Literature DB >> 21361387

Monitoring botulinum neurotoxin a activity with peptide-functionalized quantum dot resonance energy transfer sensors.

Kim E Sapsford1, Jessica Granek, Jeffrey R Deschamps, Kelly Boeneman, Juan Bautista Blanco-Canosa, Philip E Dawson, Kimihiro Susumu, Michael H Stewart, Igor L Medintz.   

Abstract

Botulinum neurotoxins (BoNTs) are extremely potent bacterial toxins that contaminate food supplies along with having a high potential for exploitation as bioterrorism agents. There is a continuing need to rapidly and sensitively detect exposure to these toxins and to verify their active state, as the latter directly affects diagnosis and helps provide effective treatments. We investigate the use of semiconductor quantum dot (QD)-peptide Förster resonance energy transfer (FRET) assemblies to monitor the activity of the BoNT serotype A light chain protease (LcA). A modular LcA peptide substrate was designed and optimized to contain a central LcA recognition/cleavage region, a unique residue to allow labeling with a Cy3 acceptor dye, an extended linker-spacer sequence, and a terminal oligohistidine that allows for final ratiometric peptide-QD-self-assembly. A number of different QD materials displaying charged or PEGylated surface-coatings were evaluated for their ability to self-assemble dye-labeled LcA peptide substrates by monitoring FRET interactions. Proteolytic assays were performed utilizing either a direct peptide-on-QD format or alternatively an indirect pre-exposure of peptide to LcA prior to QD assembly. Variable activities were obtained depending on QD materials and formats used with the most sensitive pre-exposure assay result demonstrating a 350 pM LcA limit of detection. Modeling the various QD-peptide sensor constructs provided insight into how the resulting assembly architecture influenced LcA recognition interactions and subsequent activity. These results also highlight the unique roles that both peptide design and QD features, especially surface-capping agents, contribute to overall sensor activity.

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Year:  2011        PMID: 21361387     DOI: 10.1021/nn102997b

Source DB:  PubMed          Journal:  ACS Nano        ISSN: 1936-0851            Impact factor:   15.881


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  10 in total

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