Surface plasmon resonance imaging of polymer microarrays to study protein-polymer interactions in high throughput

Sensing Volatile Pollutants with Spin-Coated Films Made of Pillar[5]arene Derivatives and Data Validation via Artificial Neural Networks

Different types of solvents, aromatic and aliphatic, are used in many industrial sectors, and long-term exposure to these solvents can lead to many occupational diseases. Therefore, it is of great importance to detect volatile organic compounds (VOCs) using economic and ergonomic techniques. In this study, two macromolecules based on pillar[5]arene, named P[5]-1 and P[5]-2, were synthesized and applied to the detection of six different environmentally volatile pollutants in industry and laboratories. The thin films of the synthesized macrocycles were coated by using the spin coating technique on a suitable substrate under optimum conditions. All compounds and the prepared thin film surfaces were characterized by NMR, Fourier transform infrared (FT-IR), elemental analysis, atomic force microscopy (AFM), scanning electron microscopy (SEM), and contact angle measurements. All vapor sensing measurements were performed via the surface plasmon resonance (SPR) optical technique, and the responses of the P[5]-1 and P[5]-2 thin-film sensors were calculated with ΔI/Io × 100. The responses of the P[5]-1 and P[5]-2 thin-film sensors to dichloromethane vapor were determined to be 7.17 and 4.11, respectively, while the responses to chloroform vapor were calculated to be 5.24 and 2.8, respectively. As a result, these thin-film sensors showed a higher response to dichloromethane and chloroform vapors than to other harmful vapors. The SPR kinetic data for vapors validated that a nonlinear autoregressive neural network was performed with exogenous input for the best molecular modeling by using normalized reflected light intensity values. It can be clearly seen from the correlation coefficient values that the nonlinear autoregressive with exogenous input artificial neural network (NARX-ANN) model for dichloromethane converged more successfully to the experimental data compared to other gases. The correlation coefficient values of the dichloromethane modeling results were approximately 0.99 and 0.98 for P[5]-1 and P[5]-2 thin-film sensors, respectively.

Fluorescence enables high throughput screening of polyelectrolyte–protein binding affinities

Förster resonance energy transfer (FRET) in combination with high throughput controlled radical polymerisation allows quick identification of polymers that can bind strongly to enzymes such as glucose oxidase.

High-Throughput and Combinatorial Approaches for the Development of Multifunctional Polymers

High-throughput (HT) development of new multifunctional polymers is accomplished by the combination of different HT tools established in polymer sciences in the last decade. Important advances are robotic/HT synthesis of polymer libraries, the HT characterization of polymers, and the application of spatially resolved polymer library formats, explicitly microarray and gradient libraries. HT polymer synthesis enables the generation of material libraries with combinatorial design motifs. Polymer composition, molecular weight, macromolecular architecture, etc. may be varied in a systematic, fine-graded manner to obtain libraries with high chemical diversity and sufficient compositional resolution as model systems for the screening of these materials for the functions aimed. HT characterization allows a fast assessment of complementary properties, which are employed to decipher quantitative structure-properties relationships. Moreover, these methods facilitate the HT determination of important surface parameters by spatially resolved characterization methods, including time-of-flight secondary ion mass spectrometry and X-ray photoelectron spectroscopy. Here current methods for the high-throughput robotic synthesis of multifunctional polymers as well as their characterization are presented and advantages as well as present limitations are discussed.

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology

The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.

Immunoassay Biosensing of Foodborne Pathogens with Surface Plasmon Resonance Imaging: A Review

Surface plasmon resonance imaging (SPRi) has been increasingly used in the label-free detections of various biospecies, such as organic toxins, proteins, and bacteria. In combination with the well-developed microarray immunoassay, SPRi has the advantages of rapid detection in tens of minutes and multiplex detection of different targets with the same biochip. Both prism-based and prism-free configurations of SPRi have been developed for highly integrated portable immunosensors, which have shown great potential on pathogen detection and living cell imaging. This review summarizes the recent advances in immunoassay biosensing with SPRi, with special emphasis on the multiplex detections of foodborne pathogens. Additionally, various spotting techniques, surface modification protocols, and signal amplification methods have been developed to improve the specificity and sensitivity of the SPRi biochip. The challenges in multiplex detections of foodborne pathogens in real-world samples are addressed, and future perspectives of miniaturizing SPRi immunosensors with nanotechnologies are discussed.

Engineering serendipity: High-throughput discovery of materials that resist bacterial attachment

Controlling the colonisation of materials by microorganisms is important in a wide range of industries and clinical settings. To date, the underlying mechanisms that govern the interactions of bacteria with material surfaces remain poorly understood, limiting the ab initio design and engineering of biomaterials to control bacterial attachment. Combinatorial approaches involving high-throughput screening have emerged as key tools for identifying materials to control bacterial attachment. The hundreds of different materials assessed using these methods can be carried out with the aid of computational modelling. This approach can develop an understanding of the rules used to predict bacterial attachment to surfaces of non-toxic synthetic materials. Here we outline our view on the state of this field and the challenges and opportunities in this area for the coming years.

STATEMENT OF SIGNIFICANCE

This opinion article on high throughput screening methods reflects one aspect of how the field of biomaterials research has developed and progressed. The piece takes the reader through key developments in biomaterials discovery, particularly focusing on need to reduce bacterial colonisation of surfaces. Such bacterial resistant surfaces are increasingly required in this age of antibiotic resistance. The influence and origin of high-throughput methods are discussed with insights into the future of biomaterials development where computational methods may drive materials development into new fertile areas of discovery. New biomaterials will exhibit responsiveness to adapt to the biological environment and promote better integration and reduced rejection or infection.

ToF-SIMS analysis of a polymer microarray composed of poly(meth)acrylates with C6 derivative pendant groups

Surface analysis plays a key role in understanding the function of materials, particularly in biological environments. Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) provides highly surface sensitive chemical information that can readily be acquired over large areas and has, thus, become an important surface analysis tool. However, the information‐rich nature of ToF‐SIMS complicates the interpretation and comparison of spectra, particularly in cases where multicomponent samples are being assessed. In this study, a method is presented to assess the chemical variance across 16 poly(meth)acrylates. Materials are selected to contain C₆ pendant groups, and ten replicates of each are printed as a polymer microarray. SIMS spectra are acquired for each material with the most intense and unique ions assessed for each material to identify the predominant and distinctive fragmentation pathways within the materials studied. Differentiating acrylate/methacrylate pairs is readily achieved using secondary ions derived from both the polymer backbone and pendant groups. Principal component analysis (PCA) is performed on the SIMS spectra of the 16 polymers, whereby the resulting principal components are able to distinguish phenyl from benzyl groups, mono‐functional from multi‐functional monomers and acrylates from methacrylates. The principal components are applied to copolymer series to assess the predictive capabilities of the PCA. Beyond being able to predict the copolymer ratio, in some cases, the SIMS analysis is able to provide insight into the molecular sequence of a copolymer. The insight gained in this study will be beneficial for developing structure–function relationships based upon ToF‐SIMS data of polymer libraries. © 2016 The Authors Surface and Interface Analysis Published by John Wiley & Sons Ltd.

Improvement of interaction between PVA and chitosan via magnetite nanoparticles for drug delivery application

Magnetite nanoparticles were synthesized by coprecipitation under ultrasonication followed by coating with chitosan. Polyvinyl alcohol (PVA) is then combined with the chitosan that coated the magnetite nanoparticles. The combination occurs by hydrogen binding and ionic cross-linking of the amino and hydroxyl groups of chitosan and PVA respectively. The magnetite nanoparticles have an average size of 10.62 nm that was confirmed by TEM. The VSM measurements showed that nanoparticles were superparamagnetic. The coatings on the core nanoparticles were estimated by AAS and the attachments of coating to the nanoparticles were confirmed by FT-IR analysis. Physicochemical properties of nanoparticles were measured by DLS and zeta potential. Naked magnetite, chitosan and PVA coating have zeta potential of +36.4, +48.1 and -12.5 mV respectively. The unspecific adsorption and interaction between nanoparticles and bovine serum albumin (BSA) were investigated systematically by UV-vis spectroscopy method. The nanoparticles that were modified by PVA present low protein adsorption, which makes them a practical choice for preventing opsonization in clinical application and drug delivery.

Strategies for MCR image analysis of large hyperspectral data-sets

Polymer microarrays are a key enabling technology for high throughput materials discovery. In this study, multivariate image analysis, specifically multivariate curve resolution (MCR), is applied to the hyperspectral time of flight secondary ion mass spectroscopy (ToF-SIMS) data from eight individual microarray spots. Rather than analysing the data individually, the data-sets are collated and analysed as a single large data-set. Desktop computing is not a practical method for undertaking MCR analysis of such large data-sets due to the constraints of memory and computational overhead. Here, a distributed memory High-Performance Computing facility (HPC) is used. Similar to what is achieved using MCR analysis of individual samples, the results from this consolidated data-set allow clear identification of the substrate material; furthermore, specific chemistries common to different spots are also identified. The application of the HPC facility to the MCR analysis of ToF-SIMS hyperspectral data-sets demonstrates a potential methodology for the analysis of macro-scale data without compromising spatial resolution (data 'binning'). Copyright © 2012 John Wiley & Sons, Ltd.

Analysis and prediction of defects in UV photo-initiated polymer microarrays

Polymer microarrays are a key enabling technology for the discovery of novel materials. This technology can be further enhanced by expanding the combinatorial space represented on an array. However, not all materials are compatible with the microarray format and materials must be screened to assess their suitability with the microarray manufacturing methodology prior to their inclusion in a materials discovery investigation. In this study a library of materials expressed on the microarray format are assessed by light microscopy, atomic force microscopy and time-of-flight secondary ion mass spectrometry to identify compositions with defects that cause a polymer spot to exhibit surface properties significantly different from a smooth, round, chemically homogeneous 'normal' spot. It was demonstrated that the presence of these defects could be predicted in 85% of cases using a partial least square regression model based upon molecular descriptors of the monomer components of the polymeric materials. This may allow for potentially defective materials to be identified prior to their formation. Analysis of the PLS regression model highlighted some chemical properties that influenced the formation of defects, and in particular suggested that mixing a methacrylate and an acrylate monomer and/or mixing monomers with long and linear or short and bulky pendant groups will prevent the formation of defects. These results are of interest for the formation of polymer microarrays and may also inform the formulation of printed polymer materials generally.

The influence of nanostructured materials on biointerfacial interactions

Control over biointerfacial interactions in vitro and in vivo is the key to many biomedical applications: from cell culture and diagnostic tools to drug delivery, biomaterials and regenerative medicine. The increasing use of nanostructured materials is placing a greater demand on improving our understanding of how these new materials influence biointerfacial interactions, including protein adsorption and subsequent cellular responses. A range of nanoscale material properties influence these interactions, and material toxicity. The ability to manipulate both material nanochemistry and nanotopography remains challenging in its own right, however, a more in-depth knowledge of the subsequent biological responses to these new materials must occur simultaneously if they are ever to be affective in the clinic. We highlight some of the key technologies used for fabrication of nanostructured materials, examine how nanostructured materials influence the behavior of proteins and cells at surfaces and provide details of important analytical techniques used in this context.

High throughput discovery of thermo-responsive materials using water contact angle measurements and time-of-flight secondary ion mass spectrometry

Switchable materials that alter their chemical or physical properties in response to external stimuli allow for temporal control of material-biological interactions, thus, are of interest for many biomaterial applications. Our interest is the discovery of new materials suitable to the specific requirements of certain biological systems. A high throughput methodology has been developed to screen a library of polymers for thermo-responsiveness, which has resulted in the identification of novel switchable materials. To elucidate the mechanism by which the materials switch, time-of-flight secondary ion mass spectrometry has been employed to analyse the top 2 nm of the polymer samples at different temperatures. The surface enrichment of certain molecular fragments has been identified by time-of-flight secondary ion mass spectrometry analysis at different temperatures, suggesting an altered molecular conformation. In one example, a switch between an extended and collapsed conformation is inferred. Copyright © 2012 John Wiley & Sons, Ltd.

Polymers with hydro-responsive topography identified using high throughput AFM of an acrylate microarray

Atomic force microscopy has been applied to an acrylate polymer microarray to achieve a full topographic characterisation. This process discovered a small number of hydro-responsive materials created from monomers with disparate hydrophilicities that show reversibility between pitted and protruding nanoscale topographies.

Microfluidic-based biosensors toward point-of-care detection of nucleic acids and proteins

This article reviews state-of-the-art microfluidic biosensors of nucleic acids and proteins for point-of-care (POC) diagnostics. Microfluidics is capable of analyzing small sample volumes (10^-9-10^-18 l) and minimizing costly reagent consumption as well as automating sample preparation and reducing processing time. The merger of microfluidics and advanced biosensor technologies offers new promises for POC diagnostics, including high-throughput analysis, portability and disposability. However, this merger also imposes technological challenges on biosensors, such as high sensitivity and selectivity requirements with sample volumes orders of magnitude smaller than those of conventional practices, false response errors due to non-specific adsorption, and integrability with other necessary modules. There have been many prior review articles on microfluidic-based biosensors, and this review focuses on the recent progress in last 5 years. Herein, we review general technologies of DNA and protein biosensors. Then, recent advances on the coupling of the biosensors to microfluidics are highlighted. Finally, we discuss the key challenges and potential solutions for transforming microfluidic biosensors into POC diagnostic applications.

Interface design and multiplexed analysis with surface plasmon resonance (SPR) spectroscopy and SPR imaging

Ever since the advent of surface plasmon resonance (SPR) and SPR imaging (SPRi) in the early 1990s, their use in biomolecular interaction analysis (BIA) has expanded phenomenally. An important research area in SPR sensor development is the design of novel and effective interfaces that allow for the probing of a variety of chemical and biological interactions in a highly selective and sensitive manner. A well-designed and robust interface is a necessity to obtain both accurate and pertinent biological information. This review covers the recent research efforts in this area with a specific focus towards biointerfaces, new materials for SPR biosensing, and novel array designs for SPR imaging. Perspectives on the challenges ahead and next steps for SPR technology are discussed.

Label-free detection techniques for protein microarrays: prospects, merits and challenges

Protein microarrays, on which thousands of discrete proteins are printed, provide a valuable platform for functional analysis of the proteome. They have been widely used for biomarker discovery and to study protein–protein interactions. The accomplishments of DNA microarray technology, which had enabled massive parallel studies of gene expression, sparked great interest for the development of protein microarrays to achieve similar success at the protein level. Protein microarray detection techniques are often classified as being label‐based and label‐free. Most of the microarray applications have employed labelled detection such as fluorescent, chemiluminescent and radioactive labelling. These labelling strategies have synthetic challenges, multiple label issues and may exhibit interference with the binding site. Therefore, development of sensitive, reliable, high‐throughput, label‐free detection techniques are now attracting significant attention. Label‐free detection techniques monitor biomolecular interactions and simplify the bioassays by eliminating the need for secondary reactants. Moreover, they provide quantitative information for the binding kinetics. In this article, we will review several label‐free techniques, which offer promising applications for the protein microarrays, and discuss their prospects, merits and challenges.

High throughput methods applied in biomaterial development and discovery

The high throughput discovery of new bio materials can be achieved by rapidly screening many different materials synthesised by a combinatorial approach to identify the optimal composition that fulfils a particular biomedical application. Here we review the literature in this area and conclude that for polymers this process is best achieved in a microarray format, which enable thousands of cell-material interactions to be monitored on a single chip. Polymer microarrays can be formed by printing pre-synthesised polymers or by printing monomers onto the chip where on-slide polymerisation is initiated. The surface properties of the material can be analysed and correlated to the biological performance using high throughput surface analysis, including time-of-flight secondary ion mass spectrometry (ToF-SIMS), X-ray photoelectron spectroscopy (XPS) and water contact angle (WCA) measurements. This approach enables the surface properties responsible for the success of a material to be understood, which in turn provides the foundations of future material design. The high throughput discovery of materials using polymer microarrays has been explored for many cell-based applications including the isolation of specific cells from heterogeneous populations, the attachment and differentiation of stem cells and the controlled transfection of cells. Further development of polymerisation techniques and high throughput biological assays amenable to the polymer microarray format will broaden the combinatorial space and biological phenomenon that polymer microarrays can explore, and increase their efficacy. This will, in turn, facilitate the discovery of optimised polymeric materials for many biomaterial applications.