Dual-Recognition Förster Resonance Energy Transfer Based Platform

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A Dual Recognition FRET-based Platform for One-Step Sensitive Detection of Pathogenic Bacteria using Fluorescent Vancomycin-Gold Nanoclusters and Aptamer-Gold Nanoparticles Mengqun Yu, Hong Wang, Fei Fu, Linyao Li, Jing Li, Gan Li, Yang Song, Mark T. Swihart, and Erqun Song Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b04958 • Publication Date (Web): 13 Mar 2017 Downloaded from http://pubs.acs.org on March 14, 2017

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A Dual Recognition FRET-based Platform for One-Step Sensitive Detection of Pathogenic Bacteria using Fluorescent Vancomycin-Gold Nanoclusters and Aptamer-Gold Nanoparticles

Mengqun Yu,† Hong Wang, † Fei Fu,† Linyao Li,† Jing Li,† Gan Li,† Yang Song,† Mark T. Swihart,‡ Erqun Song†,*



Key Laboratory of Luminescence and Real-Time Analytical Chemistry, Ministry of Education,

College of Pharmaceutical Sciences, Southwest University, Chongqing, 400715, People’s

Republic of China. Fax: +862368251225; Tel: +862368251225. E-mail: [email protected]

Department of Chemical and Biological Engineering, University at Buffalo, State University of

New York, Buffalo, NY 14260, USA.

ABSTRACT The effective monitoring, identification, and quantification of pathogenic bacteria is essential for addressing serious public health issues. In this study, we present a universal and facile one-step strategy for sensitive and selective detection of pathogenic bacteria using a dual molecular affinity-based Förster (fluorescence) resonance energy transfer (FRET) platform based on the recognition of bacterial cell walls by antibiotic and aptamer molecules, respectively. As a proof of concept,

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Vancomycin (Van), and a nucleic acid aptamer were employed in a model dual recognition scheme for detecting Staphylococcus aureus (S. aureus). Within 30 minutes, by using Van-functionalized gold nanoclusters and aptamer-modified gold nanoparticles as the energy donor and acceptor respectively, the FRET signal shows a linear variation with the concentration of S. aureus in the range of 20 to 108 cfu/mL with a detection limit of 10 cfu/mL. Other non-target bacteria showed negative results, demonstrating the good specificity of the approach. When employed to assay S. aureus in real samples, the dual recognition FRET strategy showed recoveries from 99.00% to the 109.75% with relative standard derivations (RSDs) less than 4%. This establishes a universal detection platform for sensitive, specific, and simple pathogenic bacteria detection, which could have great impact in the fields of food/public safety monitoring and infectious disease diagnosis.

Key words: bacteria, dual recognition, FRET, gold nanoparticle, gold nanocluster



INTRODUCTION Pathogenic bacteria cause serious public health issues including food poisoning and

infectious diseases, and can be used in biological weapons.1-2 Effective detection technology for pathogenic bacteria is vital to address these public health and security

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concerns. Therefore, the development of a sensitive, rapid, convenient, and low-cost method for specific detection of pathogenic bacteria is of great significance. Classic methods of detecting pathogenic bacteria, such as microorganism culture and polymerase chain reaction3-4, are limited by the disadvantages of complicated operation or sample preparation, long analysis times, and low sensitivity and specificity. More recent methodologies for detecting pathogenic bacteria are based on various recognition molecules (e.g. antibodies5-7, aptamers8-16, antibiotics17-20, lectins21-23, phages24-25, etc.) combined with signal transduction through fluorescence6, 9-11

, resonance light scattering (RLS)8, electrochemical measurement16, 22, and surface

enhanced Raman scattering (SERS)14-15. Among the possible recognition strategies, antibody-based methods are simple and high selective but rely on antibodies produced in animals, which can be expensive and subject to poor reproducibility. The antibioticand lectin-based methods are simpler and much less expensive than antibody-based methods. However, their specificity is often unsatisfactory. Aptamer-based strategies can potentially provide simplicity and low cost in combination with acceptable selectivity, and have thus been of great recent interest.26-29 Förster (or fluorescence) resonance energy transfer (FRET) is a homogeneous signal transduction technique that is simple and rapid, sensitive and selective.30-32In this method, energy transfer from an energy donor to an energy acceptor occurs when

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a molecular regognition event brings the donor and acceptor into close proximity. This energy transfer produces a characteristic change in the fluorescence of the donor and/or acceptor. FRET has previously been employed for the determination of pathogenic bacteria using a combination of recognition molecules and nanomaterials.9, 13

For example, Zuo and coworkers employed an organic dye-labelled aptamer as both

recognition molecule and energy donor with graphene oxide as energy acceptor to achieve one-step, fast and multiplexed pathogen detection in a microfluidic system.9 A similar approach to detection of bacteria using FRET was reported by Duan et al. 13 In that study, the organic dye and graphene oxide was replaced by quantum dots(QDs) and carbon nanoparticles to achieve high quenching efficiency.13 Although the aforementioned strategies show promise, the fluorescent dye is subjected to photobleaching while QDs containing heavy metal cadmium ions raise toxicity and environmental concerns. Moreover, the detection strategies in these studies still involved complicated system or procedures. Gold nanoparticles (AuNPs), which are easily synthesized, showed good optical and colloidal stability and high extinction coefficient. These features make them an excellent choice as energy acceptor.33-36 Gold nanoclusters (AuNCs) with small size, good biocompatibility and strong photobleaching-resistant photoluminescence, as well as easy synthesis, have great potential as an energy donor.37-42 Based on the

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broad-spectrum and specific recognition capabilities of antibiotic and aptamer molecules, we have previously demonstrated specific and sensitive quantification of bacteria through a dual-recognition strategy combining antibiotic and aptamer recognition moieties.43 However, the detection strategy in that study involved several steps (incubation, magnetic enrichment, elution and fluorescent detection). Here, building on that work, we demonstrate a novel antibiotic and aptamer dual molecular affinity-based FRET strategy for facile and sensitive detection pathogenic bacteria in a single step. To demonstrate the feasibility of this strategy, a proof-of-concept method for gram-positive(G+) bacterium of Staphylococcus aureus (S. aureus) assay was designed, in which vancomycin-functionalized AuNCs (Van-AuNCs) and aptamer-modified AuNPs (aptamer-AuNPs) were employed as energy donor and acceptor respectively (Scheme 1). Based on this strategy, S. aureus could be detected within 30min with good linear range, detection limit and reliability for authentic samples. The Van-AuNCs and aptamer-AuNPs dual recognition units based FRET strategy (DRU-FRET) can serve as a universal detection platform for sensitive, specific, rapid, simple, and cost-efficient testing for pathogenic bacteria, which in turn could have great impact in the fields of public safety, public health and infectious disease diagnosis.

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EXPERIMENTAL SECTION Materials and Apparatus. Vancomycin Hydrochloride (Van) were purchased

from Amresco LLC.; chloroauric acid (HAuCl4) was provided by Sinopharm Chemical Reagent Co. Ltd; tris(2-carboxyethyl)phosphine (TCEP) was purchased from Pierce Chemical (Rockford, IL,U.S.A).Staphylococcus aureus (S. aureus, ATCC 29213), were obtained from China General Microbiological Culture Collection Center. Bacillus subtilis (B. subtilis, CCTCCAB 90008), Sarcina lutea (S. lutea, CCTCC AB 91100), Escherichia coli (E. coli, CCTCC AB 212355), Salmonella typhimurium (S. typh, CCTCC AB 91105), and Pseudomonas aeruginosa (P. aerug, CCTCC AB 93078) were obtained from China Center for Type Culture Collection. The S. aureus aptamer and random DNA sequence (sequence information showed in Table S1 in supporting

information)

were

synthesized

by

Sangon

Biological

Science

&Technology Company (Shanghai, China). Human serum was supplied by Department of Oncology, the Ninth People's Hospital of Chongqing (China). The ultrapure water used in the experiments was prepared using a Milli-Q system (Merck Millipore, U.S.A.) and had a resistivity of 18.2 MΩ cm. UV-Vis

absorption

spectra

were

recorded

on

a

Shimadzu

UV-2450

spectrophotometer. Fluorescence spectra were obtained using a fluorescence spectrophotometer (F-7000, Hitachi) and fluorescence images were recorded using an

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inverted fluorescence microscope (Olympus IX71) or a confocal laser scanning microscopy (IX2-DSU, Olympus, Japan). The Zeta potential was measured using a Malvern Zetasizer Nano ZS ZEN3600 instrument (Malvern Instruments, United Kingdom). Morphology was characterized using a transmission electron microscope (TEM) (LIBRA 200PE, Carl Zeiss SMT). Bacteria Culture and Counting. Bacteria were grown in Luria-Bertani broth medium at 37 ºC with continuous shaking overnight and then washed with PBS by centrifugation (3500 rpm/5 min). According to the conventional agar plate-counting method, after incubation at 37 ºC for 18 h, the colonies on the plates were counted to determine the number of colony-forming units per milliliter (cfu/mL), yielding the concentration of ~109 cfu/mL. Detection of S. aureus using the DRU-FRET Strategy. Firstly, Van-AuNCs (0.2 mg/mL) were mixed with aptamer-AuNPs (2.5 nM). Then S. aureus with different amounts (0, 10, 20, 30, 102, 103, 104, 105, 106, 107, 5×107, and 108 cfu/mL, respectively) was added into the above solution and incubated at 37 ºC for 30 min in binding buffer. The fluorescence intensity of the final mixture was measured directly by fluorescence spectrophotometer at λex/em=303/412 nm. The same procedures were employed with a random DNA sequence (RanSeq) and with non-target bacteria (such as B. subtilis, S. lutea, E. coli, S. typh, and P. aerug) were supplied in the control

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groups. Detection of S. aureus from Confounding Bacteria Mixed Samples. Varying concentrations of S. aureus were mixed with B. subtilis, S. lutea, E.coli, S.typh and P. aerug (each at 1×108 cfu/mL) to construct an artificial complex specimen. The mixtures were then subjected to the assay as described above. Detection of S. aureus in Real Samples. The qualified milk and orange juice samples were purchased from local supermarket. Human serum was obtained from healthy volunteers. S. aureus was added at known concentration to the ten-fold diluted milk, and five-fold diluted orange juice and human serum to evaluate the applicability of the proposed strategy to real samples.



RESULTS AND DISCUSSION Principle of Van-AuNC and Aptamer-AuNP based DRU-FRET Strategy

for Detecting S. aureus. The Van-AuNC and aptamer-AuNP based DRU-FRET strategy for S. aureus is illustrated in Scheme 1. The approach was designed based on the following features. Firstly, the Van and aptamer molecules exhibit broad-spectrum and highly specific binding respectively on the surface of S. aureus (Figure S2). This provides an opportunity to construct FRET platform on the surface of bacteria. Secondly, the Van-AuNCs show bright blue fluorescence while maintaining their

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antibiotic activity for S. aureus (Figure S2). Thirdly, the emission spectrum of VanAuNCs shows spectral overlap with the absorbance spectrum of aptamer-AuNPs (Figure 1), suggesting that the aptamer-AuNPs can serve as an energy acceptor for Van-AuNCs.

Scheme1 Illustration of the vancomycin and aptamer dual recognition molecule based FRET assay platform for S. aureus.

Figure1 Typical emission spectrum of Van-AuNCs and the absorbance spectrum of aptamer-AuNPs. The inset shows a photograph of Van-AuNCs under 365 nm light illumination.

After the Van-AuNCs and aptamer-AuNPs were prepared and characterized

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respectively (Figure S1 and S3), they were mixed with the target S. aureus and then subjected to fluorescence measurement (shown in Figure 2). As shown in Figure 2A, compared with the blank sample (mixture of Van-AuNCs with aptamer-AuNPs dispersed in buffer), the fluorescence intensity of the mixture with S. aureus showed a modest decrease in intensity with fluorescence quenching efficiency about 12% (the fluorescence quenching efficiency of η was calculated by the equation: η=(F0-F)/F0 ×100%, F0 and F are the fluorescence intensities of the detection system in the absence and presence of S. aureus or other bacteria). However, when the aptamer was replaced with a random DNA sequence (RanSeq) or when S. aureus was replaced with non-target bacteria of E. coli (gram-negative bacterium, G-) and S. lutea (G+), nearly a slight fluorescence intensity decrease was observed, with corresponding η value of 3.08%, 1.14% and 2.81% respectively. The fluorescence intensity changes △F (△F=F0-F) for all the bacteria samples compared with the blank (without bacteria) were summarized with a bar graph for more clear understanding (the inset in Figure 2A). And the fluorescence quenching phenomenon for the target S. aureus was visually observed under a fluorescence microscope. As shown in Figure 2B, the fluorescence image (d) shows subdued blue fluorescence dots (pointed out by red circles for easy view) around site the S. aureus located (c) when they were treated with Van-AuNCs/aptamer-AuNPs mixture together. On the contrary, we could see

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bright blue fluorescence dots (b, f) on the same sites of where the S. aureus located (a, e) when they were incubated with Van-AuNCs (a, b) only or mixture of Van-AuNCs and RanSeq-AuNPs (e, f).

Figure 2 (A) The fluorescence spectra of the Van-AuNCs before and after mixing with aptamer-AuNPs, bacteria, or both of them. The inset is a bar graph of fluorescence intensity changes △F for different samples in Figure 2A. (B) Fluorescence microscope images of S. aureus after incubation with Van-AuNCs only (a, b), with the mixture of Van-AuNCs and aptamer-AuNPs (c, d), and with the mixture of VanAuNCs and RanSeq-AuNPs (e, f) simultaneously. The blue fluorescence dots in the fluorescence image were pointed out by red circles.

Optimization of Detection Conditions. To obtain the best sensing performance, the dosages of Van-AuNCs and aptamer-AuNPs, and the incubation time were optimized using the fluorescence intensity as the evaluating index through the orthogonal experiment method employing the L9(33) orthogonal layout. 44-46 Each of three major factors (dosages of Van-AuNCs and aptamer-AuNPs, and the

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incubation time) was studied at three levels (shown in Table S2). The orthogonal experiment program, results, and analysis are shown in detail in Supporting Information (Tables S3-S4). As shown in Table S4, the fluorescence intensity change of △F (△F=F0-F, where F0 and F are the fluorescence intensities in the absence and presence of S. aureus with concentration at 108 cfu/mL) reached a maximum when the dosages of Van-AuNCs and aptamer-AuNPs were 0.2 mg/mL and 5 nM respectively. Using these optimal dosages, the fluorescence intensity change of the system reached equilibrium after 30min.

Quantitative Detection of S. aureus based on DRU-FRET Strategy. After the assay conditions were optimized, the linear range and detection limit of S. aureus by the DRU-FRET strategy were studied. Specifically, a series of S. aureus solutions of different concentrations (0, 10, 20, 30, 102, 103, 104, 105, 106, 107, 5×107, and 108 cfu/mL, respectively) were incubated with Van-AuNCs and aptamer-AuNPs simultaneously for 30 min, followed by the determination of the fluorescence intensity of each sample. As shown in Figure 3, the decrease in fluorescence intensity (△F) of the mixture with S. aureus was linear dependent upon the logarithm of the concentration of S. aureus from 20 to 108 cfu/mL with a detection limit of 10 cfu/mL (∆F=109.92log10 N-96.09, R=0.9866, where N stands for the quantity of S. aureus in cfu/mL; LOD was determined by the equation LOD = 3S/K, where S was the standard 12

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deviation of the blank samples (n=10) and K is the slope of the calibration curve).

Figure 3 (A) Fluorescence spectra of the DRU-FRET biosensor in the presence of S. aureus at varying concentrations (curves a to l correspond to 0, 10, 20, 30, 102, 103, 104, 105, 106, 107, 5×107, and 108 cfu/mL, respectively). (B) The calibration curve obtained from the spectra of (A) showing the linear dependence of change in fluorescence intensity on the logarithm of S. aureus concentration (log10N cfu/mL).

Selectivity of the DRU-FRET Strategy for S. aureus. In the environment, S. aureus may be usually accompanied with other bacteria, including both G+ and Gbacteria, therefore the selectivity of the DRU-FRET strategy for S. aureus should be confirmed. The selectivity of the DRU-FRET strategy for S. aureus was tested by comparing the fluorescence intensity change of the detecting system to the S. aureus and other interfering bacteria. Each of the five interfering bacteria (B. subtilis(G+), S. lutea (G+), E. coli (G-), S. typh (G-), and P. aerug (G-) all at 1.0×108cfu/mL), a mixture1 of the five interfering bacteria together, and another mixture 2 (containing S. aureus and five interfering bacteria all at 1.0×108cfu/mL) were assayed with the proposed method respectively, and all the obtained fluorescence signals were compared with that from blank sample (only PBS buffer without any bacteria). As 13

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shown in Figure 4, compared with the S. aureus and blank sample, the fluorescence responses from the interfering bacteria were less than 8% of that from the former and no more than 4 times of that from the latter. Specifically, the degree of interference (DI) of these interfering bacteria to the target S. aureus was evaluated according to the following equation: DI=(FRI-FRB)/ (FRS-FRB) ×100%

(1)

where FRI, FRS and FRB are the fluorescence responses from the interfering bacteria, S. aureus, and the blank sample, respectively. The DI values of B. subtilis, S. lutea, E. coli, S. typh, P. aerug and mixture1 were calculated to be 4.11 %, 6.35%, 2.49%, 3.77%, 3.00%, and 6.95%, respectively, implying negligible interference of these bacteria. The fluorescence response of mixture2 only showed a small change of 1.43% in comparison with that of S. aureus sample. The above results revealed satisfactory selectivity of the proposed DRU-FRET strategy for S. aureus detection.

Figure 4 Fluorescence response (∆F) for blank buffer, S. aureus, interfering bacteria, and the mixtures of them respectively. The concentration of S. aureus is 105cfu/mL, and five interfering bacteria are all at 108cfu/mL.

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Detection of S. aureus in Authentic Samples. In order to demonstrate the applicability of DRU-FRET strategy for S. aureus detection in real samples, several test samples (qualified milk and orange juice samples, and the human serum from healthy volunteers) spiked with S. aureus were analyzed. Before assay, the interference (that means the background signals produced by the pure real sample without spiking any S. aureus) of the real sample to the proposed DRU-FRET strategy was studied. As shown in Figure S4, the milk sample with ten-fold dilution and another two sample (juice and serum) with five-fold dilution produced comparable background signals with the blank sample (PBS buffer). Then the diluted real samples spiked with S. aureus were subjected to assay with DRU-FRET strategy. The results in Table 1 showed that the recoveries varied from 99.00% to 109.75% with variation coefficients of 0.98-3.07%, indicating that the proposed method could be applied for detection of S. aureus in authentic samples. The limit of detections in the diluted milk, Table 1 Recovery efficiency of S. aureus detected in real samples based on the proposed DRU-FRET strategy Samples milk 1 milk 2 milk 3 orange juice 1 orange juice 2 orange juice 3 human serum1 human serum2 human serum3

Added (log10N cfu mL-1) 2 4 6 2 4 6 2 4 6

Measured (log10N cfu mL-1)

Recovery (%)

RSD (%, n =3)

2.01 4.39 6.35 1.98 4.07 6.06 1.98 4.01 5.98

100.50 109.75 105.83 99.00 101.75 101.00 99 .00 100.25 99.67

2.46 0.98 2.08 3.33 1.71 3.07 2.89 1.17 1.35

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orange juice and human serum sample for S. aureus are 300 cfu/mL, 100 cfu/mL, and 100 cfu/mL respectively. Although the pre-dilution of real sample is required for S. aureus assay, fortunately the dilution operation is very simple and fast, which will not badly affect the efficiency of the whole DRU-FRET strategy based assay. A brief comparison of various surface bio-affinity sensing methods for detecting of S. aureus was summarized in Table S5. Compared with other bio-affinity sensing methods reported, the as-proposed strategy in this study is preferable for S. aureus assay due to its high sensitivity, wide analytical range (covering several orders of magnitude), simpleness (one-step assay with ordinary instrument), and rapidness (30min). Compared with our previously published work43, the DRU-FRET strategy for S. aureus proposed in this study is much simple and faster, and it shows better detection ability with lower LOD of 10 cfu/mL for S. aureus in blank buffer. As for its disadvantage, due to lacking of pre-separation for the target bacteria from other interfering components in real sample before fluorescence measurement as done in our previous work43, the DRU-FRET strategy here showed some interference background signals for original real sample (as shown in Figure S4), resulting a predilution step to the real sample. Another point is that the emission peak of donor (VanAuNCs) did not fully overlap with the absorbance peak of acceptor (aptamer-AuNPs) (Figure 1), resulting relative lower fluorescent quenching efficiency (ηmax