Peptide Specific Nanoplastic Detection Based on Sandwich Typed Localized Surface Plasmon Resonance

Selective on-site detection and quantification of polystyrene microplastics in water using fluorescence-tagged peptides and electrochemical impedance spectroscopy

In this study, we developed a method for the on-site selective detection and quantification of microplastics in various water matrices using fluorescence-tagged peptides combined with electrochemical impedance spectroscopy (EIS). Among the types of plastics found in seawater, polystyrene (PS) microplastics were selected. Fluorometry, scanning electron microscopy (SEM), and Raman spectroscopy were used to verify the specific interaction of these peptides with PS spherical particles of different sizes (ranging from 0.1 to 250 µm). Principal component analysis (PCA) was employed to determine the effects of temperature (25-65 °C), incubation time (5 and 10 min), and particle size on plastic-peptide bonding efficiency, based on fluorescence intensity. For each water type (pure, tap, NaCl (0.5 M), and seawater), EIS plots (Nyquist and Bode) were generated. Significant factors affecting the EIS response, including particle size, shape, and material, were analyzed by measuring electrical parameters for different microplastic concentrations (50 ppb to 20 ppm). The EIS parameters changed with increasing plastic concentration, determining a limit of detection (LOD) of 50 ppb (ng/mL) for pure and tap water and 400 ppb for saline water, as the lowest concentration producing a significant change in EIS parameters compared to the baseline. The sensor proved highly effective for detecting microplastics in low ionic strength environments such as pure and tap water. However, in high ionic strength environments like saline and seawater, the detection capability diminished, likely due to the masking effect of ions on the EIS response.

A metal-insulator-metal waveguide-based plasmonic refractive index sensor for the detection of nanoplastics in water

A metal-insulator-metal waveguide-based square-ring resonator plasmonic refractive index sensor is designed and optimized for achieving high sensitivity. The sensitivity of the sensor critically depends on the physical dimension and the geometrical parameters of the resonator. Systematic studies on varying geometrical parameters of the resonator reveal that the sensitivity increases with the number of concentric square-rings. Moreover, the full-width-half-maxima of the resonance line is found to increase with the number of square rings. Importantly, variations in the coupling length affect the transmitted intensity as well as the full-width-half-maxima of the resonance spectra in a characteristic fashion. An initial exploration of the optimized sensor for nanoplastic detection for a range of volume fractions 0.15625-0.625% shows a systematic linear increase in the resonance wavelength with changing refractive index of the surrounding medium. This offers the possibility of ultrasensitive detection of extremely small change ( ∼ 0.00025 ) in the local refractive index as the signature of a minute level of plastic contamination. This was achieved by using an optimized sensor design with a sensitivity of 2700 nm/RIU and a full-width-half-maxima of 333 nm. Results presented in the paper demonstrate the considerable promise of the proposed plasmonic refractive index sensor towards nanoplastic detection.

In-situ detection of microplastics in the aquatic environment: A systematic literature review

Microplastics are ubiquitous in the aquatic environment and have emerged as a significant environmental issue due to their potential impacts on human health and the ecosystem. Current laboratory-based microplastic detection methods suffer from various drawbacks, including a lack of standardisation, limited spatial and temporal coverage, high costs, and time-consuming procedures. Consequently, there is a need for the development of in-situ techniques to detect and monitor microplastics to effectively identify and understand their sources, pathways, and behaviours. Herein, we adopt a systematic literature review method to assess the development and application of experimental and field technologies designed for the in-situ detection and monitoring of aquatic microplastics, without the need for sample preparation. Four scientific databases were searched in March 2023, resulting in a review of 62 relevant studies. These studies were classified into seven sensor categories and their working principles were discussed. The sensor classes include optical devices, digital holography, Raman spectroscopy, other spectroscopy, hyperspectral imaging, remote sensing, and other methods. We also looked at how data from these technologies are integrated with machine learning models to develop classifiers capable of accurately characterising the physical and chemical properties of microplastics and discriminating them from other particles. This review concluded that in-situ detection of microplastics in aquatic environments is feasible and can be achieved with high accuracy, even though the methods are still in the early stages of development. Nonetheless, further research is still needed to enhance the in-situ detection of microplastics. This includes exploring the possibility of combining various detection methods and developing robust machine-learning classifiers. Additionally, there is a recommendation for in-situ implementation of the reviewed methods to assess their effectiveness in detecting microplastics and identify their limitations.

Material-specific binding peptides empower sustainable innovations in plant health, biocatalysis, medicine and microplastic quantification

Material-binding peptides (MBPs) have emerged as a diverse and innovation-enabling class of peptides in applications such as plant-/human health, immobilization of catalysts, bioactive coatings, accelerated polymer degradation and analytics for micro-/nanoplastics quantification. Progress has been fuelled by recent advancements in protein engineering methodologies and advances in computational and analytical methodologies, which allow the design of, for instance, material-specific MBPs with fine-tuned binding strength for numerous demands in material science applications. A genetic or chemical conjugation of second (biological, chemical or physical property-changing) functionality to MBPs empowers the design of advanced (hybrid) materials, bioactive coatings and analytical tools. In this review, we provide a comprehensive overview comprising naturally occurring MBPs and their function in nature, binding properties of short man-made MBPs (<20 amino acids) mainly obtained from phage-display libraries, and medium-sized binding peptides (20-100 amino acids) that have been reported to bind to metals, polymers or other industrially produced materials. The goal of this review is to provide an in-depth understanding of molecular interactions between materials and material-specific binding peptides, and thereby empower the use of MBPs in material science applications. Protein engineering methodologies and selected examples to tailor MBPs toward applications in agriculture with a focus on plant health, biocatalysis, medicine and environmental monitoring serve as examples of the transformative power of MBPs for various industrial applications. An emphasis will be given to MBPs' role in detecting and quantifying microplastics in high throughput, distinguishing microplastics from other environmental particles, and thereby assisting to close an analytical gap in food safety and monitoring of environmental plastic pollution. In essence, this review aims to provide an overview among researchers from diverse disciplines in respect to material-(specific) binding of MBPs, protein engineering methodologies to tailor their properties to application demands, re-engineering for material science applications using MBPs, and thereby inspire researchers to employ MBPs in their research.

Peptide-Decorated Microneedles for the Detection of Microplastics

The escalating utilization of plastics in daily life has resulted in pervasive environmental pollution and consequent health hazards. The challenge of detecting and capturing microplastics, which are imperceptible to the naked eye, is exacerbated by their diminutive size, hydrophobic surface properties, and capacity to absorb organic compounds. This study focuses on the application of peptides, constituted of specific amino acid sequences, and microneedles for the rapid and selective identification of microplastics. Peptides, due to their smaller size and greater environmental stability compared with antibodies, emerge as a potent solution to overcome the limitations inherent in existing detection methodologies. To immobilize peptides onto microneedles, this study employed microneedles embedded with gold nanorods, augmenting them with sulfhydryl (SH) groups at the peptides' termini. The sensor developed through this methodology exhibited efficient peptide binding to the microneedle tips, thereby facilitating the capture of microplastics. Raman spectroscopy was employed for the detection of microplastics, with the results demonstrating successful attachment to the microneedles. This novel approach not only facilitates localized analysis but also presents a viable strategy for the detection of microplastics across diverse environmental settings.

A plasmonic gold nano-surface functionalized with the estrogen receptor for fast and highly sensitive detection of nanoplastics

Nanoplastics are a global emerging environmental problem whose effects might pose potential threats to the human's health. Despite the relevance of the issue, fast, reliable and quantitative in situ analytical approaches to determine nanoplastics are not yet available. The aim of this work was to devise an optical sensor with the goal of direct detecting and quantifying nanoplastics in seawater without sample pre-treatments. To this purpose, a nano-plasmonic biosensor was developed by exploiting an Estrogen Receptor (ER) recognition element grafted onto a polymer-based gold nanograting (GNG) plasmonic platform. The ER-GNG biosensor required just minute sample volumes (2 μL), allowed rapid detection (3 min) and enabled to determine nanoplastics in simulated seawater with a linear dynamic concentrations range of 1-100 ng/mL, thus encompassing the expected environmental loads. The nanostructured grating (GNG) provided remarkable performance enhancements, extending the measurement range across five orders of magnitude, thanks to the both the SPR and the localized SPR phenomena occurring at the GNG chip. At last, the ER-GNG biosensor was tested on real seawater samples collected in the Naples area and the results (∼30 ng/mL) were verified by a conventional approach (filtration and evaporation), confirming the ER-GNG sensor offers a straightforward and highly sensitive method for the direct in-field nanoplastics monitoring.

In Silico Design and Analysis of Plastic-Binding Peptides

Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist in interfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores were found to improve with increasing van der Waals interactions, although strengthening the intermolecular van der Waals interactions comes at the cost of introducing unfavorable electrostatic interactions. The best designs are enriched in amino acids with bulky side chains and possess hydrophobic and hydrophilic patches whose location depends on the adsorbed conformation. Future work will evaluate the top peptide designs in molecular dynamics simulations and experiment, enabling their application in microplastic pollution remediation and plastic-based biosensors.

Receptor-based detection of microplastics and nanoplastics: Current and future

Plastic pollution is an emerging environmental concern, gaining significant attention worldwide. They are classified into microplastics (MP; defined from 1 μm to 5 mm) and smaller nanoplastics (NP; <1 μm). NPs may pose higher ecological risks than MPs. Various microscopic and spectroscopic techniques have been used to detect MPs, and the same methods have occasionally been used for NPs. However, they are not based on receptors, which provide high specificity in most biosensing applications. Receptor-based micro/nanoplastics (MNP) detection can provide high specificity, distinguishing MNPs from the environmental samples and, more importantly, identifying the plastic types. It can also offer a low limit of detection (LOD) required for environmental screening. Such receptors are expected to detect NPs specifically at the molecular level. This review categorizes the receptors into cells, proteins, peptides, fluorescent dyes, polymers, and micro/nanostructures. Detection techniques used with these receptors are also summarized and categorized. There is plenty of room for future research to test for broader classes of environmental samples and many plastic types, to lower the LOD, and to apply the current techniques for NPs. Portable and handheld MNP detection should also be demonstrated for field use since the current demonstrations primarily utilized laboratory instruments. Detection on microfluidic platforms will also be crucial in miniaturizing and automating the assay and, eventually, collecting an extensive database to support machine learning-based classification of MNP types.

Adsorption of Different Pollutants by Using Microplastic with Different Influencing Factors and Mechanisms in Wastewater: A Review

The studies on microplastics are significant in the world. According to the literature, microplastics have greatly specific surface areas, indicating high adsorption capacities for highly toxic pollutants in aquatic and soil environments, and these could be used as adsorbents. The influencing factors of microplastic adsorption, classification of microplastics, and adsorption mechanisms using microplastics for adsorbing organic, inorganic, and mixed pollutants are summarized in the paper. Furthermore, the influence of pH, temperature, functional groups, aging, and other factors related to the adsorption performances of plastics are discussed in detail. We found that microplastics have greater advantages in efficient adsorption performance and cost-effectiveness. In this paper, the adsorptions of pollutants by microplastics and their performance is proposed, which provides significant guidance for future research in this field.

Bioanalytical approaches for the detection, characterization, and risk assessment of micro/nanoplastics in agriculture and food systems

This review discusses the most recent literature (mostly since 2019) on the presence and impact of microplastics (MPs, particle size of 1 μm to 5 mm) and nanoplastics (NPs, particle size of 1 to 1000 nm) throughout the agricultural and food supply chain, focusing on the methods and technologies for the detection and characterization of these materials at key entry points. Methods for the detection of M/NPs include electron and atomic force microscopy, vibrational spectroscopy (FTIR and Raman), hyperspectral (bright field and dark field) and fluorescence imaging, and pyrolysis-gas chromatography coupled to mass spectrometry. Microfluidic biosensors and risk assessment assays of MP/NP for in vitro, in vivo, and in silico models have also been used. Advantages and limitations of each method or approach in specific application scenarios are discussed to highlight the scientific and technological obstacles to be overcome in future research. Although progress in recent years has increased our understanding of the mechanisms and the extent to which MP/NP affects health and the environment, many challenges remain largely due to the lack of standardized and reliable detection and characterization methods. Most of the methods available today are low-throughput, which limits their practical application to food and agricultural samples. Development of rapid and high-throughput field-deployable methods for onsite screening of MP/NPs is therefore a high priority. Based on the current literature, we conclude that detecting the presence and understanding the impact of MP/NP throughout the agricultural and food supply chain require the development of novel deployable analytical methods and sensors, the combination of high-precision lab analysis with rapid onsite screening, and a data hub(s) that hosts and curates data for future analysis.