The ELISA is the mainstay for sensitive and quantitative detection of protein analytes. Despite its utility, ELISA is time-consuming, resource-intensive, and infrastructure-dependent, limiting its availability in resource-limited regions. Here, we describe a self-contained immunoassay platform (the "D4 assay") that converts the sandwich immunoassay into a point-of-care test (POCT). The D4 assay is fabricated by inkjet printing assay reagents as microarrays on nanoscale polymer brushes on glass chips, so that all reagents are "on-chip," and these chips show durable storage stability without cold storage. The D4 assay can interrogate multiple analytes from a drop of blood, is compatible with a smartphone detector, and displays analytical figures of merit that are comparable to standard laboratory-based ELISA in whole blood. These attributes of the D4 POCT have the potential to democratize access to high-performance immunoassays in resource-limited settings without sacrificing their performance.
"Non-fouling" polymer brush surfaces can greatly improve the performance of in vitro diagnostic (IVD) assays due to the reduction of non-specific protein adsorption and consequent improvement of signal-to-noise ratios. Herein, the development of synthetic polymer brush architectures that suppress adventitious protein adsorption is reviewed and their integration into surface plasmon resonance and fluorescent sandwich immunoassay formats is discussed. Also, highlighted is a novel, self-contained immunoassay platform (the D4 assay), that transforms time-consuming laboratory-based assays into a user-friendly and point-of-care format with a sensitivity and specificity comparable or better than standard ELISA directly from unprocessed samples. These advancements clearly demonstrate the This article is protected by copyright. All rights reserved. 2 utility of non-fouling polymer brushes as a substrate for ultra-sensitive and robust diagnostic assays that may be suitable for clinical testing, in field and laboratory settings.
Poly(ethylene glycol) (PEG), a linear polymer known for its “stealth” properties, is commonly used to passivate the surface of biomedical implants and devices, and it is conjugated to biologic drugs to improve their pharmacokinetics. However, its antigenicity is a growing concern. Here, the antigenicity of PEG is investigated when assembled in a poly(oligoethylene glycol) methacrylate (POEGMA) “bottlebrush” configuration on a planar surface. Using ethylene glycol (EG) repeat lengths of the POEGMA sidechains as a tunable parameter for optimization, POEGMA brushes with sidechain lengths of two and three EG repeats are identified as the optimal polymer architecture to minimize binding of anti‐PEG antibodies (APAs), while retaining resistance to nonspecific binding by bovine serum albumin and cultured cells. Binding of backbone‐ versus endgroup‐selective APAs to POEGMA brushes is further investigated, and finally the antigenicity of POEGMA coatings is assessed against APA‐positive clinical plasma samples. These results are applied toward fabricating immunoassays on POEGMA surfaces with minimal reactivity toward APAs while retaining a low limit‐of‐detection for the analyte. Taken together, these results offer useful design concepts to reduce the antigenicity of polymer brush‐based surface coatings used in applications involving human or animal matrices.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.