Ingestion of food contaminated with biologically active botulinum neurotoxin (BoNT) results in foodborne botulism. A few nanograms of the toxin can elicit symptoms. The toxin, which acts as a zinc-dependent endoprotease, is one of the most potent toxins known to humans. The “gold standard” mouse bioassay is time consuming and poses ethical concerns over the use of laboratory animals. This highlights the need for rapid and sensitive methods to supplement the mouse bioassay.<br/><br/>We developed a method based on Förster resonance energy transfer (FRET) to detect biologically active BoNT serotypes A and B which cause human botulism. A peptide containing a sequence of amino acid residues with an enzymatic cleavage site for the target BoNT serotype was labelled with a specific photoluminescent quencher (PLQ). A quantum dot (QD) was selected for each serotype detection based on its spectral overlap with the PLQ. By attaching the peptide to a QD through a terminal oligo-histidine region, QD photoluminescence was quenched. In the presence of biologically active BoNT, the specific peptide was cleaved and the quenching was removed, resulting in the recovery of QD photoluminescence.<br/><br/>The detection capability of this sensor was demonstrated with BoNT/A and /B light chains (LcA and LcB), which are the catalytic domains of the toxin serotypes. LcA in buffer was detected in 3 h with a detection limit of 4 nM (10 ng per sample), and LcB was detected with a detection limit of 0.4 nM (1 ng per sample). Linear relationship was found between the QD photoluminescence recovery and LcA/LcB concentration. The specificity of the sensor toward each serotype was evaluated. The detection and differentiation of LcA and LcB in a mixed sample was also demonstrated. The sensor was further evaluated in food samples spiked with the detection target. The performance of the sensor indicates its potential application as a rapid screening method for biologically active BoNT in foods.

Active botulinum neurotoxin serotypes A and B detection and differentiation by FRET-based sensor

254th National Meeting (2017)

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