Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests

Limitations of the recognition elements in terms of synthesis, cost, availability, and stability have impaired the translation of biosensors into practical use. Inspired by nature to mimic the molecular recognition of the anti-SARS-CoV-2 S protein antibody (AbS) by the S protein binding site, we synthesized the peptide sequence of Asn-Asn-Ala-Thr-Asn-COOH (abbreviated as PEP2003) to create COVID-19 screening label-free (LF) biosensors based on a carbon electrode, gold nanoparticles (AuNPs), and electrochemical impedance spectroscopy. The PEP2003 is easily obtained by chemical synthesis, and it can be adsorbed on electrodes while maintaining its ability for AbS recognition, further leading to a sensitivity 3.4-fold higher than the full-length S protein, which is in agreement with the increase in the target-to-receptor size ratio. Peptide-loaded LF devices based on noncovalent immobilization were developed by affording fast and simple analyses, along with a modular functionalization. From studies by molecular docking, the peptide-AbS binding was found to be driven by hydrogen bonds and hydrophobic interactions. Moreover, the peptide is not amenable to denaturation, thus addressing the trade-off between scalability, cost, and robustness. The biosensor preserves 95.1% of the initial signal for 20 days when stored dry at 4 °C. With the aid of two simple equations fitted by machine learning (ML), the method was able to make the COVID-19 screening of 39 biological samples into healthy and infected groups with 100.0% accuracy. By taking advantage of peptide-related merits combined with advances in surface chemistry and ML-aided accuracy, this platform is promising to bring COVID-19 biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point of care, with social and economic impacts being achieved.

Graphene oxide-silver nanoparticle hybrid material: an integrated nanosafety study in zebrafish embryos

This work reports an integrated nanosafety study including the synthesis and characterization of the graphene oxide-silver nanoparticle hybrid material (GO-AgNPs) and its nano-ecotoxicity evaluation in the zebrafish embryo model. The influences of natural organic matter (NOM) and a chorion embryo membrane were considered in this study, looking towards more environmentally realistic scenarios and standardized nanotoxicity testing. The nanohybrid was successfully synthesized using the NaBH₄ aqueous method, and AgNPs (~ 5.8 nm) were evenly distributed over the GO surface. GO-AgNPs showed a dose-response acute toxicity: the LC₅₀ was 1.5 mg L^-1 for chorionated embryos. The removal of chorion, however, increased this toxic effect by 50%. Furthermore, the presence of NOM mitigated mortality, and LC₅₀ for GO-AgNPs changed respectively from 2.3 to 1.2 mg L^-1 for chorionated and de-chorionated embryos. Raman spectroscopy confirmed the ingestion of GO by embryos; but without displaying acute toxicity up to 100 mg L^-1, indicating that the silver drove toxicity down. Additionally, it was observed that silver nanoparticle dissolution has a minimal effect on these observed toxicity results. Finally, understanding the influence of chorion membranes and NOM is a critical step towards the standardization of testing for zebrafish embryo toxicity in safety assessments and regulatory issues.

Monitoring the Surface Chemistry of Functionalized Nanomaterials with a Microfluidic Electronic Tongue

Advances in nanomaterials have led to tremendous progress in different areas with the development of high performance and multifunctional platforms. However, a relevant gap remains in providing the mass-production of these nanomaterials with reproducible surfaces. Accordingly, the monitoring of such materials across their entire life cycle becomes mandatory to both industry and academy. In this paper, we use a microfluidic electronic tongue (e-tongue) as a user-friendly and cost-effective method to classify nanomaterials according to their surface chemistry. The chip relies on a new single response e-tongue with association of capacitors in parallel, which consisted of stainless steel microwires coated with SiO₂, NiO₂, Al₂O₃, and Fe₂O₃ thin films. Utilizing impedance spectroscopy and a multidimensional projection technique, the chip was sufficiently sensitive to distinguish silica nanoparticles and multiwalled carbon nanotubes dispersed in water in spite of the very small surface modifications induced by distinct functionalization and oxidation extents, respectively. Flow analyses were made acquiring the analytical readouts in a label-free mode. The device also allowed for multiplex monitoring in an unprecedented way to speed up the tests. Our goal is not to replace the traditional techniques of surface analysis, but rather propose the use of libraries from e-tongue data as benchmark for routine screening of modified nanomaterials in industry and academy.