Detection and Quantification of Biologically Active Botulinum

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Detection and Quantification of Biologically Active Botulinum Neurotoxin Serotypes A and B Using a F#rster Resonance Energy Transfer-based Quantum Dot Nanobiosensor Yun Wang, Harry Christopher Fry, Guy E. Skinner, Kristin M. Schill, and Timothy V. Duncan ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b08736 • Publication Date (Web): 25 Aug 2017 Downloaded from http://pubs.acs.org on August 26, 2017

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ACS Applied Materials & Interfaces

Detection and Quantification of Biologically Active Botulinum Neurotoxin Serotypes A and B Using a Fӧrster Resonance Energy Transfer-based Quantum Dot Nanobiosensor Yun Wang,† H. Christopher Fry,‡ Guy E. Skinner,† Kristin M. Schill,† Timothy V. Duncan†,*

†Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Bedford Park, IL 60501 ‡Center for Nanoscale Materials, Argonne National Laboratory, 9700 S. Cass Ave. Lemont, IL 60439 *Address correspondence to [email protected]

KEYWORDS. Förster resonance energy transfer (FRET), botulinum neurotoxin, nanobiosensor, quantum dot, food safety, nanotechnology, foods

ACS Paragon Plus Environment

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ABSTRACT. Botulinum neurotoxin (BoNT) is the most potent toxin known. The ingestion of food contaminated with biologically active BoNT causes foodborne botulism, which can lead to respiratory paralysis, coma and death after ingestion of as little as 70 μg for a 70 kg human. Because of its lethality and challenges associated with current detection methods, there is an urgent need for highly sensitive rapid screening techniques capable of detecting biologically active BoNT. Here we describe a Förster resonance energy transfer-based nanobiosensor that uses quantum dots (QDs) and two specific quencher-labeled peptide probes to detect and differentiate two biologically active forms of BoNT, serotypes A and B, which were responsible for 80% of human foodborne botulism cases in the U.S. from 2012-2015. Each peptide probe contains an enzymatic cleavage site specific to only one serotype. QDs were selected based on spectral overlap with the quenchers. In the presence of the target BoNT serotype, the peptide probe is cleaved and the quenching of QD photoluminescence (PL) is reduced, giving a signal that is easily detected by a PL spectrophotometer. This sensor performance was evaluated with light chains of BoNT/A and /B (LcA and LcB), catalytic domains of these respective serotypes. LcA and LcB were detected in 3 h with limits of detection of 0.2 and 2 ng/mL, respectively. Specificity of the sensor was evaluated, and no cross reactivity from non-target serotypes was observed with 2 h incubation. Because each serotype-specific peptide is conjugated to a QD with a unique emission wavelength, multiple biologically active BoNT serotypes could be detected in one PL spectrum. The sensor was shown to also be responsive to BoNT/A and /B holotoxins. Good performance of this sensor implies its potential application as a rapid screening method for biologically active BoNT/A and /B in the laboratory and the field.


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TABLE OF CONTENTS


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INTRODUCTION Botulinum neurotoxin (BoNT) is the most potent toxin known.1-2 It is produced by strains of Clostridium botulinum, Clostridium baratii, Clostridium sporogenes, and Clostridium butyricum, which are spore-forming anaerobic bacteria commonly found in soil.3-4 BoNT acts as a zinc-dependent endopeptidase and results in the proteolysis of soluble N-ethylmaleimide-sensitive-factor attachment protein receptor (SNARE) proteins and disruption of acetylcholine release in exocytosis, which leads to muscle paralysis and potentially death.3, 5 Systemic exposure to BoNT causes botulism, which most frequently occurs through food contaminated by the toxin, wound infection, or ingestion of spores by infants or other individuals whose digestive systems are not populated with enough competitive microflora to prevent infection by Clostridium. There are seven serologically distinct BoNTs (designated A to G), and botulinum neurotoxin serotypes A, B, E, and F (BoNT/A, /B, /E and /F) have been associated with human botulism cases.2 As reported to U.S. Centers for Disease Control and Prevention (CDC), there were 673 laboratory-confirmed botulism cases in the U.S. from 2012-2015, of which foodborne botulism accounted for 12%, infant botulism for 78%, wound botulism for 8%, and botulism of unknown or other etiology for 2%.6 Among the recent foodborne intoxication cases, BoNT/A accounted for the largest percentage (72%), followed by BoNT/E (20%) and BoNT/B (8%).6 Foodborne botulism typically results from improperly processed home-canned foods or refrigerated foods that are improperly stored. There is also concern that, due to its extremely low threshold for lethality, and the relative ease to produce toxin from soilborne spores, BoNT could become a potent bioterrorism or biological warfare agent.7-8 Although the incidence of botulism is low, the mortality rate is high if patients are not promptly diagnosed and immediately and appropriately treated.9 In the case of outbreaks due to commercial foods, the availability of rapid methods to detect BoNT is critical so that contaminated product lots can be quickly identified and the scale of the outbreaks can be minimized. Detection methods must be very


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sensitive due to the low threshold for lethal BoNT toxicity; they must be able to discriminate between active and inactive forms of the toxin because only active forms constitute a biological threat; and in many cases they must be able to discriminate between BoNT serotypes in order to provide public health agencies with epidemiological information to understand the relatedness of multiple outbreaks and devise strategies to prevent further outbreaks from occurring. Currently, the gold-standard method for BoNT detection is the mouse bioassay, which has a limit of detection (LOD) of BoNT/A at 10 pg in a 0.5 mL injection volume (0.02 ng/mL) and BoNT/B at 2 ng/mL.10-12 Although the bioassay is robust and routinely used in outbreak management, it takes up to 4 days to confirm the toxin by monitoring exposed animals for signs of flaccid paralysis, and it requires a high level of skill and the costly maintenance of animal handling facilities.13 Moreover, the number of selectively immunized animals required for a test can escalate quickly for outbreak scenarios in which serotyping analysis is desired. As a result of these limitations, there is an active interest in the development of rapid screening techniques that can be used to supplement the mouse bioassay for BoNT detection and quantification. Methods based on the interactions between antigen (toxin) and antibody, such as the enzyme-linked immunosorbent assay (ELISA), lateral flow tests, immuno-electrochemiluminescence, and immuno-PCR, have been applied to BoNT detection.10 However, the inactivation of the toxin due to, for example, thermal food processing, may result in the presence of BoNT epitopes but loss of enzymatic activity, such that the immunological assay results in a positive signal even though the tested food is safe to consume. Immunological assays are also dependent on access to high quality antibodies, which may vary in sensitivity or selectivity from batch to batch, have prohibitive cost or limited shelf life, or simply may not be readily available. Mass spectrometry14 and cell-based assays15 have been developed to detect and quantify biologically active BoNT, but expensive instrumentation and the need for skilled personnel limit them to laboratory settings.


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Recently, various biosensors have been developed for more cost-efficient and rapid detection of BoNT. Immunosensors16-22 and aptamer-based biosensors23-24 have both been heavily investigated. Both types may exhibit low LODs and short detection times, but suffer from similar drawbacks as other immunoassays (e.g., lack of discrimination between active and inactive forms of the analyte, as well as procurement and quality control issues related to antibodies). Some biosensors have been reported to provide information regarding the endopeptidase activity by detecting proteolytic products of BoNT substrates or monitoring changes in Förster resonance energy transfer (FRET) upon the cleavage of the substrates.25-30 Organic fluorescent dyes used in most FRET-based assays are susceptible to environmental factors such as pH change and photo-bleaching, and their broad-overlapping emission spectra impair their application in dual and triple labelling experiments for rapid serotype evaluation. Therefore, a simple, sensitive and rapid method that detects only biologically active BoNT with relatively low cost, possible multiplex capability to differentiate BoNT serotypes, and potential in-field application remains elusive despite its obvious advantages for foodborne botulism prevention and outbreak analysis. Here, we describe a novel FRET-based nanobiosensor that uses luminescent semiconductor nanocrystals (quantum dots, QDs) and dark quencher-labeled peptide probes to rapidly (on the order of hours) detect and quantify biologically active BoNT and differentiate serotypes A and B, the most common serotypes involved in food-related outbreaks. Figure 1 presents a scheme illustrating the probe design and function, which is based on quantifiable differences in the photoluminescence (PL) intensity of QDs reporters. The biorecognition elements for these probes are peptides that contain an amino acid sequence specific for BoNT/A or /B cleavage, a poly(histidine) sequence at the C-terminal for assembly on the QDs, and a dark quencher label (a dye with no native fluorescence) that quenches the QD PL only when the peptide chain is uncleaved (i.e., in the absence of the target BoNT).


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Figure 1. (A) Schematic of Förster resonance energy transfer (FRET)-based nanobiosensor for botulinum neurotoxin (BoNT) detection. The sensor is created by first incubating a biorecognition peptide with a test matrix that may or may not contain the matching BoNT serotype. In the presence of biologically active toxin, the peptide is cleaved by the toxin and the quencher and the binding module are separated; if biologically active toxin is not present, the peptide remains intact and the binding module remains attached to the quencher. The resulting mixture is subjected to bioconjugation conditions with quantum dots (QDs) chosen to exhibit strong FRET coupling to the corresponding quencher. When attached to QD, intact quencher-labeled peptide quenches the QD photoluminescence (PL), while cleaved peptide does not, resulting in either an “on” (biologically active toxin presence) or “off” (biologically active toxin absence) state of the QD PL. The PL intensity compared to that of the negative control correlates to the BoNT concentration. (B) Photograph demonstrating a measurable reduction of the quenching of the QD PL due to the presence of BoNT: Tube 1, QD with an emission maximum at 525nm (QD525) prior to being exposed to the quencher-labeled peptide; Tube 2, QD525 with uncleaved BHQ1-labeled peptide (BHQ1-pepA); and Tube 3, QD525 with BHQ1-pepA cleaved by BoNT/A light chain (LcA, 120 nM).

QDs have become popular donors in FRET-based bioanalytical assays due to their advantages over traditional organic fluorophores, including: broad excitation and narrow emission spectra; large Stokes shifts; long excited state lifetimes; size-tuneable emission from visible to infrared wavelengths;


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favorable platforms for attachment of multiple biorecognition molecules; and high degree of stability.3135

The sensor design employs a dark quencher rather than a second reporter dye as a FRET acceptor as it

avoids contamination of the QD’s spectral signature from the second reporter dye and eliminates the need for spectral deconvolution of multiple fluorescence signatures in the serotyping assay. QDs with different emission maxima were paired with dark quenchers according to their spectral overlap to maximize the FRET efficiency, and each QD-quencher pair was tethered with a peptide specific to one of the BoNT serotypes. In this way, each QD PL signature represents one serotype, and quantification of the two serotypes can be obtained in a single PL experiment by measuring the PL intensities at the peak maxima of the corresponding QDs. Since the detection scheme is based on the proteolytic activity of the toxin, we have optimized some parameters affecting the selectivity and sensitivity of this sensor using the catalytic domains or so-called light chains of BoNT/A (LcA) and BoNT/B (LcB), which represent the endopeptidase activity of the toxin and are commonly used as the target in BoNT detection assays.28-30, 36-37

After optimization of the sensor design, we also evaluated the sensor performance with BoNT

holotoxins, which more closely represent the native forms of the toxin that could be found in contaminated foods. This study represents the first time a FRET-style activity nanobiosensor has been used to detect and quantify toxicologically relevant concentrations of multiple BoNT serotypes with a single experiment on a timescale of hours.

MATERIALS AND METHODS Materials. 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), Tween-20, and dimethyl sulfoxide (DMSO) were purchased from Fisher Scientific (Pittsburgh, PA). ZnCl2 and NiCl2 were purchased from Acros (Morris Plains, NJ). HEPES potassium salt was obtained from Sigma-Aldrich (St. Louis, MO). Qdot® 525 ITKTM and 585 ITKTM Carboxyl Quantum Dots (QD525 and QD585) were purchased from Thermo Fisher Scientific (Waltham, MA). Black hole quencher®-1 (BHQ1) succinimidyl ester was from Bioresearch Technologies (Petaluma, CA). LcA, LcB, LcE and LcF (light chains of BoNT/A, /B, /E and /F)


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were from List Biological Laboratories (Campbell, CA). BoNT/A and /B holotoxins in phosphate buffered saline at the concentration of 1 mg/mL were purchased from Metabiologics, Inc. (Madison, WI). All peptide substrates were manufactured by the authors or were obtained from commercial sources, as described in the Supporting Information section. HEPES buffer (20 mM, pH 7.4 or pH 8.0) was prepared by titrating 20 mM HEPES solution with 20 mM HEPES potassium salt solution to the desired pH. Assay buffer for enzymatic reaction was prepared with 20 mM HEPES buffer (pH 8.0) and 0.1% (v/v) Tween-20. NiCl2 solution (0.25 mM) was prepared for facilitating the binding of peptides to QDs. Dilution buffer was prepared with 20 mM HEPES buffer (pH 7.4) and 0.1% (v/v) Tween-20. Each light chain (Lc) was reconstituted in dilution buffer to the concentration of 100 μg/mL and stored at -20°C until use. The holotoxin A or B was diluted from 1 mg/mL to 100 μg/mL with dilution buffer. The diluted holotoxins were stored at -20°C until use. All buffers were prepared using deionized water from a Type 1 Milli-Q water system (Millipore, Milford, MA) and sterile-filtered using 0.2 µm syringe filter and syringe. QD PL measurement. QD525 and QD585 were used for type A and B detection, respectively. An LS 55 Fluorescence Spectrometer (PerkinElmer, Waltham, MA) was used for all PL measurements. Samples with light chains were measured in sub-micro PL cuvettes (catalog #:16.100F-Q-10, Starna Cells, Atascadero, CA). For all experiments, the excitation wavelength was 400 nm. The emission spectra of QD525 were recorded in the range of 450 to 600 nm for LcA detection alone, while spectra of QD585 were recorded from 510 to 660 nm for LcB alone. For LcA and LcB mixed sample detection, the emission spectra were recorded from 450 to 660 nm. Reported spectra were the average of three scans acquired at 200 nm/min. In most cases involving Lc concentration quantification, the excitation slit was set to a bandwidth of 5 nm, and emission slit was set to 5 nm (LcA quantification) or 7 nm (LcB quantification). To determine the lowest detectable concentrations of Lc, the instrument sensitivity was increased by widening the emission slit to a bandwidth of 10 nm. As described in the results section, this significantly


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improved the LOD but did not impact the limit of quantification (LOQ) or improve the linear detection range. Samples with holotoxin were loaded into white flat-bottomed 96-well plates (Corning Inc, Corning, NY) sealed with non-fluorescing ultra-clear adhesive polyester films from VWR (Radnor, PA) for measurement. A top reading microplate reader in the LS 55 Fluorescence Spectrometer was employed. Sample excitation was performed at 400 nm, while the emission was recorded at 526, 528, or 530 nm for type A detection, and at 584, 585, or 586 nm for type B detection. Samples in 96-well plates were measured with and without a 430 nm emission filter for background PL comparison. LcA and LcB detection. LcA (100 μg/mL) and BHQ1-pepA (1.6 mM) stock solutions were diluted to desired concentrations in assay buffer before each experiment. Fifty μL of the diluted LcA solution were mixed with 10 μL of BHQ1-pepA at the optimal concentration (see Supporting Information for details) in a microcentrifuge tube, and incubated in an orbital hybridization shaking oven (Major Science, Saratoga, CA) at 37°C, 50 rpm. After the incubation, the samples were removed from the hybridization oven. QD525 (3 μL of a 0.8 µM solution was diluted from 8 µM stock using deionized water; the amount of QDs in each sample was 2.4 pmol) and NiCl2 (5 µL, 0.25 mM) were then added to each sample (shown in Figure 1A). The samples were incubated at room temperature for a period of time determined via optimization studies (see Supporting Information for details). After incubation, deionized water was added to each sample to bring the volume to 200 μL, and the samples were transferred to sub-micro PL cuvettes for PL measurement. Negative control samples (0 nM LcA) were prepared using 50 μL assay buffer instead of LcA solution, while all other reagents and procedures were the same as LcA samples. For comparison, QD-only samples were prepared using total 60 μL assay buffer instead of LcA and BHQ1-pepA solution. The sensor response was characterized by the intensity at the QD PL peak maximum exhibited by the samples exposed to LcA compared to that of the negative control sample:


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ௌ ௌబ

௉௅

= ௉௅

(1)

ವಲ

where S represents the PL signal of sample with LcA, and S0 represents PL signal of the negative control sample. PL and PLDA are the PL intensities of the LcA sample and negative control sample, respectively. This ratio was defined as the sensor signal. LOD was determined as the lowest LcA concentration that generated a repeatable PL intensity at the QD peak maximum that was a factor of 3 standard deviations larger than the mean value of the peak maximum intensity exhibited by the negative control samples. A signal that was 5 standard deviations above the QD PL peak maximum exhibited by the negative control samples was used as the LOQ. The cleavage products were analyzed by liquid chromatography-electrospray ionization−Vme-of-flight (LC-ESI-TOF) mass spectrometry using an Agilent 6210A (Agilent Technologies, Santa Clara, CA) at Northwestern University (Evanston, IL). The specificity of the sensor to LcA was tested by introducing 50 μL of a 40 or 80 nM LcB, LcE, and/or LcF solution to the BHQ1-pepA at the same point that LcA would normally be added in the sensitivity experiments. Two or four hour incubation of light chains and BHQ1-pepA was conducted, followed by one hour incubation with QD525 in assay buffer supplemented with NiCl2. The specificity of the sensor to biologically active toxin was conducted using 120 nM LcA, which was heat-denatured in a microcentrifuge tube in a boiling water bath for 5 min before the test. One-way analysis of variance (ANOVA) and t test with significance level of 0.05 were used to compare signals for non-target light chains which were above the detection threshold (PL intensity threshold to determine LOD, as described above) and signals of target analytes. Similar procedures to those described above were followed to detect LcB with the optimal QSY9-pepB concentration and peptide-QD incubation time (see Supporting Information for details). Sensor specificity to LcB was evaluated with LcA, LcE and/or LcF at different concentrations and with 2 or 4 h


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incubation time at 37°C. Heat-denatured LcB at 120 nM was also tested to demonstrate the specificity to biologically active toxin. Procedures for holotoxin detection and differentiation of LcA and LcB in mixed samples are provided in the Supporting Information section.

RESULTS AND DISCUSSION Biorecognition peptide design and substrate cleavage. BoNT is expressed as a 150-kDa single polypeptide and post-translationally cleaved by an endogenous protease to form a dimeric structure (holotoxin) consisting of a 50-kDa N-terminal catalytic domain, commonly referred to as the light chain (Lc), and a 100-kDa heavy chain that can be further proteolyzed into two 50-kDa domains: a central translocation domain and C-terminal receptor binding domain.5, 38 The Lc and heavy chain are connected by a disulfide bond.38 The Lc of each BoNT serotype cleaves at a specific site of one of the following SNARE proteins: synaptobrevin, syntaxin, or synaptosomal-associated protein 25 (SNAP-25).38 Type A cleaves the peptide bond between Gln197 and Arg198 of SNAP-25, type B cleaves between Gln76 and Phe77 of vesicle-associated membrane protein-2 (VAMP-2), type E cleaves between Arg180 and Ile181 of SNAP-25, and type F cleaves between Gln58 and Lys59 of VAMP-2.39-41 All of these proteins play critical roles in the docking of synaptic vesicles in mammalian neurons and the subsequent transport of neurotransmitters, the disruption of which causes the symptoms of botulism. The biorecognition elements of the nanobiosensor developed herein are short peptides containing amino acid sequences that mimic the cleavage sites of the respective target BoNT serotypes. The peptide design contains three modules: quencher label, substrate module, and binding module. In choosing appropriate quencher elements, it has been reported that dark quencher-black hole quenchers® (BHQ) show less variation than other dye equivalents,42 and therefore improve the sensitivity and reproducibility of the detection. BHQ1 (black hole quencher-1)-labeled peptide for type A detection (BHQ1-pepA) was designed based on the minimum BoNT/A substrate sequence,43 which


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consists of the residues 187-202 of SNAP-25. Glu194 in the native sequence was replaced by glutamine to increase the proteolysis rate.44 For a simple binding procedure, we appended 6 histidine residues to the C-terminal of substrate module. Research by Yao and coworkers showed high affinity of poly(histidine) to ITKTM QDs with amphiphilic block-copolymer-type surface in the presence of Ni2+.45 BHQ1 has a broad absorption spectrum with a maximum at 535 nm and exhibits good overlap with the emission band of QD525 (see the Supporting Information, Figure S1A); the overlap of the spectra is necessary for efficient FRET between the quencher and the QD. The ITKTM carboxyl quantum dot with an emission maximum at 525nm (QD525) has a quantum yield of 0.81, and the extinction coefficient of BHQ1 at its absorption maximum is 34,000 cm-1M-1, as reported by the manufacturers. A Förster critical distance (R0) was calculated to be 56 Å (eq. S3). BHQ1 was used to label the N-terminal of the substrate module. With the quencher and binding module on different terminals, once the substrate is cleaved by biologically active BoNT, the binding module and the quencher are no longer linked. Therefore, when binding to QDs through the poly(histidine) module, the C-terminal cleavage product can’t quench the QD (Figure 1A). The concept is illustrated by photographs that show initial bright PL of QDs before peptide binding (Figure 1B, Tube 1), quenching of QD525 PL after binding to intact BHQ1-pepA (Figure 1B, Tube 2), and reduced quenching of QD 525 PL after binding to LcA cleavage products of BHQ1-pepA (Figure 1B, Tube 3). Quantitative measurement of the QD525 PL after binding of BHQ1-pepA cleavage products, and therefore active BoNT concentration, is conveniently facilitated using a standard fluorescence spectrometer. Cleavage of BHQ1-pepA was verified by mass spectrometry (Figure S2). LcA, which is the catalytic domain of BoNT/A, is expected to cleave the peptide and yield two cleavage products with calculated molecular weights of 1761 and 1428 Da. With a starting concentration of 160 μM BHQ1-pepA and 333.3 nM LcA, the intact BHQ1-pepA (3172 Da, Figure S2A) and N-terminal cleavage product with molecular weight of 1761 Da (Figure S2B) were observed. It has been reported that


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sometimes one cleavage product may be missing in the mass spectra (C-terminal cleavage product in this case), but the detection of either one or two cleavage products is the indication of cleavage.46 The QSY9-labeled peptide for BoNT/B detection (QSY9-pepB) contains three modules analogous to those described above for the BoNT/A biorecognition peptide. QSY® dyes are nonfluorescent diarylrhodamine chromophores, which are also reported as being very effective dark quenchers.47 The substrate module for the BoNT/B probe consists of residues 60 to 94 of human VAMP-2, with the LcB cleavage site between Gln76 and Phe77 in the native sequence.37 Leu70 in the native sequence was replaced by Lys for attaching the QSY9 quencher. As with BHQ1-pepA, the poly(histidine) binding module was directly appended to the C-terminal of substrate module. The superimposed donor (QD585) emission and acceptor (QSY9) absorption spectra exhibit good overlap, as shown in the Supporting Information (Figure S1B). Based on a QD585 quantum yield of 0.78 and extinction coefficient of QSY9 at the absorption maximum as 88,000 cm-1M-1 (as reported by the manufacturers), the Förster critical distance (R0) was predicted to be 67 Å (eq. S3). Optimization of peptide:QD ratio and bioconjugation reaction time. Considerable effort was expended to optimize the sensor performance by studying the assembly of quencher-labeled peptides on QD surfaces. Peptide:QD molar ratios and reaction times were varied systematically to determine optimal values that balance adequate quenching of QDs at the reference point (no BoNT present) with incubation time and also limiting potential interference by excess peptide. This optimization was done for both BoNT/A and BoNT/B sensors. Additional details on this process are provided in the Supporting Information. The optimized peptide:QD ratio and reaction time for BoNT/A was 20 and 1 h, respectively; for the BoNT/B sensor, these values were 100 and 0.5 h, respectively. Unless noted otherwise, these optimized conditions were used for all sensing experiments described below.


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Sensitivity and selectivity of LcA detection. LcA is the catalytic domain of BoNT/A; although it possesses endopeptidase activity, it is not toxic in vivo by itself because the heavy chain binds the BoNT complex to nerve cells and assists in the transfer of the proteolytic Lc into the target cell. We used LcA to optimize the sensor performance rather than the full biological form of BoNT/A because the detection is based on the endopeptidase activity of the Lc and working with the non-toxic Lc is more convenient since it is not a regulated as a select agent; 48 a preliminary evaluation of the sensor with the full holotoxin form is presented later in this manuscript. Figure 2A plots PL spectra of QD525 samples that were conjugated to BHQ1-pepA probes (1 h reaction time) after the probes were incubated for 2 h with LcA concentrations ranging from 0 to 240 nM. Compared with negative control (NC) samples that were not exposed to LcA (0 nm LcA), the QD525 PL intensity was observed to increase after conjugation to BHQ1-pepA that was incubated in the presence of LcA, representing a positive detection event. Figure 2B plots the quantitative sensor signal (S/S0, PL peak intensity relative to that of negative control, eq. 1) against the LcA concentration for three incubation times (2, 4, and 6 h). Under all incubation conditions, the sensor signal scaled linearly with the analyte concentration over a range from 8 nM to 200 nM, with 8 nM as the LOQ. R2 values of 0.977, 0.989 and 0.991 were obtained from 2, 4 and 6 h linear fit, respectively, indicating good linearity over this range. A 4 h incubation of LcA and BHQ1-pepA prior to conjugation to QD525 yielded a higher sensitivity (larger slope) compared to 2 h incubation; further extending the incubation time to 6 or even 20 h (not shown) did not result in improved sensitivity, which implies that LcA cleaved substantial amount of BHQ1-pepA in 2 h and the enzymatic reaction reached saturation after 4 h. We also evaluated LcA concentrations in excess of 200 nM (data not shown) and observed that the sensor response began to exhibit signs of decreased linearity, and may approach an asymptotic limit of S/S0 values of approximately 3.5 for a 4 h incubation. At these high LcA concentrations, the substrate peptide concentration and the diffusion and attachment of peptide to QD surface may begin to limit the


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reaction. (Additional information on the curve fitting used for these data is provided in the Supporting Information.) The reproducibility of the sensor was evaluated based on relative standard deviation (RSD). Average RSD of the quantification experiment was calculated to be ±5.28%, ±7.67% and ±8.71% for 2, 4 and 6 h incubation times, respectively, showing good reproducibility of the sensor; RSD values less than 20% are typically indicative of acceptable reproducibility.49

Figure 2. Detection of LcA using BHQ1-pepA and QD525. (A) Typical sensorgrams (PL spectra) observed during detection of different concentrations of LcA. The spectra were obtained from QD samples introduced to BHQ1-pepA that was incubated with LcA of various concentrations for 2 h. The QD concentration was 0.24 pmol and the peptide:QD ratio was 20. (B) The sensor signal (S/S0, PL peak intensity peak of QDs in the presence of BHQ1-pepA that was incubated with LcA relative to that of the negative control sample) obtained with a peptide:QD ratio 20 is plotted as a function of the LcA concentration, with LcA/peptide incubation times of 2 h (blue circles), 4 h (red squares) and 6 h (green triangles). Linear relationships were found between the sensor signal and LcA concentration, as


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indicated by the black fit lines. NC: negative control. Linear equation for 2 h: y=0.0071x+1.123; 4 h: 0.0102x+1.213; 6 h: y=0.0093+1.054 (y: S/S0, x: LcA concentration in nM).

Although 8 nM represents the approximate LOQ for the LcA assay, it was hypothesized that the assay sensitivity was primarily limited by the ability of the PL spectrophotometer to discriminate increasingly small differences between the assay control and QD525 conjugated to vanishingly low concentrations of BHQ1-pepA cleavage products. Instrument sensitivity could be drastically increased at a negligible cost to spectral resolution by widening the emission slits on the PL spectrophotometer to a bandwidth of 10 nm (from the standard value of 5 nm). In this more sensitive detection scheme, we were able to reliably detect positive LcA cleavage of BHQ1-pepA at Lc concentrations as low as 4 pM (0.2 ng/mL, 10 pg per sample), which represents the LOD for this LcA nanobiosensor. However this scheme did not extend the linear quantitation range to lower limits because at LcA concentrations lower than 8 nM we found inconsistent values for the measured luminescence intensity regardless of the emission slit widths. We noted that in most practical use scenarios, the LOD is a more critical parameter than the LOQ, as public health experts engaged in an outbreak response may be more concerned with identifying presence or absence of BoNT than knowing the precise BoNT concentration. Nevertheless, this nanobiosensor does exhibit a quantifiable detection range in addition to a low threshold for binary “yes/no” Lc detection, meaning it offers a degree of flexibility that some currently available detection methods lack. 11, 14-15 The specificity of the LcA detection sensor was evaluated using light chains of other BoNT serotypes: LcB and LcF, which cleave a different protein substrate (VAMP-2), and LcE, which cleaves the same SNAP-25 protein as LcA. Figure 3A plots the response (S/S0 value) for the LcA sensor in the presence of various combinations of LcA, LcB, and LcE after a 4 h incubation with BHQ1-pepA. Figure 3B shows a similar test using a 2 h incubation time, and also includes incubation with LcF and a heat-denatured form of LcA. Data plotted in these figures shows that there was no cleavage of BHQ1-pepA by LcB or LcF, but weak reactivity was observed with LcE during the 4 h test. LcE at a concentration of 80 nM resulted in an


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S/S0 not significantly different (p>0.05) from LcA at 4 and 8 nM with 4 h BHQ1-pepA and Lc incubation time, as shown in Figure 3A, suggesting that LcE may be a weak interference for the LcA assay. This weak reactivity of LcE with BHQ1-pepA may be due to the fact that both BoNT/A and BoNT/E target the same substrate, SNAP-25, though they cleave the substrate at different sites. BoNT/E cleaves between Arg180 and Ile181, while BoNT/A cleaves between Gln197 and Arg198.40 In addition, the minimum amino acid sequence for BoNT/A cleavage includes adjacent arginine and isoleucine, offering a potential cleavage site for LcE. Note that if the Lc and BHQ1-pepA incubation time was reduced to 2 h (Figure 3B), LcE at 40 or 80 nM did not result in false positive signals. Figure 3B also shows that when LcA, LcB and LcE were incubated for 2 h in one pot with BHQ1-pepA, where the LcB and LcE concentrations were double that of LcA, the detection of LcA was not affected, as the sensor response to the mixed sample was not significantly different (p>0.05) from a sample in which BHQ1-pepA was incubated with LcA only. Because this sensor was designed only to detect biologically active toxin, the specificity test was also expanded to include an incubation of BHQ1-pepA with LcA that was deactivated by heating in boiling water for 5 min. The S/S0 of heat-treated LcA was diminished significantly compared to LcA that was not heat treated (Figure 3B), indicating that the sensor is not reactive to denatured toxin.


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Figure 3. Specificity tests for LcA detection. The bars show the measured signal when BHQ1-pepA was incubated in the presence of other BoNT Lc serotypes. (A) The specificity test with 4 h Lc and peptide incubation time; and (B) the specificity test with 2 h Lc and peptide incubation time. D-LcA: LcA deactivated by heating in boiling water bath for 5 min. LcB/E/F: light chain of botulinum neurotoxin serotype B/E/F. Letters above the bars (a, b and c) indicate statistical groups (significance level of 0.05) for those samples with signals (S/S0) above the detection threshold. Samples not sharing the same letters exhibit a significant difference from each other.

Sensitivity and selectivity of LcB detection. The LcB sensor response was evaluated in a manner identical to the LcA sensor. LcB was first incubated with QSY-pepB for 2, 4 or 6 h, and then the cleavage


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products were reacted with QD585 for 30 min with the QSY9-pepB:QD585 optimized ratio of 100. The QD585 PL intensity was observed to increase with increasing LcB concentration. The sensor signal (S/S0) for 2, 4, and 6 h is plotted vs. LcB concentration in Figure 4A. The LOD (determined with emission slits set to a bandwidth of 10 nm to increase instrument sensitivity, as noted above) was determined to be 40 pM (2 ng/mL, 100 pg per sample). The LOQ was determined to be 2 nM. Good reproducibility in the quantification experiment was obtained, with RSD less than 4% for all three different incubation times. Over a concentration range of 2 nM to 280 nM, there is a linear relationship between S/S0 and the natural logarithm of the LcB concentration. The sensitivity became higher with longer incubation times, as shown by a larger slope, indicating slower reaction between LcB and QSY9-pepB than the reaction between LcA and BHQ1-pepA. This trend was also observed by plotting the S/S0 values for incubation of QSY9-pepB in the presence of 40 nM LcB as a function of incubation time (Figure 4B). The S/S0 value increased 9.8% from 2 h to 4 h incubation, 15.0% from 2 h to 6 h and 26.2% from 2 h to 20 h. The logarithmic relationship between the sensor response and LcB concentration (compared to the linear relationship for the LcA sensor) may be due to: 1) differing affinity between the two recognition peptides and the target light chains; 2) the binding kinetics of different peptides to QDs, especially due to the different surface area of the two QDs and the spatial structure of the peptide-quencher complexes; and/or LcB-concentration dependence of non-FRET quenching of QD by LcB (see below).


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Figure4. Detection of LcB using QSY9-pepB and QD585. (A) The sensor signal (S/S0, PL peak intensity of QDs in the presence of QSY9-pepB that was incubated with LcB relative to that of the negative control sample) obtained with a peptide:QD ratio 100 is plotted as a function of LcB concentration, with LcB and peptide incubation times of 2 h (blue circles), 4 h (red squares) and 6 h (green triangles). A linear relationship was found between the sensor signal and natural logarithm of LcB concentration, as indicated by the black fit lines. Equation for 2 h: y=0.270ln(x)+0.761; 4 h: 0.293ln(x)+0.806; 6 h: 0.331ln(x)+0.820 (y: S/S0, x: LcB concentration in nM). (B) The sensor signal is plotted vs. different LcB and QSY9-pepB incubation times. The LcB concentration was 40 nM. (C) The sensor signal obtained with a peptide:QD ratio of 120 plotted as a function of LcB concentration, with a 2 h LcB and peptide incubation time. A linear relationship was found between the sensor signal and LcB concentration. Linear equation: y=0.00742x+1.183 (y: S/S0, x: LcB concentration in nM). (D) The sensor signal obtained with different peptide:QD ratios are plotted as a function of LcB concentration, with a 4 h LcB and peptide incubation time.

In initial optimization studies, the peptide:QD ratio for the functional sensor was selected to be the value at which the PL response of the quenched QD PL was approximately 10% of the PL response of the


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native QDs (see Supporting Information). However, since the peptide:QD ratio may play an important role in the peptide interaction with LcB and QDs, the effect of this ratio on the detection signal was investigated. As shown in Figure 4C for a 2 h incubation of LcB and QSY9-pepB, when the QSY9pepB:QD585 ratio was increased to 120 from a benchmark value of 100, an approximately linear relationship between the sensor signal (S/S0) and LcB concentration was obtained in the range of 0.4 to 280 nM. (Additional information on the curve fitting for the data shown in Figure 4C, including nonlinear curve fitting, is provided in the Supporting Information) It is noted that the LOQ was lower (0.4 nM, compared to 2 nM) when the peptide:QD ratio increased. The S/S0 values for higher LcB concentrations (≥160 nM) increased compared to S/S0 values observed using a QSY9-pepB:QD585 ratio 100 (Figure 4A), but not at lower LcB concentrations. We also performed a 4 h incubation experiment with QSY9pepB:QD585 ratios ranging from 100 to 200, and the S/S0 values as a function of LcB concentration for these experiments are plotted in Figure 4D. In these cases we observed increased S/S0 values at higher LcB concentrations as well. However, when S/S0 reached values exceeding 3, the sensor response plateaued, even when the QSY9-pepB:QD585 ratio was increased up to 200. The PL peak intensity at the highest LcB concentration tested (280 nM) was only 28.9% of the PL peak intensity of native QD585 (no quencher); at a sufficiently high concentration of LcB and a sufficiently long incubation time, 100% of the QSY9-pepB recognition elements should be cleaved, which should theoretically yield no change to the QD PL intensity. This phenomenon implies that there may be a limit to the extent of peptide cleavage or that there is a weakly deleterious photophysical interaction between the QDs and either the cleaved peptide fragments or the Lc that lead to some QD quenching unrelated to FRET. Luminescence quenching resulting from non-specific adsorption of the quencher on QD surfaces may also explain this phenomenon.50 Further exploration of the effect showed that PL of pristine QD585 was partially quenched after incubation with LcB for 1 h. Note that for LcA detection, we also observed that the sensor signal reached a plateau at S/S0 >3. However, no quenching of pristine QD525 was observed by


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LcA, implying a unique PL quenching interaction between QD585 and LcB. Although this effect may limit these sensors’ respective high end linear ranges, the data show that it does not adversely impact the sensors’ limits of detection or quantification. As with the LcA sensor, we evaluated the specificity of the LcB sensor using light chains for BoNT serotypes other than B, with a peptide:QD ratio of 100. Among the four serotypes causing human botulism, BoNT/F cleaves the same protein substrate as BoNT/B, but LcF did not appear to interfere with LcB detection (Figure 5A), as incubation of 40 nM LcF with QSY9-pepB did not generate a signal higher than the detection threshold (red line) which is defined as 3 standard deviations above the mean value exhibited by the samples without any Lc. LcA and LcE were also tested using a 4 h peptide and Lc incubation at 37°C. These tests both resulted in weak false positive signals, which was unexpected because they typically are active toward a different protein substrate and there is no amino acid sequences in QSY9-pepB that are a good match to their target cleavage sites. We performed a statistical analysis between the sensor signal (S/S0) of non-targets and target at different concentrations, and found that LcA and LcE at 40 and 80 nM each resulted in a signal interfering with the detection of LcB less than 4 nM (non-target generated a S/S0 significantly larger than, or not significantly different from S/S0 of LcB, Pcritical = 0.05). When all four light chains were mixed in one sample, each at 40 nM, a large variation was observed between the replicates even though the mean value was very close to the experiment where QSY9-pepB was incubated only with 40 nM LcB, indicating there were significant interferences from the non-targets. When the incubation time was reduced to 2 h (Figure 5B), there was no detection from either LcA or LcE at 80 nM, as their signals are below the detection threshold (red line), implying that the cleavage reaction between these non-targets and pepB was still much slower than the target LcB. Therefore reducing the incubation time is an effective way to reduce the prevalence of interferences by other BoNT serotypes.


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Figure 5. Specificity tests for LcB detection. The bars show the measured signal when QSY9-pepB was incubated in the presence of other BoNT Lc serotypes. (A) The specificity test with 4 h Lc and peptide incubation time; and (B) the specificity test with 2 h Lc and peptide incubation time. D-LcB: LcB deactivated by heating in boiling water bath for 5 min. Letters above the bars (a, b and c) indicate statistical groups (significance level of 0.05) for those samples with signals (S/S0) above the detection threshold. Samples not sharing the same letters exhibit a significant difference from each other.

Detection and discrimination of LcA and LcB in mixed samples using a single PL experiment. The goal of this study is to develop a method to detect and differentiate BoNT serotypes. To demonstrate this capability, we selected QD525 and QD585 for LcA and LcB detection, respectively, as these two QDs exhibit minimally overlapping spectral signatures. This is one of the signature advantages of QDs as donors in FRET-based detection assays compared to conventional organic chromophores. In addition, different sized QDs can be excited with the same excitation energy.51 A detection method for mixed samples of LcA and LcB was devised in which the mixed sample was divided into two equal volumes. Each volume was incubated in the presence of one of the quencherpeptide probes, followed by incubation with a matching QD under conditions determined for the single Lc detection experiments. The incubation and bioconjugation conditions for each Lc type are provided in


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the Materials and Methods section. The two reaction mixtures were then recombined into a spectrometric cuvette and PL spectra were acquired to determine relative concentrations of LcA and LcB in the mixture.

Figure 6. Sensorgrams (PL spectra) of QD525 and QD585 used in combination with BHQ1-pepA and QSY9-pepB for detecting LcA and LcB in mixed samples, with 2 h Lc and peptide incubation times. A PL peak intensity higher than the negative control sample (0 nM of LcA and LcB) at 525 nM represents LcA detection, while that at 585 nm represents LcB detection.

Figure 6 shows sensorgrams (PL spectra) acquired when BHQ1-pepA and QSY9-pepB probes were exposed under this scheme to various mixtures of LcA and LcB. PL peaks at 525 nm and 585 nm represent the relative quantities of LcA and LcB, respectively, detected in each mixture. To quantify concentrations of LcA and LcB in each mixture, the previously determined conditions and associated linear equations for LcA (Figure 2B) and LcB (Figure 4C) were used. The recovery for 4 h incubation of light chains and peptides was also evaluated, using QSY9-pepB: QD585 ratio of 100 and the equation from Figure 4A for LcB quantification, and BHQ1:pepA: QD525 ratio of 20 and the linear equation from Figure 2B for LcA quantification. The determined Lc concentrations and percentages of recovery (the amount of Lc detected divided by the theoretical amount) are listed in Table 1. Only samples that contain light chains with concentrations higher than the LOQs (LcA: > 8 nM; LcB: >0.4 nM) were listed in the table. Better accuracy of the sensors at theoretical Lc concentrations lower than 40 nM and with


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shorter incubation time was indicated by the fact that recovery percentages were closer to 100%. The high percentage (162.4%) for LcB with 4 h incubation is consistent with the 4 h specificity test, where 40 nM LcA interfered with LcB detection (Figure 5A). Performance of the sensor in this case could be improved by separating different serotypes before the detection in order to minimize the interference. The overall good recovery obtained from the LcA/B differentiation test implies potential multiplex quantification capability. Table 1. The recovery a of BoNT LcA and LcB serotypes from mixed samples using the FRET-based nanobiosensor.

Lc & peptide incubation time = 2 h

Mixed sample b set

LcA spiked (nM)

LcA determined by FRET sensor (nM)

LcA recovery (%)

RSD (%)

LcB spiked (nM)

LcB determined by FRET sensor (nM)

LcB recovery (%)

RSD (%)

1

20

25.41

125.7

18.3

20

21.21

106.1

2.7

2

40

46.28

115.7

21.7

4

3.95

98.9

11.9

3

80

99.72

124.7

4.7

40

57.47

143.7

8.2

2h average recovery Lc & peptide incubation time = 4 h 4h average recovery

122.0

116.2

1

2

< LOQ

c

N/A

N/A

2

2.06

103.2

0.4

2

4

< LOQ

c

N/A

N/A

4

3.77

94.3

7.5

3

20

28.62

143.1

15.1

20

18.84

94.2

17.9

4

40

51.13

127.8

16.4

40

64.97

162.4

7.4

135.5

117.0

a

Recovery is defined as the amount of Lc experimentally detected in the sample mixture, as determined from the respective linear relationship measured during experiments with only a single Lc, compared to the theoretical (spiked) concentration in the mixture. b

Spiked LcA and LcB concentrations in the same row are the concentrations that comprise the mixed sample. c

The spiked concentration is lower than the limit of quantification (LOQ).


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Detection of BoNT/A and /B holotoxins. Although detection of BoNT Lc is routinely used to demonstrate performance of BoNT detection and quantification methods, in real life situations a practical sensor must be able to detect active forms of the holotoxin, as this is the native BoNT form that would potentially contaminate foods and cause illness in people. Most activity-based sensor studies, however, evaluate sensor performance with Lc, despite the fact that holotoxin and isolated Lc forms could respond to detection events differently. To be confident in the practical utility of our sensor, we explored the sensor’s performance using the BoNT holotoxin and most of the optimized conditions presented above. The only significant modification was the composition of the assay buffer. Assay buffer with Zn2+ (0.6 mM) was found to yield a better detection signal (higher S/S0) than without or low concentration Zn2+ (≤0.3 mM, data not shown). This is consistent with previous studies showing that Zn2+ plays a structural and catalytic role in BoNT/A.52-53 Without further optimization, we detected BoNT/A holotoxin at concentrations ≥ 6.67 nM, and BoNT/B holotoxin at ≥ 2.67 nM, as shown in Table 2. Previous studies have shown that free Lc is a more catalytically active form of BoNT.5 Therefore, it is expected that when detecting holotoxin, there will be less cleavage of the biorecognition peptide with the same incubation time than with free Lc. We stress that significant improvements in the sensitivity of the assay for holotoxin BoNT forms could likely be achieved by adjusting the pH, adding reductants to assist in the release of free Lc from the holotoxin, modifying the composition of the assay buffer, or changing the measurement parameters of the fluorimeter. We are currently optimizing these procedures and anticipate that the limit of detection will be substantially improved for this more natural form of the toxin. Nevertheless, this is the first time that a rapid FRET-based nanosensor has been used to positively detect active forms of BoNT holotoxin.


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Table 2. The results of BoNT/A and /B holotoxin detection using the FRET nanobiosensor. BoNT/A concentration (nM)

ng/sample

Detection

BoNT/B concentration (nM)

ng/sample

Detection

1.33

10

+/-

1.33

10

+/-

2.67

20

+/-

2.67

20

+

6.67

50

+

6.67

50

+

13.33

100

+

13.33

100

+

26.67

200

+

26.67

200

+

53.33

400

+

53.33

400

+

Samples detected by the sensor are marked as “+”, which generated a PL intensity at the QD peak maximum at least 3 standard deviations above the mean value exhibited by the negative control samples. “-“: not detected by the sensor. “+/-“: some replicates were not detected. We note that at present the detection method for BoNT holotoxins is not optimized and so 6.67 and 2.67 nM represent approximate LODs for type A and B, respectively. With further optimization of the assay parameters we anticipate a more quantitative determination of BoNT holotoxin concentration is achievable, and furthermore the LODs can be substantially improved.

CONCLUSIONS We developed a simple and rapid method to detect and discriminate multiple biologically active BoNT serotypes based on FRET between QDs and specific BoNT-cleavable quencher-tagged peptides. The method is intended to potentially be used as a fast screening method to supplement the timeconsuming mouse bioassay. Easy implementation of this method can be expected for in-field application because handheld fluorimeters are commercially available and simple to use. In some cases, the presence of BoNT can be detected by eye (see Figure 1) without any instrumentation at all. Because the detection depends on the enzymatic activity of BoNT, this method could greatly reduce interference from inactive toxin, as in the case of toxin that may be denatured during food processing. This method will be more suitable for food sample tests than antibody-based methods, which are more likely to report false positive results and depend on continued access to expensive and potentially unreliable sources of antibodies.


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The sensor performance was demonstrated using BoNT light chains, which are the catalytic domains of BoNTs. Both LcA and LcB could be detected within 3 h, with a LOD and sensitivity comparable to or better than other recently reported activity-based assays.28-29 The serotype A biosensor’s LOD (0.2 ng/mL) is approximately one order of magnitude higher than the extremely high sensitivity of the serotype A mouse bioassay (0.02 ng/mL), and the serotype B biosensor’s current LOD is approximately the same as that of the serotype B mouse bioassay (2 ng/mL).12 Given the room for potential refinement of the analysis parameters (e.g., improvement of PL signal to noise ratio) or modification of the biorecognition peptide sequence (to tune the FRET, cleavage, or QD binding efficiencies), there are obvious routes by which the sensitivity of this FRET-based sensor for both serotypes could be improved to make it a favorable rapid screening method for food samples. Although in a functional BoNT detection assay, a “present/not present” response at a practical LOD threshold is more important than being able to measure toxin concentration, we also note that the measured PL signal of our sensor is concentration-dependent over 2-3 orders of magnitude. This could make our sensor useful for toxin quantitation, something that is difficult to accomplish using the mouse bioassay. It is worth also briefly comparing the performance of our sensor to other recently reported BoNT detection methods. The most apt comparison is a study published in 2011 by Sapsford et al.29 This system also employed peptide-based recognition elements bound to QD FRET donors, but is distinguished from our work by the fact that the acceptor element was a Cy3 organic fluorophore rather than a PL quencher. Organic fluorophores have broad emission profiles due to vibronic structure, which would limit their utility in multiplexing assays for serotyping. Moreover, although the acceptor emission maximum of the Cy3 dye is red-shifted by ~ 25 nm from the QD donor emission maximum, spectral deconvolution of the acceptor and residual donor emission signatures was still required to quantify changes in the QD donor emission in the presence of BoNT. This process may be increasingly inaccurate as the BoNT concentration diminishes, because the tailing region of the relatively strong accepter


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emission interferes with the weak residual donor emission. This is contrasted with the quencher-based design employed by our study, in which the only signal contributing to the measure PL spectrum originates from the QD donor. As a result, our improvement on the basic conceptual design put forward by Sapsford et al contributes to a roughly two order of magnitude improvement in sensitivity (4 pM vs. 350 pM), which brings our sensor much closer to the mouse bioassay reference point. Even in the event that FRET-based or other optimized activity assays cannot surpass the current gold standard mouse technique in terms of sensitivity, they may nevertheless find a valuable place in the repertoire of food protection agencies as convenient alternatives for serotyping analysis of samples that are identified as BoNT positive by more sensitive tests. We note that other published FRET-based methods have focused exclusively on the A serotype, which is not the only serotype that has relevance to food safety.6 We have shown that our method was able to differentiate and independently calculate the concentrations of two Lc serotypes (A and B, which are implicated in most food outbreaks) in a matter of a few hours using a single PL spectrum without any separation or concentration steps. Moreover, the sensor was demonstrated to function for BoNT holotoxin detection as well, which is often neglected in proof-of-concept reports of new BoNT sensing methods. Aside from continuing to lower the detection threshold via methods described above, future directions will be to evaluate and optimize BoNT detection and serotype discrimination in food samples and the expansion to other BoNT serotypes or even other proteinase toxins.

ASSOCIATED CONTENT Supporting Information. Additional description of peptide synthesis methods, optimization of sensor design, and figures illustrating the spectral overlap between quenchers and QDs and mass spectra of intact BHQ1-pepA and BHQ1-pepA N-terminal cleavage products.


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AUTHOR INFORMATION Corresponding Author * E-mail: [email protected]

Funding Sources Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT The authors thank Dr. Igor Medintz at Naval Research Laboratory for providing peptides and helpful discussion. The authors thank Dr. Reddy Rukma and Dr. Gregory J. Fleischman for helping with experiments. The authors also thank Dr. Rebecca G. Weiner and Dr. Joelle K. Salazar for their helpful comments on the manuscript. YW was supported by the Oak Ridge Institute for Science and Education Research Participation Program to the U. S. Food and Drug Administration. This work was performed, in part, at the Center for Nanoscale Materials, a U.S. Department of Energy Office of Science User Facility under Contract No. DE-AC02-06CH11357. The sponsors had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Detection and Quantification of Biologically Active Botulinum

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