-ray refractive index (light polarized perpendicular to the interface) is 1% larger than the ordinary-ray refractive index (light polarized parallel to the interface). This indicates that the polarization dependence of the CPA phenomenon is extremely sensitive to the difference between the in-plane and out-of-plane refractive indices of the thin film.

Microprobe-Capture In-Emitter Elution: An Affinity Capture Technique to Directly Couple a Label-Free Optical Sensing Technology with Mass Spectrometry for Protein Analysis

Affinity capture of an analyte by a capture agent is one of the most effective sample preparation approaches in mass spectrometry (MS), especially top-down MS. We describe a new affinity capture technique for protein targets, called microprobe-capture in-emitter elution (MPIE), which can directly couple a label-free optical sensing technology (next-generation biolayer interferometry, BLI) with MS. To implement MPIE, an analyte is first captured on the surface of a microprobe and subsequently eluted from the microprobe inside an electrospray emitter. The capture process is monitored in real-time via BLI. When electrospray is established from the emitter to a mass spectrometer, the analyte is immediately ionized via electrospray ionization (ESI) for MS analysis. By this means, BLI and MS are directly coupled in the form of MPIE-ESI-MS. The performance of MPIE-ESI-MS was demonstrated by the analysis of β-amyloid 1-40 and transferrin using both standard samples and human specimens. In comparison to conventional affinity capture techniques such as bead-based immunoprecipitation, MPIE innovates the affinity capture methodology by introducing real-time process monitoring and providing binding characteristics of analytes, offering more information-rich experiment results. Thus, MPIE is a valuable addition to the top-down MS sample preparation toolbox, and MPIE-ESI-MS can be useful for identification and characterization of targets of interest.

C-band operating plasmonic sensor with a high Q-factor/figure of merit based on a silicon nano-ring

In this paper, we take advantage of the high refractive index property of silicon to design a practical and sensitive plasmonic sensor on a photonic integrated circuit (PIC) platform. It has been demonstrated that a label-free refractive index sensor with sensitivity up to 1124 nm/RIU can be obtained using a simple design of a silicon nano-ring with a concentric hexagonal plasmonic cavity. It has also been shown that, with optimum structural parameters, a quality factor (Q-factor) of 307 and a figure of merit (FOM) of 234R I U ^-1 can be achieved, which are approximately 8 times and 5 times higher than the proposed sensors counterparts, respectively. In addition, the resonance mode of the hexagonal cavity with Si nano-ring (HCS) sensor can be adjusted to operate in the C-band, which is a highly desirable wavelength range in terms of compatibility with devices in PIC technology.

Graphene-on-gold surface plasmon resonance sensors resilient to high-temperature annealing

Gold films coated with a graphene sheet are being widely used as sensors for the detection of label-free binding interactions using surface plasmon resonance (SPR). During the preparation of such sensors, it is often essential to subject the sensor chips to a high-temperature treatment in order to ensure a clean graphene surface. However, sensor chips used currently, which often use chromium as an adhesion promoter, cannot be subjected to temperatures above 250 °C, because under such conditions, chromium is found to reorganize and diffuse to the surface, where it is easily oxidized, impairing the quality of SPR spectra. Here we present an optimized preparation strategy involving a three-cycle tempering coupled with chromium (oxide) etching, which allows the graphene-coated SPR chips to be annealed up to 500 °C with little deterioration of the surface morphology. In addition, the treatment delivers a surface that shows a clear enhancement in spectral response together with a good refractive index sensitivity. We demonstrate the applicability of our sensors by studying the kinetics of avidin-biotin binding at different pH repeatedly on the same chip. The possibility to anneal can be exploited to recover the original surface after sensing trials, which allowed us to reuse the sensor for at least six cycles of biomolecule adsorption.

Metal-Chelating Peptides Separation Using Immobilized Metal Ion Affinity Chromatography: Experimental Methodology and Simulation

Metal-Chelating Peptides (MCPs), obtained from protein hydrolysates, present various applications in the field of nutrition, pharmacy, cosmetic etc. The separation of MCPs from hydrolysates mixture is challenging, yet, techniques based on peptide-metal ion interactions such as Immobilized Metal Ion Affinity Chromatography (IMAC) seem to be efficient. However, separation processes are time consuming and expensive, therefore separation prediction using chromatography modelling and simulation should be necessary. Meanwhile, the obtention of sorption isotherm for chromatography modelling is a crucial step. Thus, Surface Plasmon Resonance (SPR), a biosensor method efficient to screen MCPs in hydrolysates and with similarities to IMAC might be a good option to acquire sorption isotherm. This review highlights IMAC experimental methodology to separate MCPs and how, IMAC chromatography can be modelled using transport dispersive model and input data obtained from SPR for peptides separation simulation.

Handheld, Low-Cost, Aptamer-Based Sensing Device for Rapid SARS-CoV-2 RNA Detection Using Novelly Synthesized Gold Nanoparticles

The development of a cost-efficient device to rapidly detect pandemic viruses is paramount. Hence, an innovative and scalable synthesis of metal nanoparticles followed by its usage for rapid detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been reported in this work. The simple synthesis of metal nanoparticles utilizing tin as a solid-state reusable reducing agent is used for the SARS-CoV-2 ribonucleic acid (RNA) detection. Moreover, the solid-state reduction process occurs faster and leads to the enhanced formation of silver and gold nanoparticles (AuNPs) with voltage. By adding tin as a solid-state reducing agent with the precursor, the nanoparticles are formed within 30 s. This synthesis method can be easily scaled up for a commercially viable process to obtain different-sized metal nanoparticles. This is the first disclosure of the usage of tin as a reusable solid-state reducing agent for metal nanoparticle synthesis. An electronic device, consisting of AuNPs functionalized with a deoxyribonucleic acid (DNA)-based aptamer, can detect SARS-CoV-2 RNA in less than 5 min. With an increase in SARS-CoV-2 variants, such as Delta and Omicron, the detection device could be used for identifying the nucleic acids of the COVID-19 variants by modifying the aptamer sequence. The reported work overcomes the drawbacks of complex instrumentation, trained labor, and increased turnaround time.

Biomedical Applications of an Ultra-Sensitive Surface Plasmon Resonance Biosensor Based on Smart MXene Quantum Dots (SMQDs)

In today’s world, the use of biosensors occupies a special place in a variety of fields such as agriculture and industry. New biosensor technologies can identify biological compounds accurately and quickly. One of these technologies is the phenomenon of surface plasmon resonance (SPR) in the development of biosensors based on their optical properties, which allow for very sensitive and specific measurements of biomolecules without time delay. Therefore, various nanomaterials have been introduced for the development of SPR biosensors to achieve a high degree of selectivity and sensitivity. The diagnosis of deadly diseases such as cancer depends on the use of nanotechnology. Smart MXene quantum dots (SMQDs), a new class of nanomaterials that are developing at a rapid pace, are perfect for the development of SPR biosensors due to their many advantageous properties. Moreover, SMQDs are two-dimensional (2D) inorganic segments with a limited number of atomic layers that exhibit excellent properties such as high conductivity, plasmonic, and optical properties. Therefore, SMQDs, with their unique properties, are promising contenders for biomedicine, including cancer diagnosis/treatment, biological sensing/imaging, antigen detection, etc. In this review, SPR biosensors based on SMQDs applied in biomedical applications are discussed. To achieve this goal, an introduction to SPR, SPR biosensors, and SMQDs (including their structure, surface functional groups, synthesis, and properties) is given first; then, the fabrication of hybrid nanoparticles (NPs) based on SMQDs and the biomedical applications of SMQDs are discussed. In the next step, SPR biosensors based on SMQDs and advanced 2D SMQDs-based nanobiosensors as ultrasensitive detection tools are presented. This review proposes the use of SMQDs for the improvement of SPR biosensors with high selectivity and sensitivity for biomedical applications.

A review on the contamination of SARS-CoV-2 in water bodies: Transmission route, virus recovery and recent biosensor detection techniques

The discovery of SARS-CoV-2 virus in the water bodies has been reported, and the risk of virus transmission to human via the water route due to poor wastewater management cannot be disregarded. The main source of the virus in water bodies is the sewage network systems which connects to the surface water. Wastewater-based epidemiology has been applied as an early surveillance tool to sense SARS-CoV-2 virus in the sewage network. This review discussed possible transmission routes of the SARS-CoV-2 virus and the challenges of the existing method in detecting the virus in wastewater. One significant challenge for the detection of the virus is that the high virus loading is diluted by the sheer volume of the wastewater. Hence, virus preconcentration from water samples prior to the application of virus assay is essential to accurately detect traceable virus loading. The preparation time, materials and conditions, virus type, recovery percentage, and various virus recovery techniques are comprehensively discussed in this review. The practicability of molecular methods such as Polymer-Chain-Reaction (PCR) for the detection of SARS-CoV-2 in wastewater will be revealed. The conventional virus detection techniques have several shortcomings and the potential of biosensors as an alternative is also considered. Biosensing techniques have also been proposed as an alternative to PCR and have reported detection limits of 10 pg/μl. This review serves to guide the reader on the future designs and development of highly sensitive, robust and, cost effective SARS-CoV-2 lab-on-a-chip biosensors for use in complex wastewater.

Coherent Perfect Absorption of a Transparent Polymer Film on a Transparent Substrate Utilizing Total Internal Reflection by Grazing Incidence

A simple scheme for single-channel coherent perfect absorption (CPA) of transparent materials is proposed and experimentally realized using total internal reflection by grazing incidence, with a single dielectric layer sandwiched by semi-infinite dielectric layers. In a 1.48-µm thick polyvinylpyrrolidone (PVP) film, dip-coated on a MgF2 substrate both transparent in the visible, reflectance dips due to nearly 90% absorption by single-channel CPA were observed in the wavelength range of 370–800 nm, with white light from a Xe lamp incident on the side face of the substrate and extracted from the other side through multiple reflections in the PVP layer. This is a simple and inexpensive CPA scheme, and it is expected to have various applications by changing the substrate/polymer material or dispersing molecules in the polymer film. This paper also provides a design guideline for grazing-incidence waveguide-mode sensors using transparent dielectric materials.

Fano Resonance Hybrid Waveguide-Coupled Plasmonic Sensor Using Transparent Conductive Oxide in the Near-Infrared Range

We proposed an ultra-sensitive refractive index sensor by using indium-doped cadmium oxide as a plasmonic material operating in near-infrared based on Fano resonance. The proposed sensor has a hybrid multilayer waveguide structure that supports both a long-range surface plasmon polariton (LRSPP) mode and a dielectric waveguide (DWG) mode. The design strategy of the structure parameters of the inner layers is elaborated in detail through the numerical analysis of the two modes. By suitably tailoring the thickness of the coupling layer, a strong mode coupling between the two modes could be achieved, leading to a sharp asymmetric Fano resonance. With the designed optimal physical parameters, our proposed sensor could achieve a maximum intensity sensitivity of 19,909 RIU−1, a 193-fold enhancement than that of a conventional long-range SPR (LRSPR) based scheme. The proposed design can be a promising platform for biochemical sensing in the near-infrared region.

Surface plasmon resonance: A promising approach for label-free early cancer diagnosis

Cancer is the second leading cause of death worldwide after cardiovascular disease. The major cause of high mortality is delayed detection. Therefore, detection at an early stage followed by early treatment can mitigate morbidity as well as mortality. The utilization of biomarker-based detection tools helps in early-stage recognition. Fortunately, biomarkers indicating disease status can be released in to the circulation. These include traditional marker proteins as well as exosomes, micro-RNA (miRNA) and circulating tumor DNA (ct-DNA). Biosensors are biological and chemical reaction devices that generate signals based on analyte concentration. Due to analyte binding, these devices demonstrate high sensitivity and specificity. This review examines the use of surface plasmon resonance (SPR)-based sensors in the diagnosis of various cancer including those of the breast, prostate, lung, ovary, cervix and pancreas. SPR is a label-free, real-time and non-invasive optical biosensing technology representing a novel diagnostic tool in cancer detection.

A structural-based machine learning method to classify binding affinities between TCR and peptide-MHC complexes

The activation of T cells is triggered by the interactions of T cell receptors (TCRs) with their epitopes, which are peptides presented by major histocompatibility complex (MHC) on the surfaces of antigen presenting cells (APC). While each TCR can only recognize a specific subset from a large repertoire of peptide-MHC (pMHC) complexes, it is very often that peptides in this subset share little sequence similarity. This is known as the specificity and cross-reactivity of T cells, respectively. The binding affinities between different types of TCRs and pMHC are the major driving force to shape this specificity and cross-reactivity in T cell recognition. The binding affinities, furthermore, are determined by the sequence and structural properties at the interfaces between TCRs and pMHC. Fortunately, a wealth of data on binding and structures of TCR-pMHC interactions becomes publicly accessible in online resources, which offers us the opportunity to develop a random forest classifier for predicting the binding affinities between TCR and pMHC based on the structure of their complexes. Specifically, the structure and sequence of a given complex were projected onto a high-dimensional feature space as the input of the classifier, which was then trained by a large-scale benchmark dataset. Based on the cross-validation results, we found that our machine learning model can predict if the binding affinity of a given TCR-pMHC complex is stronger or weaker than a predefined threshold with an overall accuracy approximately around 75 %. The significance of our prediction was estimated by statistical analysis. Moreover, more than 60 % of binding affinities in the ATLAS database can be successfully classified into groups within the range of 2 kcal/mol. Additionally, we show that TCR-pMHC complexes with strong binding affinity prefer hydrophobic interactions between amino acids with large aromatic rings instead of electrostatic interactions. Our results therefore provide insights to design engineered TCRs which enhance the specificity for their targeted epitopes. Taken together, this method can serve as a useful addition to a suite of existing approaches which study binding between TCR and pMHC.

Metal ion implantation into transparent dielectric slab: an effective route to high-stability localized surface plasmon resonance sensors

Ag/SiO₂and Au/SiO₂samples were prepared by separately implanting 30 keV Ag and Au ions into 0.5-mm-thick SiO₂slabs at a fluence of 6 × 10¹⁶ion·cm^-2, and their optical and structural properties were studied in detail by using a fiber spectrometer and a transmission electron microscope, respectively. Our results showed that the two samples featured by their respective nanocomposite surface layers were asymmetrical in structure, and hence, their characteristic signals in the reflectance spectra excited by the lights incident from the rear surfaces were able to exhibit corresponding blueshifts when the overlays on the implanted surfaces were increased in refractive index with respect to air. Our results also showed that each of characteristic signals was strongly dependent on the localized surface plasmon resonance (LSPR) behavior of the involved Ag or Au nanoparticles (NPs), and it could not appear at a wavelength position smaller than or equal to that of the LSPR absorption peak since the involved Ag or Au NPs were quite small in size. These results meant that the two samples could be regarded as the LSPR sensors with a negative refractive index sensitivity (RIS), although their sensing abilities would lose when the overlays were very large in refractive index. Especially, the two samples were demonstrated to be relatively high in stability because the involved Ag and Au NPs were closely hugged and chemically protected by the matrices of SiO₂, and consequently, they could have a chance to become prospective sensing devices in some special fields as long as their RISs and linearities could be improved in the future. The above findings substantially confirmed that the metal ion implantation into transparent dielectric slab was an effective route to the high-stability LSPR sensors.

Design and Optimization of Surface Plasmon Resonance Spectroscopy for Optical Constant Characterization and Potential Sensing Application: Theoretical and Experimental Approaches

The best surface plasmon resonance (SPR) signal can be generated based on several factors that include the excitation wavelength, the type of metal used, and the thickness of the metal layer. In this study, the aforementioned factors have been investigated to obtain the best SPR signal. The excitation wavelength of 633 nm and gold metal with thickness of 50 nm were required to generate the SPR signal before the SPR was used for optical constant characterization by fitting of experimental results to the theoretical data. The employed strategy has good agreement with the theoretical value where the real part refractive index, n value, of the gold thin film was 0.1245 while the value for the imaginary part, k, was 3.6812 with 47.7 nm thickness. Besides that, the optical characterization of nanocrystalline cellulose (NCC)-based thin film has also been demonstrated. The n and k values found for this thin film were 1.4240 and 0.2520, respectively, with optimal thickness of 9.5 nm. Interestingly when the NCC-based thin film was exposed to copper ion solution with n value of 1.3333 and k value of 0.0060 to 0.0070 with various concentrations (0.01–10 ppm), a clear change of the refractive index value was observed. This result suggests that the NCC-based thin film has high potential for copper ion sensing using SPR with a sensitivity of 8.0052°/RIU.

Classification of protein-protein association rates based on biophysical informatics

BACKGROUND

Proteins form various complexes to carry out their versatile functions in cells. The dynamic properties of protein complex formation are mainly characterized by the association rates which measures how fast these complexes can be formed. It was experimentally observed that the association rates span an extremely wide range with over ten orders of magnitudes. Identification of association rates within this spectrum for specific protein complexes is therefore essential for us to understand their functional roles.

RESULTS

To tackle this problem, we integrate physics-based coarse-grained simulations into a neural-network-based classification model to estimate the range of association rates for protein complexes in a large-scale benchmark set. The cross-validation results show that, when an optimal threshold was selected, we can reach the best performance with specificity, precision, sensitivity and overall accuracy all higher than 70%. The quality of our cross-validation data has also been testified by further statistical analysis. Additionally, given an independent testing set, we can successfully predict the group of association rates for eight protein complexes out of ten. Finally, the analysis of failed cases suggests the future implementation of conformational dynamics into simulation can further improve model.

CONCLUSIONS

In summary, this study demonstrated that a new modeling framework that combines biophysical simulations with bioinformatics approaches is able to identify protein-protein interactions with low association rates from those with higher association rates. This method thereby can serve as a useful addition to a collection of existing experimental approaches that measure biomolecular recognition.

Recent Experimental Developments in Studying Passive Membrane Transport of Drug Molecules

The ability to measure the passive membrane permeation of drug-like molecules is of fundamental biological and pharmaceutical importance. Of significance, passive diffusion across the cellular membranes plays an effective role in the delivery of many pharmaceutical agents to intracellular targets. Hence, approaches for quantitative measurement of membrane permeability have been the topics of research for decades, resulting in sophisticated biomimetic systems coupled with advanced techniques. In this review, recent developments in experimental approaches along with theoretical models for quantitative and real-time analysis of membrane transport of drug-like molecules through mimetic and living cell membranes are discussed. The focus is on time-resolved fluorescence-based, surface plasmon resonance, and second-harmonic light scattering approaches. The current understanding of how properties of the membrane and permeant affect the permeation process is discussed.

Computational Assessment of Protein-Protein Binding Affinity by Reverse Engineering the Energetics in Protein Complexes

The cellular functions of proteins are maintained by forming diverse complexes. The stability of these complexes is quantified by the measurement of binding affinity, and mutations that alter the binding affinity can cause various diseases such as cancer and diabetes. As a result, accurate estimation of the binding stability and the effects of mutations on changes of binding affinity is a crucial step to understanding the biological functions of proteins and their dysfunctional consequences. It has been hypothesized that the stability of a protein complex is dependent not only on the residues at its binding interface by pairwise interactions but also on all other remaining residues that do not appear at the binding interface. Here, we computationally reconstruct the binding affinity by decomposing it into the contributions of interfacial residues and other non-interfacial residues in a protein complex. We further assume that the contributions of both interfacial and non-interfacial residues to the binding affinity depend on their local structural environments such as solvent-accessible surfaces and secondary structural types. The weights of all corresponding parameters are optimized by Monte-Carlo simulations. After cross-validation against a large-scale dataset, we show that the model not only shows a strong correlation between the absolute values of the experimental and calculated binding affinities, but can also be an effective approach to predict the relative changes of binding affinity from mutations. Moreover, we have found that the optimized weights of many parameters can capture the first-principle chemical and physical features of molecular recognition, therefore reversely engineering the energetics of protein complexes. These results suggest that our method can serve as a useful addition to current computational approaches for predicting binding affinity and understanding the molecular mechanism of protein–protein interactions.

A multiscale study on the mechanisms of spatial organization in ligand-receptor interactions on cell surfaces

The binding of cell surface receptors with extracellular ligands triggers distinctive signaling pathways, leading into the corresponding phenotypic variation of cells. It has been found that in many systems, these ligand-receptor complexes can further oligomerize into higher-order structures. This ligand-induced oligomerization of receptors on cell surfaces plays an important role in regulating the functions of cell signaling. The underlying mechanism, however, is not well understood. One typical example is proteins that belong to the tumor necrosis factor receptor (TNFR) superfamily. Using a generic multiscale simulation platform that spans from atomic to subcellular levels, we compared the detailed physical process of ligand-receptor oligomerization for two specific members in the TNFR superfamily: the complex formed between ligand TNFα and receptor TNFR1 versus the complex formed between ligand TNFβ and receptor TNFR2. Interestingly, although these two systems share high similarity on the tertiary and quaternary structural levels, our results indicate that their oligomers are formed with very different dynamic properties and spatial patterns. We demonstrated that the changes of receptor’s conformational fluctuations due to the membrane confinements are closely related to such difference. Consistent to previous experiments, our simulations also showed that TNFR can preassemble into dimers prior to ligand binding, while the introduction of TNF ligands induced higher-order oligomerization due to a multivalent effect. This study, therefore, provides the molecular basis to TNFR oligomerization and reveals new insights to TNFR-mediated signal transduction. Moreover, our multiscale simulation framework serves as a prototype that paves the way to study higher-order assembly of cell surface receptors in many other bio-systems.

A computational study of co-inhibitory immune complex assembly at the interface between T cells and antigen presenting cells

The activation and differentiation of T-cells are mainly directly by their co-regulatory receptors. T lymphocyte-associated protein-4 (CTLA-4) and programed cell death-1 (PD-1) are two of the most important co-regulatory receptors. Binding of PD-1 and CTLA-4 with their corresponding ligands programed cell death-ligand 1 (PD-L1) and B7 on the antigen presenting cells (APC) activates two central co-inhibitory signaling pathways to suppress T cell functions. Interestingly, recent experiments have identified a new cis-interaction between PD-L1 and B7, suggesting that a crosstalk exists between two co-inhibitory receptors and the two pairs of ligand-receptor complexes can undergo dynamic oligomerization. Inspired by these experimental evidences, we developed a coarse-grained model to characterize the assembling of an immune complex consisting of CLTA-4, B7, PD-L1 and PD-1. These four proteins and their interactions form a small network motif. The temporal dynamics and spatial pattern formation of this network was simulated by a diffusion-reaction algorithm. Our simulation method incorporates the membrane confinement of cell surface proteins and geometric arrangement of different binding interfaces between these proteins. A wide range of binding constants was tested for the interactions involved in the network. Interestingly, we show that the CTLA-4/B7 ligand-receptor complexes can first form linear oligomers, while these oligomers further align together into two-dimensional clusters. Similar phenomenon has also been observed in other systems of cell surface proteins. Our test results further indicate that both co-inhibitory signaling pathways activated by B7 and PD-L1 can be down-regulated by the new cis-interaction between these two ligands, consistent with previous experimental evidences. Finally, the simulations also suggest that the dynamic and the spatial properties of the immune complex assembly are highly determined by the energetics of molecular interactions in the network. Our study, therefore, brings new insights to the co-regulatory mechanisms of T cell activation.

The activation of a T cell can be regulated by the receptors on its surface, such as CTLA-4 and PD-1. People used to think that these two receptors inhibit T cell activation through distinct pathways. However, recent experiments discovered that the ligands of these two receptors, B7 and PD-L1, can interact with each other on the same surface of antigen presenting cells. Here we utilized computational simulations to investigate functional roles of this newly discovered interaction in T cell coregulation. The specific environment of interface between T cell and antigen presenting cell has been taken into account of our model. Ligand and receptors randomly diffuse within this interface area. They further involve in different types of interactions, with each other from the same side or the opposite side of cell surface. Using this method, we found ligands and receptors can not only form complexes, but also aggregate into large-scale clusters. We also demonstrated that the engagement between B7 and PD-L1 can reduce the interactions with their corresponding receptors. This study, therefore, offers new insights to our understanding of signal regulation in T cells.

Understanding the impacts of cellular environments on ligand binding of membrane receptors by computational simulations

Binding of cell surface receptors with their extracellular ligands initiates various intracellular signaling pathways. However, our understanding of the cellular functions of these receptors is very limited due to the fact that in vivo binding between ligands and receptors has only been successfully measured in a very small number of cases. In living cells, receptors are anchored on surfaces of the plasma membrane, which undergoes thermal undulations. Moreover, it has been observed in various systems that receptors can be organized into oligomers prior to ligand binding. It is not well understood how these cellular factors play roles in regulating the dynamics of ligand-receptor interactions. Here, we tackled these problems by using a coarse-grained kinetic Monte Carlo simulation method. Using this method, we demonstrated that the membrane undulations cause a negative effect on ligand-receptor interactions. We further found that the preassembly of membrane receptors on the cell surface can not only accelerate the kinetics of ligand binding but also reduce the noises during the process. In general, our study highlights the importance of membrane environments in regulating the function of membrane receptors in cells. The simulation method can be potentially applied to specific receptor systems involved in cell signaling.

Tunable narrowband plasmonic light emission from metallic crossed surface relief gratings

Plasmonic crossed surface relief gratings were fabricated using interference lithography. Their topographies were studied by AFM as a function of laser exposure time and their surface plasmon resonance at a gold-air interface was measured between crossed polarizers in transmission and in reflection modes. Both modes resulted in emitted plasmonic light at specific wavelengths related to the grating pitch, with the reflectance SPR having a much higher intensity than the transmittance SPR. The use of these gratings as plasmonic sensors was examined and their sensitivities were measured in the reflectance and transmittance modes to be 601 nm/RIU and 589 nm/RIU, respectively.

Understanding the Targeting Mechanisms of Multi-Specific Biologics in Immunotherapy with Multiscale Modeling

Immunotherapeutics are frequently associated with adverse side effects due to the elicitation of global immune modulation. To lower the risk of these side effects, recombinant DNA technology is employed to enhance the selectivity of cell targeting by genetically fusing different biomolecules, yielding new species referred to as multi-specific biologics. The design of new multi-specific biologics is a central challenge for the realization of new immunotherapies. To understand the molecular determinants responsible for regulating the binding between multi-specific biologics and surface-bound membrane receptors, we developed a multiscale computational framework that integrates various simulation approaches covering different timescales and spatial resolutions. Our model system of multi-specific biologics contains two natural ligands of immune receptors, which are covalently tethered by a peptide linker. Using this method, a number of interesting features of multi-specific biologics were identified. Our study therefore provides an important strategy to design the next-generation biologics for immunotherapy.

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Two proteins are connected by different linkers as a model of bispecific biologics

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Conformational dynamics of biologics are captured by microsecond MD simulations

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Coarse-grained simulations are used to test binding between biologics and receptors

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Biologics with long and flexible linkers are more efficient in targeting receptors

Fluorophore Coupling to Internal Modes of Bragg Gratings

Multilayer structures with two dielectrics having different optical constants and no structural features in the x-y plane can display photonic band gaps (PBGs) and are called one-dimensional photonic crystals (1DPCs). If the top layer thickness is carefully selected, the electromagnetic energy can be trapped at the top surface. These highly enhanced fields are called Bloch surface waves (BSWs). The BSW resonance angles are sensitive to the dielectric constant above the top dielectric layer. As a result, BSW structures have been used for surface plasmon resonance-like measurements without the use of a metal film. However, the emphasis on surface-localized BSWs has resulted in limited interest in fluorophore interactions with other optical modes of 1DPCs or Bragg gratings without the different thickness top layer. Herein, three different fluorescent probes were used to cover the short, center, and long wavelengths of the PBG. We demonstrate efficient coupling of fluorophores to both the BSW and internal modes (IMs) of a 1DPC. Coupling to the IM is expected to be low because of the micron-scale distances between the fluorophores and IM, which exists inside the Bragg gratings. At different wavelengths or observation angles, the IM-coupled emission (IMCE) can occur with the first three modes of the multilayer. This coupling is not dependent on a BSW mode. IMCE was also observed for a monolayer of fluorophore-labeled protein. IMCE enables sensitive detection of surface-bound fluorophores. Applications are anticipated in high sensitivity detection and super-resolution imaging.

Understanding the Impacts of Conformational Dynamics on the Regulation of Protein-Protein Association by a Multiscale Simulation Method

Complexes formed among diverse proteins carry out versatile functions in nearly all physiological processes. Association rates which measure how fast proteins form various complexes are of fundamental importance to characterize their functions. The association rates are not only determined by the energetic features at binding interfaces of a protein complex but also influenced by the intrinsic conformational dynamics of each protein in the complex. Unfortunately, how this conformational effect regulates protein association has never been calibrated on a systematic level. To tackle this problem, we developed a multiscale strategy to incorporate the information on protein conformational variations from Langevin dynamic simulations into a kinetic Monte Carlo algorithm of protein-protein association. By systematically testing this approach against a large-scale benchmark set, we found the association of a protein complex with a relatively rigid structure tends to be reduced by its conformational fluctuations. With specific examples, we further show that higher degrees of structural flexibility in various protein complexes can facilitate the searching and formation of intermolecular interactions and thereby accelerate their associations. In general, the integration of conformational dynamics can improve the correlation between experimentally measured association rates and computationally derived association probabilities. Finally, we analyzed the statistical distributions of different secondary structural types on protein-protein binding interfaces and their preference to the change of association rates. Our study, to the best of our knowledge, is the first computational method that systematically estimates the impacts of protein conformational dynamics on protein-protein association. It throws lights on the molecular mechanisms of how protein-protein recognition is kinetically modulated.

Combining Fluorinated Polymers with Ag Nanoparticles as a Route to Enhance Optical Properties of Composite Materials

Polymer-based nanocomposites have recently received considerable attention due to their unique properties, which makes them feasible for applications in optics, sensors, energy, life sciences, etc. The present work focuses on the synthesis of nanocomposites consisting of a polytetrafluorethylene-like matrix in which metallic nano-silver are embedded, by using multiple magnetron plasmas. By successively exposing the substrate to separate RF magnetrons using as combination of target materials polytetrafluorethylene (PTFE) and silver, individual control of each deposition process is insured, allowing obtaining of structures in which silver nanoparticles are entrapped in-between two PTFE layers with given thicknesses. The topographical and morphological characteristics investigated by means of Scanning Electron Microscopy and Atomic Force Microscopy techniques evidenced the very presence of Ag nanoparticles with typical dimension 7 nm. The chemical composition at various depositing steps was evaluated through X-ray Photoelectron Spectroscopy. We show that the presence of the top PTFE layer prevents silver oxidation, while its thickness allows the tailoring of optical properties, as evidenced by spectroellipsometry. The appearance of chemical bonds between silver atoms and PTFE atoms at interfaces is observed, pointing out that despite of pure physical deposition processes, a chemical interaction between the polymeric matrix and metal is promoted by plasma.

Using Coarse-Grained Simulations to Characterize the Mechanisms of Protein-Protein Association

The formation of functionally versatile protein complexes underlies almost every biological process. The estimation of how fast these complexes can be formed has broad implications for unravelling the mechanism of biomolecular recognition. This kinetic property is traditionally quantified by association rates, which can be measured through various experimental techniques. To complement these time-consuming and labor-intensive approaches, we developed a coarse-grained simulation approach to study the physical processes of protein–protein association. We systematically calibrated our simulation method against a large-scale benchmark set. By combining a physics-based force field with a statistically-derived potential in the simulation, we found that the association rates of more than 80% of protein complexes can be correctly predicted within one order of magnitude relative to their experimental measurements. We further showed that a mixture of force fields derived from complementary sources was able to describe the process of protein–protein association with mechanistic details. For instance, we show that association of a protein complex contains multiple steps in which proteins continuously search their local binding orientations and form non-native-like intermediates through repeated dissociation and re-association. Moreover, with an ensemble of loosely bound encounter complexes observed around their native conformation, we suggest that the transition states of protein–protein association could be highly diverse on the structural level. Our study also supports the idea in which the association of a protein complex is driven by a “funnel-like” energy landscape. In summary, these results shed light on our understanding of how protein–protein recognition is kinetically modulated, and our coarse-grained simulation approach can serve as a useful addition to the existing experimental approaches that measure protein–protein association rates.

A Systematic Test of Receptor Binding Kinetics for Ligands in Tumor Necrosis Factor Superfamily by Computational Simulations

Ligands in the tumor necrosis factor (TNF) superfamily are one major class of cytokines that bind to their corresponding receptors in the tumor necrosis factor receptor (TNFR) superfamily and initiate multiple intracellular signaling pathways during inflammation, tissue homeostasis, and cell differentiation. Mutations in the genes that encode TNF ligands or TNFR receptors result in a large variety of diseases. The development of therapeutic treatment for these diseases can be greatly benefitted from the knowledge on binding properties of these ligand–receptor interactions. In order to complement the limitations in the current experimental methods that measure the binding constants of TNF/TNFR interactions, we developed a new simulation strategy to computationally estimate the association and dissociation between a ligand and its receptor. We systematically tested this strategy to a comprehensive dataset that contained structures of diverse complexes between TNF ligands and their corresponding receptors in the TNFR superfamily. We demonstrated that the binding stabilities inferred from our simulation results were compatible with existing experimental data. We further compared the binding kinetics of different TNF/TNFR systems, and explored their potential functional implication. We suggest that the transient binding between ligands and cell surface receptors leads into a dynamic nature of cross-membrane signal transduction, whereas the slow but strong binding of these ligands to the soluble decoy receptors is naturally designed to fulfill their functions as inhibitors of signal activation. Therefore, our computational approach serves as a useful addition to current experimental techniques for the quantitatively comparison of interactions across different members in the TNF and TNFR superfamily. It also provides a mechanistic understanding to the functions of TNF-associated cell signaling pathways.

A computational model for understanding the oligomerization mechanisms of TNF receptor superfamily

By recognizing members in the tumor necrosis factor (TNF) receptor superfamily, TNF ligand proteins function as extracellular cytokines to activate various signaling pathways involved in inflammation, proliferation, and apoptosis. Most ligands in TNF superfamily are trimeric and can simultaneously bind to three receptors on cell surfaces. It has been experimentally observed that the formation of these molecular complexes further triggers the oligomerization of TNF receptors, which in turn regulate the intracellular signaling processes by providing transient compartmentalization in the membrane proximal regions of cytoplasm. In order to decode the molecular mechanisms of oligomerization in TNF receptor superfamily, we developed a new computational method that can physically simulate the spatial-temporal process of binding between TNF ligands and their receptors. The simulations show that the TNF receptors can be organized into hexagonal oligomers. The formation of this spatial pattern is highly dependent not only on the molecular properties such as the affinities of trans and cis binding, but also on the cellular factors such as the concentration of TNF ligands in the extracellular area or the density of TNF receptors on cell surfaces. Moreover, our model suggests that if TNF receptors are pre-organized into dimers before ligand binding, these lateral interactions between receptor monomers can play a positive role in stabilizing the ligand-receptor interactions, as well as in regulating the kinetics of receptor oligomerization. Altogether, this method throws lights on the mechanisms of TNF ligand-receptor interactions in cellular environments.

The Binding of Drug Molecules to Serum Albumin: The Effect of Drug Hydrophobicity on Binding Strength and Protein Desolvation

In this work, dual polarization interferometry (DPI) and quartz crystal microgravimetry with dissipation monitoring (QCM-D) were used to examine the binding characteristics and structure-activity relationships of 12 common drugs on a model bovine serum albumin (BSA) film. By taking advantage of the different hydration sensitivities of DPI and QCM-D, we were able to quantify changes in the solvent state upon drug binding to BSA. Quantifying the changes in water mass within binding pockets and upon drug-protein binding allows for a more complete understanding of binding phenomena between drug molecules and serum proteins. For the drugs tested, a quantitative structure-activity relationship (QSAR) was used to establish a correlation between drug binding (K_D) and hydrophobicity (ClogP), with the latter being related to the drug's ability to desolvate the BSA upon binding. Understanding these relationships provides insight into the role of water at the protein-ligand interface and is of particular importance in the area of ligand binding within the field of drug design. This study underscores the importance of hydrophobicity to drug binding kinetics and may be used to further understand and improve drug design and delivery protocols.

Computational studies of protein-protein dissociation by statistical potential and coarse-grained simulations: a case study on interactions between colicin E9 endonuclease and immunity proteins

Proteins carry out their diverse functions in cells by forming interactions with each other. The dynamics of these interactions are quantified by the measurement of association and dissociation rate constants. Relative to the efforts made to model the association of biomolecules, little has been studied to understand the principles of protein complex dissociation. Using the interaction between colicin E9 endonucleases and immunity proteins as a test system, here we develop a coarse-grained simulation method to explore the dissociation mechanisms of protein complexes. The interactions between proteins in the complex are described by the knowledge-based potential that was constructed by the statistics from available protein complexes in the structural database. Our study provides the supportive evidences to the dual recognition mechanism for the specificity of binding between E9 DNase and immunity proteins, in which the conserved residues of helix III of Im2 and Im9 proteins act as the anchor for binding, while the sequence variations in helix II make positive or negative contributions to specificity. Beyond that, we further suggest that this binding specificity is rooted in the process of complex dissociation instead of association. While we increased the flexibility of protein complexes, we further found that they are less prone to dissociation, suggesting that conformational fluctuations of protein complexes play important functional roles in regulating their binding and dissociation. Our studies therefore bring new insights to the molecule mechanisms of protein-protein interactions, while the method can serve as a new addition to a suite of existing computational tools for the simulations of protein complexes.

The influence of truncating the carboxy-terminal amino acid residues of streptococcal enolase on its ability to interact with canine plasminogen

The native octameric structure of streptococcal enolase from Streptococcus pyogenes increasingly dissociates as amino acid residues are removed one by one from the carboxy-terminus. These truncations gradually convert native octameric enolase into monomers and oligomers. In this work, we investigated how these truncations influence the interaction between Streptococcal enolase and canine plasminogen. We used dual polarization interferometry (DPI), localized surface plasmon resonance (LSPR), and sedimentation velocity analytical ultracentrifugation (AUC) to study the interaction. The DPI was our first technique, was performed on all the truncations and used one exclusive kind of chip. The LSRP was used to show that the DPI results were not dependent on the type of chip used. The AUC was required to show that our surface results were not the result of selecting a minority population in any given sample; the majority of the protein was responsible for the binding phenomenon we observed. By comparing results from these techniques we identified one detail that is essential for streptococcal enolase to bind plasminogen: In our hands the individual monomers bind plasminogen; dimers, trimers, tetramers may or may not bind, the fully intact, native, octamer does not bind plasminogen. We also evaluated the contribution to the equilibrium constant made by surface binding as well as in solution. On a surface, the association coefficient is about twice that in solution. The difference is probably not significant. Finally, the fully octameric form of the protein that does not contain a hexa-his N-terminal peptide does not bind to a silicon oxynitride surface, does not bind to an Au-nanoparticle surface, does not bind to a surface coated with Ni-NTA nor does it bind to a surface coated with DPgn. The likelihood is great that the enolase species on the surface of Streptococcus pyogenes is an x-mer of the native octamer.

MicroRNA sensors based on gold nanoparticles

MicroRNAs (miRNAs) are small regulatory RNAs, the dysregulation of which has been associated with the progression of several human diseases, including cancer. Interestingly, these molecules can be used as biomarkers for early disease diagnosis and can be found in a variety of body fluids and tissue samples. However, their specific properties and very low concentrations make their detection rather challenging. In this regard, current detection methods are complex, cost-ineffective, and of limited application in point-of-care settings or resource-limited facilities. Recently, nanotechnology-based approaches have emerged as promising alternatives to conventional miRNA detection methods and paved the way for research towards sensitive, fast, and low-cost detection systems. In particular, due to their exceptional properties, the use of gold nanoparticles (AuNPs) has significantly improved the performance of miRNA biosensors. This review discusses the application of AuNPs in different miRNA sensor modalities, commenting on recently reported examples. A practical overview of each modality is provided, highlighting their future use in clinical diagnosis. Graphical abstract ᅟ.

Fabrication of buried nanostructures by atomic layer deposition

We present a method for fabricating buried nanostructures by growing a dielectric cover layer on a corrugated surface profile by atomic layer deposition of TiO₂. Selecting appropriate process parameters, the conformal growth of TiO₂ results in a smooth, nearly flat-top surface of the structure. Such a hard surface can be easily cleaned without damage, making the nanostructure reusable after contamination. The technique has wide applicability in resonance-domain diffractive optics and in realization of quasi-planar metamaterials. We discuss design issues of such optical elements and demonstrate the method by fabricating narrow-band spectral filters based on the guided-mode resonance effect. These elements have strong potential for, e.g., sensing applications in harsh conditions.

The role of small-angle scattering in structure-based screening applications

In many biomolecular interactions, changes in the assembly states and structural conformations of participants can act as a complementary reporter of binding to functional and thermodynamic assays. This structural information is captured by a number of structural biology and biophysical techniques that are viable either as primary screens in small-scale applications or as secondary screens to complement higher throughput methods. In particular, small-angle X-ray scattering (SAXS) reports the average distance distribution between all atoms after orientational averaging. Such information is important when for example investigating conformational changes involved in inhibitory and regulatory mechanisms where binding events do not necessarily cause functional changes. Thus, we summarise here the current and prospective capabilities of SAXS-based screening in the context of other methods that yield structural information. Broad guidelines are also provided to assist readers in preparing screening protocols that are tailored to available X-ray sources.

Integrating Structural Information to Study the Dynamics of Protein-Protein Interactions in Cells

The information of how two proteins interact is embedded in the atomic details of their binding interfaces. These interactions, spatial-temporally coordinating each other as a network in a variable cytoplasmic environment, dominate almost all biological functions. A feasible and reliable computational model is highly demanded to realistically simulate these cellular processes and unravel the complexities beneath them. We therefore present a multiscale framework that integrates simulations on two different scales. The higher-resolution model incorporates structural information of proteins and energetics of their binding, while the lower-resolution model uses a highly simplified representation of proteins to capture the long-time-scale dynamics of a system with multiple proteins. Through a systematic benchmark test and two practical applications of biomolecular systems with specific cellular functions, we demonstrated that this method could be a powerful approach to understand molecular mechanisms of dynamic interactions between biomolecules and their functional impacts with high computational efficiency.

Biosensors for wastewater monitoring: A review

Water pollution and habitat degradation are the cause of increasing water scarcity and decline in aquatic biodiversity. While the freshwater availability has been declining through past decades, water demand has continued to increase particularly in areas with arid and semi-arid climate. Monitoring of pollutants in wastewater effluents are critical to identifying water pollution area for treatment. Conventional detection methods are not effective in tracing multiple harmful components in wastewater due to their variability along different times and sources. Currently, the development of biosensing instruments attracted significant attention because of their high sensitivity, selectivity, reliability, simplicity, low-cost and real-time response. This paper provides a general overview on reported biosensors, which have been applied for the recognition of important organic chemicals, heavy metals, and microorganisms in dark waters. The significance and successes of nanotechnology in the field of biomolecular detection are also reviewed. The commercially available biosensors and their main challenges in wastewater monitoring are finally discussed.

Highly Sensitive Label-Free Detection of Small Molecules with an Optofluidic Microbubble Resonator

The detection of small molecules has increasingly attracted the attention of researchers because of its important physiological function. In this manuscript, we propose a novel optical sensor which uses an optofluidic microbubble resonator (OFMBR) for the highly sensitive detection of small molecules. This paper demonstrates the binding of the small molecule biotin to surface-immobilized streptavidin with a detection limit reduced to 0.41 pM. Furthermore, binding specificity of four additional small molecules to surface-immobilized streptavidin is shown. A label-free OFMBR-based optical sensor has great potential in small molecule detection and drug screening because of its high sensitivity, low detection limit, and minimal sample consumption.

New trends in plasmonic (bio)sensing

The strong enhancement and localization of electromagnetic field in plasmonic systems have found applications in many areas, which include sensing and biosensing. In this paper, an overview will be provided of the use of plasmonic phenomena in sensors and biosensors with emphasis on two main topics. The first is related to possible ways to enhance the performance of sensors and biosensors based on surface plasmon resonance (SPR), where examples are given of functionalized magnetic nanoparticles, magnetoplasmonic effects and use of metamaterials for SPR sensing. The other topic is focused on surface-enhanced Raman scattering (SERS) for sensing, for which uniform, flexible, and reproducible SERS substrates have been produced. With such recent developments, there is the prospect of improving sensitivity and lowering the limit of detection in order to overcome the limitations inherent in ultrasensitive detection of chemical and biological analytes, especially at single molecule levels.