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Black phosphorus-Au filter paper-based three-dimensional SERS substrate for rapid detection of foodborne bacteria
Applied Surface Science 497 (2019) 143825
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Black phosphorus-Au filter paper-based three-dimensional SERS substrate for rapid detection of foodborne bacteria
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Deqiu Huanga,1, Zhengfei Zhuanga,1, Zhen Wanga, Shengtao Lia, Huiqing Zhonga, Zhiming Liua, , ⁎ ⁎⁎ Zhouyi Guoa, , Wen Zhangb,c, a MOE Key Laboratory of Laser Life Science & SATCM Third Grade Laboratory of Chinese Medicine and Photonics Technology, College of Biophotonics, South China Normal University, Guangzhou 510631, Guangdong, China b Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, China c Hunan Key Laboratory of Biomedical Nanomaterials and Devices, College of Life Sciences and Chemistry, Hunan University of Technology, Zhuzhou 412007, Hunan, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Surface-enhanced Raman scattering BP-Au nanoparticles Foodborne bacteria detection Filter paper-based SERS substrate
Rapid and accurate detection of foodborne bacteria is believed to be of vital importance in assuring food safety. In this work, we explored a novel label-free three-dimensional surface-enhanced Raman scattering (3D-SERS) substrate based on black phosphorus-Au (BP-Au) filter paper for the detection and discrimination of three common foodborne bacteria including Staphylococcus aureus, Listeria monocytogenes and Escherichia coli without complicated sample processing. It was found that the BP-Au filter paper-based 3D-SERS substrate could offer larger surface area as well as more “hotspots” than 2D-SERS substrate for sample detection. Moreover, our results showed that this 3D substrate could efficiently enhance Raman signals from model molecules and exhibit satisfactory SERS activity allowing for specific recognition and discrimination of three types of target bacteria at a concentration of 107 CFU/mL. Subsequently, SERS spectral data from three bacteria were successfully distinguished by principle component analysis (PCA) and linear discriminant analysis (LDA). These results demonstrated that the novel 3D SERS substrate with facile, low-cost, green fabrication process as well as high sensitivity could serve as an excellent alternative to conventional substrates for rapid label-free detection and identification of foodborne bacteria with the aid of statistical discriminant analysis PCA-LDA in food safety application.
1. Introduction Foodborne diseases caused by foodborne pathogens bacteria such as Staphylococcus aureus, Salmonella enterica, Escherichia coli, Campylobacter jejuni and Listeria monocytogenes may result in severe illness in humans [1]. Rapid detection and discrimination of foodborne bacteria is becoming increasingly important in assuring food safety [2,3]. Current methods for bacteria detection mainly include conventional culture identification strategies [4], immunoassay techniques [5,6], polymerase chain reaction (PCR) [7–10]. The traditional culturing method is regarded as the gold standard, but it is time consuming and labor intensive. Immunoassay strategies can simplify the procedure of bacteria identification with the properties of rapid and sensitive,
however, this method has complicated procedures and low selectivity. PCR-based testing can detect specific bacteria DNA timely and simply; nevertheless, it suffers from the limitation of background interference [11]. For these reasons, it is necessary to explore a more rapid and sensitive methods for accurate bacteria identification. Raman spectroscopy (RS) shows great potential in identifying substances according to their vibrational fingerprint [11–14]. However, low intensity of conventional RS and fluorescence interference generated by some molecules make it difficult to detect biological samples with complex composition and strong spontaneous fluorescence. As the Raman signal of target analyte can be greatly enhanced compared with conventional RS when the sample is close to or adsorbed on the rough surface of noble metals such as Au and Ag, surface enhanced Raman
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Corresponding authors. Correspondence to: W. Zhang, Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, China. E-mail addresses: [email protected] (Z. Liu), [email protected] (Z. Guo), [email protected] (W. Zhang). 1 These authors contributed equally to this work. ⁎⁎
https://doi.org/10.1016/j.apsusc.2019.143825 Received 22 May 2019; Received in revised form 18 July 2019; Accepted 28 August 2019 Available online 28 August 2019 0169-4332/ © 2019 Elsevier B.V. All rights reserved.
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2. Materials and methods
spectroscopy (SERS) has emerged as a more sensitive analytical technique in biological detection with advantages of simple pretreatment, simple operation, short detection time and high sensitivity. Using SERS technique, high-quality of Raman signals can be obtained with low excitation power which may prevent damage to biological samples. Moreover, SERS can reduce the spontaneous fluorescence background of biological samples [15]. Hence, SERS has shown great promise in biological field. In recent years, SERS has also played an important role in the detection of microorganisms [16,17]. Drikell et al. used SERS labeled immunoassay to detect viruses at low concentrations [18]. Martin Kögler et al. synthesized Au nanoparticles-based SERS substrate and successfully applied it to the discrimination of E. coli and Listeria monocytogenes [19]. Although SERS was reported to have the ability of discriminating bacteria using noble metal (Au, Ag, etc.) as SERS substrate, its practical application is still challenging, such as poor reproducibility of Raman signal, low bacteria concentration and background interference in the sample [20–24]. Therefore, it is necessary to explore novel label-free SERS substrates with the characteristics of simple preparation, highly stable and low cost to get more enhanced and reproducible SERS signals for bacteria detection. Two mechanisms may attribute to SERS effect; chemical mechanism (CM) based on the charge transfer between substrate and analytes, and electromagnetic mechanism (EM) which depends on the plasmonic nanostructures [25]. Black phosphorus (BP), as the emerging inorganic two-dimensional nanomaterial potential with high biocompatibility and a layer-dependent direct bandgap varying from 0.3 eV for the bulk to 2.0 eV for a single layer has been becoming one of the most perspective materials of great potentials in biomedicine, electronics and optoelectronics [26]. In our previous study, BP-Au nanosheets was applied for SERS bioanalysis [27,28]. The decoration of Au nanoparticles onto BP nanosheets enabled the integration of CM from BP nanosheets and EM from Au nanoparticles, resulting in significant enhanced and highly reproducible detection of chemical molecules than bare Au nanoparticles or BP nanosheets, demonstrating its great potential in bio-application. Compared with conventional substrates, three-dimensional (3D) SERS substrates not only possess larger surface area, which is favor of adsorbing more probe molecules, but also can provide more “hotspots” and binding sites for analytes when the substrate is modified by noble metal nanoparticles [29–32]. Inspired by this idea, numerous efforts have been taken to synthesis 3D SERS platforms. Yang et al. prepared a novel 3D mesoporous ZnO/Ag SERS substrate with high sensitivity and reproductivity for the detection of dye, and the 3D substrate showed good SERS activity [33]. In addition, similar 3D SERS substrate based on Au/TiO2, Ag/ZnO, Au/graphene and Ag/graphene has been developed for biomedical detection [33–36]. Nevertheless, the preparation procedure of these substrates is time-consuming and complex, thus limited their use in rapid SERS assay. Natural filter paper is considered to be an ideal solid substrate ascribing to their low-cost, easy to obtain, biodegradable, recyclable, and natural 3D porous structure. Filter paper can attach nanoparticles in many ways such as in situ synthesis, indirect deposition, silver mirror reaction, ink jet printing, water immersion method, etc. [37,38]. These filter paper-based SERS substrates could create more “hot spots” to achieve stronger enhancement effect as well as maintain good signal reproducibility. Based on the above background, we prepared a novel label-free BPAu filter paper-based 3D-SERS substrate by simply absorption of the in situ fabricated BP-Au nanosheets onto natural filter paper with several immersion-rinsing-drying cycles. SERS performance of the prepared 3D SERS substrate was evaluated. Furthermore, the synthesized BP-Au filter paper-based 3D SERS substrate was used for the detection and discrimination of three common foodborne bacteria including Staphylococcus aureus, Listeria monocytogenes and Escherichia coli.
2.1. Materials Whatman qualitative filter paper was purchased from Dalian Meilun Biotechnology Co., LTD. Crystal violet (CV), Malachite green (MG) and Ponceau S (PS) were purchased from Sigma-Aldrich. Bulk BP crystals were obtained from XFNANO Materials Tech Co. Ltd. (Nanjing, China) and stored in a dark Ar-filled glovebox. N-Methyl-2-pyrrolidone (NMP), sodium citrate and chloroauric acid (HAuCl4·4H2O) were obtained from China National Medicine Corporation (Shanghai, China). Ultrapure water (18.2 MΩ, Milli-Q System, Millipore, USA) was used in all experiments. 2.2. Preparation of BP-Au filter paper-based SERS substrate 2.2.1. Synthesis of BP nanosheets Probe sonication in combination with bath sonication was applied to prepare BP nanosheets via liquid exfoliation method according to our previous study [28]. Briefly, 30 mg of the bulk BP powders were dispersed in 30 mL of NMP and sonicated with an ultrasonic probe (600 W, 2 s duration and 4 s interval) for 6 h on ice. Then, the mixture was bath sonicated overnight in an ice bath at a power of 300 W. The dispersion was centrifuged for 10 min at 2000 rpm to remove unexfoliated BP. Subsequently, BP nanosheets was collected by centrifuged at 7000 rpm for 20 min and re-suspended in NMP. 2.2.2. In situ synthesis of BP-Au BP-Au nanosheets were synthesized by a facile reflux method. Briefly, 300 μL of HAuCl4 (10 mM) were dispersed in 20 mL boiling water, Afterward, 150 μL of as-prepared BP nanosheet at the concentration of 5 mg/mL in NMP was added under constant stirring for 2 min until the color of the solution was changed from yellow-brown to purple red. Finally, the product was centrifugated at 7000 rpm for 10 min to remove bare Au nanoparticles and dispersed in water. 2.2.3. Synthesis of Au filter paper and BP-Au filter paper-based SERS substrate The BP-Au filter paper-based 3D SERS substrate was prepared simply by immersing filter paper in a petri dish containing 5 mL BP-Au particles for 24 h. Then the filter paper was rinsing thoroughly with distilled water to remove loosely bound BP-Au nanoparticles, and dried at room temperature overnight. After several cycles of immersion-rinsing-drying procedure, the BP-Au filter paper-based 3D SERS substrate was obtained for further detection. The whole preparation process is shown in Scheme 1. Au filter paper-based SERS substrate was synthesized under the same process except for the incubating nanoparticles being replaced by Au nanoparticles. 2.3. Characterization The morphology and energy dispersive X-ray (EDX) spectrum of BP nanosheets and BP-Au nanosheets were characterized by a 120 kV transmission electron microscope (TEM, JEOL, JEM-2100HR, Japan) equipped with an EDX spectrometer. The morphology of SERS substrates was observed by Scanning electron microscope (SEM, ZEISS Gemini 500), equipped with an energy-dispersive X-ray (EDX) spectrum. X-ray photoelectron spectroscopy (XPS) spectra of BP-Au NSs and BP-Au NSs mixed with CV (BP-Au/CV) were recorded on ESCALAB250Xi (Thermal Fisher Scientific). The ultraviolet visible nearinfrared (UV–Vis-NIR) spectra of the materials were conducted on an UV-VIS-NIR spectrometer (UV-3200S, MAPADA, China). Raman spectra were collected using Renishaw inVia microspectrometer (Renishaw, UK) under a 514.5 nm diode laser excitation. The UV-VIS spectrometer of 3D SERS substrates were accorded on an optical fiber spectrometer. 2
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Scheme 1. Schematic of the fabrication of BP-Au filter paper-based SERS substrates and its application in detection of analytes and three foodborne bacteria.
USA). The baseline correction was performed to analyze the data. In this study, principal component analysis (PCA) and linear discriminative analysis (LDA) were used for the identification and discrimination of three types of bacteria.
2.4. SERS experiments For investigating the SERS effect of 3D SERS substrates, crystal violet (CV), Malachite green (MG) and Ponceau S (PS) were chosen as probe samples. Firstly, with filter paper used as blank control, Au filter paper-based and BP-Au filter paper-based 3D substrates served as control group and experimental group, the enhancement effect of SERS substrates to CV, MG and PS at different concentrations was studied. Second, different ratio of HAuCl4 and BP in 3D SERS substrates were synthesized and 3D substrate with the best SERS effect was selected for the following experiments. All experiments were independently conducted three times. All the dye molecules were dropped onto the 3D SERS substrates and were then detected using a Renishaw inVia Raman microspectroscopy. The spectral coverage was from 700 to 1700 cm−1 with a 514.5 nm laser excitation. The laser power was 25 mW with a scan time of 10 s. Bacteria samples such as Escherichia coli, Staphylococcus aureus and Listeria monocytogenes with the concentration of 107 CFU/mL were dropped onto 3D substrates and their SERS spectra between 620 and 1720 cm−1 were recorded under 785 nm laser excitation. Bacteria samples on bare filter paper-based 3D SERS substrate were also scanned.
3. Results and discussion 3.1. Characterization of BP-Au filter paper-based 3D SERS substrate As shown in Fig. S1, single and few-layered BP nanosheets were successfully obtained via liquid exfoliation in NMP from BP crystal. The average lateral size of BP nanosheets was between 300 nm and 1 μm. After in situ reduction of HAuCl4, BP-Au nanosheets were synthesized, which was evidenced by the massive coated Au nanoparticles with an average size of 30 nm on the surface of BP nanosheets (Fig. S2). These Au nanoparticles could generate abundant “hot spots” between the gap of two neighboring nanostructures, showing great potential to serve as excellent SERS substrates. The EDX image of BP-Au spectrum also confirmed the existence of Au and P in BP-Au nanosheets (Fig.S3). The characteristic absorption peak at 530 nm in UV-VIS spectra of BP-Au NP also suggested the successful attachment of AuNPs in BP NSs. After several immersion-rinsing-drying cycles, BP-Au filter paper-based 3D SERS substrate was synthesized. SEM characterization of the 3D SERS substrate was shown in Fig. 1. It could be seen that the BP-Au nanosheets were distributed in the filter paper, and the elemental mapping of Au, P and O in the selected region matched well with BP-Au nanosheets, demonstrating the successful fabrication of BP-Au filterpaper 3D SERS substrates. As can be seen in Fig. 2, three distinct Raman peaks located at 361 cm−1, 437 cm−1 and 465 cm−1 were revealed from the Raman spectra of BP NSs, which represents one out-of-plane phonon mode (A1g) and two in-plane modes (B2g and A2g), respectively [39]. Compared with BP, BP-Au exhibited a significant red shift in its Raman spectra due to the presence of Au NPs, which further verifying that the BP-Au NPs was successfully prepared. The optical fiber spectrometer characterization of BP-Au filter paper-based 3D SERS substrate was also performed. The characteristic absorption peak at 530 nm and the enhanced absorption in NIR region of BP-Au filter paper indicated that BP-Au was coated onto the surface of filter paper.
2.5. Electromagnetic field distribution simulations Finite-difference time domain (FDTD) simulations were performed by using FDTD Solutions software (Lumerical Solutions Inc.) to analyze the plasmonic nanostructures of Au NPs and BP-Au NSs. The diameter of the AuNPs and the thickness of BP NSs was set according to the average size measured from the experimental results. A total-field scattered-field light source with a wavelength of 785 nm was chosen. Perfectly matched layer (PML) boundary conditions was used to XYZ axis directions around the AuNPs. The mesh size between BP and AuNPs was set as 0.2 nm. 2.6. Data analysis The SERS spectra data analysis were conducted using GraphPad Prism 8.0.1 for Windows (GraphPad Software, San Diego, California, 3
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Fig. 1. Characterization of BP-Au filter paper-based SERS substrate. (a) SEM image of filter paper; (b-d) SEM images with different magnification and (e) EDS image of BP-Au filter paper-based SERS substrate; (f-h) EDS mapping of element O, Au and P in BP-Au filter paper-based SERS substrate, respectively.
1370 cm−1, 1178 cm−1 and 916 cm−1 were attributed to the N-phenyl stretching vibration mode, CeH bending vibration and the skeleton vibration of the ring, respectively. The characteristic peaks at 1539 cm−1, 1588 cm−1 and 1620 cm−1 were assigned to the CeC stretching vibration of the aromatic ring. In comparison with Au filter paper-based substrate, BP-Au filter paper-based substrate displayed obviously enhanced Raman signal, indicating excellent SERS activity of BP-Au filter paper-based 3D SERS substrates. The superior SERS performance of BP-Au filter paper-based 3D substrates can be attributed to the following reasons. Firstly, the dotted BP-Au NPs in the 3D nanostructures of filter paper formed a large number of “hot spots”. “Hot spots” are highly localized regions of greatly enhanced electromagnetic fields caused by localized surface plasmon resonance (LSPR) from the
3.2. SERS activity of BP-Au filter paper-based 3D substrate In order to find the optimal BP-Au filter paper-based 3D substrates for further SERS detection, the SERS enhancement effects on 1 μM CV based on a group of BP-Au filter paper-based 3D substrates prepared by adjusting the ratio of the amount of HAuCl4 to BP NSs were investigated (Fig. 3a–b). The substrate 2 had the superior SERS activity and was used in the following experiments. Subsequently, crystal violet (CV) was used as a Raman probe molecule to explore the SERS performance of BP-Au filter paper-based 3D substrate due to its confirmed and unique Raman peak. As shown in Fig. 3c, Raman signal of CV could be significantly enhanced when BP-Au filter paper-based 3D substrate was served as SERS substrate. The typical characteristic bands located at 4
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Fig. 2. (a) Raman spectra of BP NSs and BP-Au NSs; (b) Absorbance spectra of BP-filter paper, Au NPs-filter paper and BP-Au NPs-filter paper substrate.
BP-Au NPs in filter paper could produce synergistic enhancement effect between EM from Au NPs and additional CM from BP NSs. It is recognized that there are two main mechanisms for SERS enhancement, EM dependent on metal nanoparticles and CM based on charge transfer between substrate and analyte. Generally, these two mechanisms usually coexist in reality, with the EM enhancement playing dominate role. In order to verify the combined SERS enhancement mechanism from BP-Au, FDTD simulation of the electromagnetic field enhancement
noble metals such as Au and silver, and usually occurs in the gaps or sharp tips of plasmonic materials. Once the analytes are very close to “hot spots” of the SERS substrates, a strong SERS enhancement effect will be achieved [40]. In the BP-Au filter paper-based 3D substrates, BPAu NSs has massive Au NPs closely aligned on the BP NSs, which makes “hot spots” be generated without any aggregation process. Secondly, the analytes adsorption ability of the 3D SERS substrates was greatly improved due to its large specific surface area. Thirdly, the scattered
Fig. 3. (a) Raman spectra of bare filter paper and different BP-Au NPs filter paper-based SERS substrate; (b) SERS spectra of 1 μM CV with different BP-Au NPs filter paper SERS substrate; (c) SERS spectra of CV on filter paper, Au NPs filter paper, BP-Au NPs filter paper-based SERS substrate, respectively; (d) SERS spectra of CV with different concentrations on BP-Au NPs filter paper-based SERS substrate. 5
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3.3. Reproducibility and stability of BP-Au filter paper-based SERS substrate
of Au NPs and BP-Au NSs was performed. As shown in Fig. S5a, the results indicated that a strong electromagnetic field was localized between adjacent Au NPs from Au NPs array as well as BP-Au array. Moreover, there was also a greatly enhanced electromagnetic field between Au NPs and BP NSs, which may lead to the enhanced SERS effect of BP-Au compared with Au NPs. On the other hand, chemical states analysis of BP-Au NSs were performed by XPS characterization to elucidate the interaction between the absorbed CV molecules and BP-Au substrate. It can be seen from Fig. S5b and c that BP-Au NSs exhibited characteristic P 2p3/2 (129.8 eV) and P 2p1/2 (130.6 eV) bands, as well as a sub-band (134.59 eV) of phosphorus oxide [41]. However, this phosphorus oxides band shifted to 134.22 eV in the XPS spectra of BPAu/CV, implying moderate charge transfer between absorbed CV and phosphorus oxides from BP-Au. In addition, the Au 4f7/2 and 4f5/2 doublet pair only shifted less than 0.1 eV, which can be considered no charge transfer happened between Au and CV. These results confirmed that the CM enhancement may mainly originate from the interaction between BP NSs and CV. Furthermore, the SERS performance of BP-Au and Au NPs substrates was also explored in Fig. 5Sd and e. It was found that the SERS enhancement effect of BP-Au was more superior than Au NPs, which may be ascribed to the above listed two reasons. In order to analyze the SERS effect of the 3D substrate quantitatively, we calculated its enhancement factor (EF) according to the following formula: EF = (ISERS / CSERS) / (IRaman / CRaman). CSERS, ISERS IRaman and CRaman represent the concentration of SERS probe molecule, the intensity of SERS signals, the intensity of normal RS signals and the concentration of probe molecule used in normal RS assay, respectively. The EF value of 3D BP-Au filter paper-based substrate was calculated to be 2.4 × 104, which is 12 times as high as the Au filter paper-based substrate whose EF value was 2.0 × 103, demonstrating better SERS activity than Au filter paper-based substrate. It also can be seen from Fig. 3d that the SERS signal intensity of CV decreased with the decrease of CV concentration. However, the characteristic peaks of CV could still be identified clearly even when the CV concentration decreased to 1 nM. The SERS effects of 3D substrates on two opposite charged probe dye molecules including a cationic dyes malachite green (MG) and an anionic dye ponceau S (PS) were evaluated. As can be seen from Fig. 4, although both of Au filter paper-based and BP-Au filter paper-based 3D substrate showed significantly SERS effect on two dyes with opposite charges, BP-Au filter paper-based 3D substrate revealed more preferred SERS activity with equivalent amount of Au NPs in two substrates. It is worth noting that the enhancement effect of BP-Au filter paper 3D substrate on negatively charged PS was distinct weaker than that on positively charged MG. This phenomenon could be attributed to the absorption capacity of the negative-charged BP in BP-Au filter paper 3D substrate to positive charged groups in the PS.
In practical application, the stability and reproducibility of the SERS substrate is of vital importance for analytes detection. We dropped exactly the same concentration of CV solution to BP-Au filter paperbased 3D substrates and randomly selected eight points on each substrate for SERS measurement. It can be seen from Fig. 5 that the characteristic peak and intensity of the obtained SERS spectra were similar to each other. To quantitatively evaluate the repeatability of the SERS spectra, we selected three characteristic peak of CV (811 cm−1, 1370 cm−1 and 1620 cm−1) as model reference to calculated their relative standard deviation (RSD) values. The calculated results were 9.4%, 9.1% and 4.2%, respectively, which can be proved that the SERS substrate has high reproducibility. Then, we further explored the stability of BP-Au filter paper-based 3D substrate by SERS experiment. The 3D SERS substrate prepared in the same batch was stored in a refrigerator at 4 °C for 12 days. CV aqueous solution of 1 mM concentration was added to the 3D substrate for SERS assay every 3 days. There results showed no obvious changes among the five measured spectra. Moreover, the intensity of characteristic peak of CV at 1178 cm−1 stored for 12 days was analyzed and the signal intensity displayed a decline of 6.2%, indicating that the BP-Au filter paper-based 3D substrate has reasonable stability (Fig. 6). 3.4. SERS Spectra and classification analysis of foodborne bacteria In order to verify the SERS effect on three types of foodborne bacteria with BP-Au filter paper-based 3D SERS substrate, the Raman spectra of three bacteria with filter paper were recorded firstly. As shown in Fig. 7a, the bacteria on the bare filter paper showed no distinguished Raman signals. After being added onto the BP-Au filter paper-based 3D SERS substrate, the Raman spectra of three bacteria exhibited remarkably enhanced Raman signals (Fig. 7b-d). The average spectra of three foodborne bacteria were distinct and the intensity of the Raman peaks were greatly improved than with filter paper substrate, demonstrating that the above three foodborne bacteria could be detected with BP-Au filter paper served as SERS substrate. To confirm the SERS spectra reproducibility of BP-Au filter paper-based SERS substrate, SERS spectra of Escherichia coli, Staphylococcus aureus and Listeria monocytogenes on BP-Au filter paper-based substrate from five randomly selected points were shown in Fig. 7 and showed good reproducibility. As shown in Fig. 7b–d, the SERS spectra located between 620 cm−1 to 1720 cm−1 of Escherichia coli, Listeria monocytogenes and Staphylococcus aureus showed a little difference between each other. By comparison of SERS spectra of three bacteria, distinctions of their
Fig. 4. (a) SERS spectra of a cationic dyes malachite green (a) and an anionic dye ponceau S (b) at the concentration of 1 mM with filter paper, Au NPs filter paperbased SERS substrate and BP-Au NPs filter paper-based SERS substrate, respectively. 6
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Fig. 5. (a) SERS spectra of CV with BP-Au NPs filter paper-based SERS substrate at randomly selected eight positions; (b–d) SERS intensity distribution of the above eight spectra in the bands of 811 cm−1, 1370 cm−1 and 1620 cm−1 of CV, respectively.
characteristic Raman bands were collected for further bacteria discrimination (Table S1). The SERS spectra characteristic peaks of Escherichia coli with were observed at 690, 790, 850, 920, 1001, 1053, 1097, 1161, 1168, 1220, 1305, 1317, 1382, 1418, 1474, 1543 and 1621 cm−1. The SERS spectra of Staphylococcus aureus displayed characteristic peaks at 668, 727, 785, 859, 919, 999, 1058, 1151, 1319, 1331, 1389, 1482, 1543 and 1621 cm−1. The typical Raman bands of Listeria monocytogenes were mainly located at 678, 735, 791, 859, 921, 996, 1098, 1064, 1138, 1151, 1161, 1228, 1310, 1391, 1476, 1546, 1597 and 1630 cm−1. The Raman fingerprint information can mainly be assigned to proteins, phospholipids, nucleic acids, lipopolysaccharides, carbohydrates, peptidoglycan in the cell structural components of bacteria. Through spectral match, we could acquire special structural information of different bacteria, thus differentiating the bacteria. As shown in Fig. 7b–d, the Raman peaks at 727–735, 860, 1098, 1151 and 1621–1630 cm−1 were similar among three species bacteria spectra, which could be assigned to the components of bacteria cell wall (727–735 cm−1 for peptidoglycan structure of the bacterial cell wall, 860 cm−1 for CeC stretch skeletal protein, 1098 cm−1 for CeC and CeO stretch in carbohydrates, 1151 cm−1 for = C-C = unsaturated fatty acids in lipids and CeN aromatic amino acids in proteins,
Fig. 6. SERS stability of BP-Au NPs filter paper-based SERS substrate within12 days.
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Fig. 7. (a) SERS spectra of three foodborne pathogens including Escherichia coli, Staphylococcus aureus and Listeria monocytogenes on filter paper substrate. SERS spectra of (b) Escherichia coli, (c) Staphylococcus aureus and (d) Listeria monocytogenes on BP-Au filter paper-based substrate from five randomly selected points.
1621–1630 cm-1 for amide II, CeN stretch and NeH bend). The tentative assignment of Raman bands from the SERS spectra of three foodborne bacteria were listed in Table. S1. The intensity of Raman bands at 623, 668, 860, 1000, 1098, 1389 cm−1 were stronger in Staphylococcus aureus S. aureus and Escherichia coli, which are assigned to aromatic ring skeletal, COO– deformation of guanine, CeC stretch of skeletal proteins, “Breathing” in aromatic rings of phenylalanine, CeC and CeO stretching in carbohydrates, COO-stretching of proteins, respectively. The Raman bands were more distinct for Listeria monocytogenes at 735 and 1064 cm−1, which are assigned to glycosidic ring mode of adenine and CeC and CeO stretching in carbohydrates, respectively. The SERS peaks of 927 and 1123 cm−1 were not found in Staphylococcus aureus, and the band of 999 cm−1 did not appear in Listeria monocytogenes. The differences among SERS spectra from three type of bacteria originating from their different composition and structure make it possible to classify various bacteria when combined with statistical analysis. Although the relative characteristic peaks intensities of three SERS spectra are different, the majority spectral bands of Escherichia coli, Listeria monocytogenes and Staphylococcus aureus exhibit little difference. Therefore, it is essential that chemometric method be used to discriminate different bacteria accurately and automatically. The combination of Principal component analysis (PCA)-Linear discriminative analysis (LDA) has been proved to be a robust method for identifying different biological systems. PCA is widely used as a multivariable analysis method allowing the reduction of multidimensional data sets to several principal components (PCs) to identify and differentiate various spectral groups with similar spectra [42]. LDA is carried out on transformed data after PCA calculations for spectra group classification. By using this method, the minimum intra-class distance and
the maximum inter-class distance of projected pattern sample can be achieved, which means that the pattern sample has the best separability in this space. Considering that it was difficult to classify three bacteria based on similar SERS spectra, the potential application of PCA-LDA for differentiating SERS spectra acquired from three species of food borne bacteria samples were studied in this work. For PCA-LDA analysis, the input SERS spectra from three bacteria were served as PCA model and were projected into transformed space. Then, LDA was performed to find out the variances of SERS spectra and establish models for differentiating three bacteria based on the PCA calculations. As can be seen from Fig. 8a, PCA scores plot of the first two PCs for Escherichia coli, Staphylococcus aureus and Listeria monocytogenes were displayed. The PCA plot showed three separated clusters of SERS spectra originating from the three foodborne bacteria samples, indicating the possibility of bacteria discrimination. Furthermore, we can see the LDA results (Fig. 8b) that the differences among three groups can be determined and the SERS spectra can mainly be categorized into three clusters which is consistent with the PCA results, demonstrating the successfully classification of three foodborne bacteria samples. The discrimination accuracy of three bacteria calculated by LDA is 98.68%. ROC curve was also plotted to evaluate the applicability of PCA-LDA method (Fig. 8c). The integrated area under the curve (AUC) of the ROC was 0.76, 1 and 1, respectively, implying good performance of this classification method. These results indicated that PCA-LDA analysis combined with BP-Au filter paper-based SERS method has a great potential for rapid detection and discrimination of foodborne bacteria.
4. Conclusions In summary, a novel 3D SERS substrate based on BP-Au filter paper 8
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Fig. 8. (a) PCA scores plot of Escherichia coli, Staphylococcus aureus and Listeria monocytogenes. (b) PCA-LDA plots of three foodborne bacteria categories calculated from SERS spectra. (c) ROC curve of the SERS classification result using PCA-LDA method.
with high SERS activity, good reproducibility and stability was successfully prepared by a simple green synthesis method. The 3D SERS substrate was used for the detection of three common foodborne bacteria (Escherichia coli, Listeria monocytogenes and Staphylococcus aureus) for the first time. Remarkable enhancement effect of this 3D SERS substrate on bacteria was proved. Moreover, PCA combined with LDA was employed to classify and identify the three bacteria based on their similar SERS spectra. The results showed that PCA-LDA could successfully differentiate SERS spectra obtained from three bacterial samples. As the whole assay time takes only a few minutes, we suppose that BPAu filter paper-based 3D substrate combined with PCA-LDA can be used for low-cost, rapid and accurate detection of foodborne bacteria. However, it is still challenging to detect pathogens in complicated food matrices using SERS. By integrating the methods of bacteria separation from food with SERS techniques, as well as chemometrics methods, the detection of foodborne pathogen would be more beneficial to practical application in food safety.
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Acknowledgments This work was supported by the National Natural Science Foundation of China (11874021, 61675072, 21505047, 61505055, 61275187, 81500361 and 81670417), the Natural Science Foundation of Guangdong Province of China (2017A030313813 and 2014A030311024), the Science and Technology Project of Guangdong Province of China (2017A020215059), the China Postdoctoral Science Foundation (2018M633065) and the Scientific Research Cultivation Fund for Young Teachers of South China Normal University (18KJ16). Appendix A. Supplementary data TEM image of BP nanosheets (Fig. S1); TEM image of BP-Au nanosheets (Fig. S2); EDS image of BP-Au nanosheets (Fig. S3); UV-Vis spectra of Au NPs, BP and BP-Au NPs (Fig. S4a); UV-Vis spectra of BPAu NPs with different concentrations (Fig. S4b); FDTD simulations of the electromagnetic field enhancement of Au NPs and BP-Au NSs, highresolution P 2p and Au 4f XPS spectra of BP-Au and BP-Au/CV, SERS spectra of CV with Au NPs and BP-Au NSs substrate (Fig. S5). Supplementary data to this article can be found online at https://doi. org/10.1016/j.apsusc.2019.143825. References [1] L. Chen, W. Alali, Editorial: recent discoveries in human serious foodborne pathogenic bacteria: resurgence, pathogenesis, and control strategies, Front. Microbiol. 9 (2018) 2412. [2] X. Zhao, C.W. Lin, J. Wang, D.H. Oh, Advances in rapid detection methods for foodborne pathogens, J. Microbiol. Biotechnol. 24 (3) (2014) 297–312. [3] X.H. Zhao, J.L. Zhong, C.J. Wei, C.W. Lin, T. Ding, Current perspectives on viable but non-culturable state in foodborne pathogens, Front. Microbiol. 8 (2017). [4] E. Eriksson, A. Aspan, Comparison of culture, elisa and pcr techniques for salmonella detection in faecal samples for cattle, pig and poultry, BMC Vet. Res. 3
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Black phosphorus-Au filter paper-based three-dimensional SERS substrate for rapid detection of foodborne bacteria
T ⁎
Deqiu Huanga,1, Zhengfei Zhuanga,1, Zhen Wanga, Shengtao Lia, Huiqing Zhonga, Zhiming Liua, , ⁎ ⁎⁎ Zhouyi Guoa, , Wen Zhangb,c, a MOE Key Laboratory of Laser Life Science & SATCM Third Grade Laboratory of Chinese Medicine and Photonics Technology, College of Biophotonics, South China Normal University, Guangzhou 510631, Guangdong, China b Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, China c Hunan Key Laboratory of Biomedical Nanomaterials and Devices, College of Life Sciences and Chemistry, Hunan University of Technology, Zhuzhou 412007, Hunan, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Surface-enhanced Raman scattering BP-Au nanoparticles Foodborne bacteria detection Filter paper-based SERS substrate
Rapid and accurate detection of foodborne bacteria is believed to be of vital importance in assuring food safety. In this work, we explored a novel label-free three-dimensional surface-enhanced Raman scattering (3D-SERS) substrate based on black phosphorus-Au (BP-Au) filter paper for the detection and discrimination of three common foodborne bacteria including Staphylococcus aureus, Listeria monocytogenes and Escherichia coli without complicated sample processing. It was found that the BP-Au filter paper-based 3D-SERS substrate could offer larger surface area as well as more “hotspots” than 2D-SERS substrate for sample detection. Moreover, our results showed that this 3D substrate could efficiently enhance Raman signals from model molecules and exhibit satisfactory SERS activity allowing for specific recognition and discrimination of three types of target bacteria at a concentration of 107 CFU/mL. Subsequently, SERS spectral data from three bacteria were successfully distinguished by principle component analysis (PCA) and linear discriminant analysis (LDA). These results demonstrated that the novel 3D SERS substrate with facile, low-cost, green fabrication process as well as high sensitivity could serve as an excellent alternative to conventional substrates for rapid label-free detection and identification of foodborne bacteria with the aid of statistical discriminant analysis PCA-LDA in food safety application.
1. Introduction Foodborne diseases caused by foodborne pathogens bacteria such as Staphylococcus aureus, Salmonella enterica, Escherichia coli, Campylobacter jejuni and Listeria monocytogenes may result in severe illness in humans [1]. Rapid detection and discrimination of foodborne bacteria is becoming increasingly important in assuring food safety [2,3]. Current methods for bacteria detection mainly include conventional culture identification strategies [4], immunoassay techniques [5,6], polymerase chain reaction (PCR) [7–10]. The traditional culturing method is regarded as the gold standard, but it is time consuming and labor intensive. Immunoassay strategies can simplify the procedure of bacteria identification with the properties of rapid and sensitive,
however, this method has complicated procedures and low selectivity. PCR-based testing can detect specific bacteria DNA timely and simply; nevertheless, it suffers from the limitation of background interference [11]. For these reasons, it is necessary to explore a more rapid and sensitive methods for accurate bacteria identification. Raman spectroscopy (RS) shows great potential in identifying substances according to their vibrational fingerprint [11–14]. However, low intensity of conventional RS and fluorescence interference generated by some molecules make it difficult to detect biological samples with complex composition and strong spontaneous fluorescence. As the Raman signal of target analyte can be greatly enhanced compared with conventional RS when the sample is close to or adsorbed on the rough surface of noble metals such as Au and Ag, surface enhanced Raman
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Corresponding authors. Correspondence to: W. Zhang, Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, China. E-mail addresses: [email protected] (Z. Liu), [email protected] (Z. Guo), [email protected] (W. Zhang). 1 These authors contributed equally to this work. ⁎⁎
https://doi.org/10.1016/j.apsusc.2019.143825 Received 22 May 2019; Received in revised form 18 July 2019; Accepted 28 August 2019 Available online 28 August 2019 0169-4332/ © 2019 Elsevier B.V. All rights reserved.
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2. Materials and methods
spectroscopy (SERS) has emerged as a more sensitive analytical technique in biological detection with advantages of simple pretreatment, simple operation, short detection time and high sensitivity. Using SERS technique, high-quality of Raman signals can be obtained with low excitation power which may prevent damage to biological samples. Moreover, SERS can reduce the spontaneous fluorescence background of biological samples [15]. Hence, SERS has shown great promise in biological field. In recent years, SERS has also played an important role in the detection of microorganisms [16,17]. Drikell et al. used SERS labeled immunoassay to detect viruses at low concentrations [18]. Martin Kögler et al. synthesized Au nanoparticles-based SERS substrate and successfully applied it to the discrimination of E. coli and Listeria monocytogenes [19]. Although SERS was reported to have the ability of discriminating bacteria using noble metal (Au, Ag, etc.) as SERS substrate, its practical application is still challenging, such as poor reproducibility of Raman signal, low bacteria concentration and background interference in the sample [20–24]. Therefore, it is necessary to explore novel label-free SERS substrates with the characteristics of simple preparation, highly stable and low cost to get more enhanced and reproducible SERS signals for bacteria detection. Two mechanisms may attribute to SERS effect; chemical mechanism (CM) based on the charge transfer between substrate and analytes, and electromagnetic mechanism (EM) which depends on the plasmonic nanostructures [25]. Black phosphorus (BP), as the emerging inorganic two-dimensional nanomaterial potential with high biocompatibility and a layer-dependent direct bandgap varying from 0.3 eV for the bulk to 2.0 eV for a single layer has been becoming one of the most perspective materials of great potentials in biomedicine, electronics and optoelectronics [26]. In our previous study, BP-Au nanosheets was applied for SERS bioanalysis [27,28]. The decoration of Au nanoparticles onto BP nanosheets enabled the integration of CM from BP nanosheets and EM from Au nanoparticles, resulting in significant enhanced and highly reproducible detection of chemical molecules than bare Au nanoparticles or BP nanosheets, demonstrating its great potential in bio-application. Compared with conventional substrates, three-dimensional (3D) SERS substrates not only possess larger surface area, which is favor of adsorbing more probe molecules, but also can provide more “hotspots” and binding sites for analytes when the substrate is modified by noble metal nanoparticles [29–32]. Inspired by this idea, numerous efforts have been taken to synthesis 3D SERS platforms. Yang et al. prepared a novel 3D mesoporous ZnO/Ag SERS substrate with high sensitivity and reproductivity for the detection of dye, and the 3D substrate showed good SERS activity [33]. In addition, similar 3D SERS substrate based on Au/TiO2, Ag/ZnO, Au/graphene and Ag/graphene has been developed for biomedical detection [33–36]. Nevertheless, the preparation procedure of these substrates is time-consuming and complex, thus limited their use in rapid SERS assay. Natural filter paper is considered to be an ideal solid substrate ascribing to their low-cost, easy to obtain, biodegradable, recyclable, and natural 3D porous structure. Filter paper can attach nanoparticles in many ways such as in situ synthesis, indirect deposition, silver mirror reaction, ink jet printing, water immersion method, etc. [37,38]. These filter paper-based SERS substrates could create more “hot spots” to achieve stronger enhancement effect as well as maintain good signal reproducibility. Based on the above background, we prepared a novel label-free BPAu filter paper-based 3D-SERS substrate by simply absorption of the in situ fabricated BP-Au nanosheets onto natural filter paper with several immersion-rinsing-drying cycles. SERS performance of the prepared 3D SERS substrate was evaluated. Furthermore, the synthesized BP-Au filter paper-based 3D SERS substrate was used for the detection and discrimination of three common foodborne bacteria including Staphylococcus aureus, Listeria monocytogenes and Escherichia coli.
2.1. Materials Whatman qualitative filter paper was purchased from Dalian Meilun Biotechnology Co., LTD. Crystal violet (CV), Malachite green (MG) and Ponceau S (PS) were purchased from Sigma-Aldrich. Bulk BP crystals were obtained from XFNANO Materials Tech Co. Ltd. (Nanjing, China) and stored in a dark Ar-filled glovebox. N-Methyl-2-pyrrolidone (NMP), sodium citrate and chloroauric acid (HAuCl4·4H2O) were obtained from China National Medicine Corporation (Shanghai, China). Ultrapure water (18.2 MΩ, Milli-Q System, Millipore, USA) was used in all experiments. 2.2. Preparation of BP-Au filter paper-based SERS substrate 2.2.1. Synthesis of BP nanosheets Probe sonication in combination with bath sonication was applied to prepare BP nanosheets via liquid exfoliation method according to our previous study [28]. Briefly, 30 mg of the bulk BP powders were dispersed in 30 mL of NMP and sonicated with an ultrasonic probe (600 W, 2 s duration and 4 s interval) for 6 h on ice. Then, the mixture was bath sonicated overnight in an ice bath at a power of 300 W. The dispersion was centrifuged for 10 min at 2000 rpm to remove unexfoliated BP. Subsequently, BP nanosheets was collected by centrifuged at 7000 rpm for 20 min and re-suspended in NMP. 2.2.2. In situ synthesis of BP-Au BP-Au nanosheets were synthesized by a facile reflux method. Briefly, 300 μL of HAuCl4 (10 mM) were dispersed in 20 mL boiling water, Afterward, 150 μL of as-prepared BP nanosheet at the concentration of 5 mg/mL in NMP was added under constant stirring for 2 min until the color of the solution was changed from yellow-brown to purple red. Finally, the product was centrifugated at 7000 rpm for 10 min to remove bare Au nanoparticles and dispersed in water. 2.2.3. Synthesis of Au filter paper and BP-Au filter paper-based SERS substrate The BP-Au filter paper-based 3D SERS substrate was prepared simply by immersing filter paper in a petri dish containing 5 mL BP-Au particles for 24 h. Then the filter paper was rinsing thoroughly with distilled water to remove loosely bound BP-Au nanoparticles, and dried at room temperature overnight. After several cycles of immersion-rinsing-drying procedure, the BP-Au filter paper-based 3D SERS substrate was obtained for further detection. The whole preparation process is shown in Scheme 1. Au filter paper-based SERS substrate was synthesized under the same process except for the incubating nanoparticles being replaced by Au nanoparticles. 2.3. Characterization The morphology and energy dispersive X-ray (EDX) spectrum of BP nanosheets and BP-Au nanosheets were characterized by a 120 kV transmission electron microscope (TEM, JEOL, JEM-2100HR, Japan) equipped with an EDX spectrometer. The morphology of SERS substrates was observed by Scanning electron microscope (SEM, ZEISS Gemini 500), equipped with an energy-dispersive X-ray (EDX) spectrum. X-ray photoelectron spectroscopy (XPS) spectra of BP-Au NSs and BP-Au NSs mixed with CV (BP-Au/CV) were recorded on ESCALAB250Xi (Thermal Fisher Scientific). The ultraviolet visible nearinfrared (UV–Vis-NIR) spectra of the materials were conducted on an UV-VIS-NIR spectrometer (UV-3200S, MAPADA, China). Raman spectra were collected using Renishaw inVia microspectrometer (Renishaw, UK) under a 514.5 nm diode laser excitation. The UV-VIS spectrometer of 3D SERS substrates were accorded on an optical fiber spectrometer. 2
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Scheme 1. Schematic of the fabrication of BP-Au filter paper-based SERS substrates and its application in detection of analytes and three foodborne bacteria.
USA). The baseline correction was performed to analyze the data. In this study, principal component analysis (PCA) and linear discriminative analysis (LDA) were used for the identification and discrimination of three types of bacteria.
2.4. SERS experiments For investigating the SERS effect of 3D SERS substrates, crystal violet (CV), Malachite green (MG) and Ponceau S (PS) were chosen as probe samples. Firstly, with filter paper used as blank control, Au filter paper-based and BP-Au filter paper-based 3D substrates served as control group and experimental group, the enhancement effect of SERS substrates to CV, MG and PS at different concentrations was studied. Second, different ratio of HAuCl4 and BP in 3D SERS substrates were synthesized and 3D substrate with the best SERS effect was selected for the following experiments. All experiments were independently conducted three times. All the dye molecules were dropped onto the 3D SERS substrates and were then detected using a Renishaw inVia Raman microspectroscopy. The spectral coverage was from 700 to 1700 cm−1 with a 514.5 nm laser excitation. The laser power was 25 mW with a scan time of 10 s. Bacteria samples such as Escherichia coli, Staphylococcus aureus and Listeria monocytogenes with the concentration of 107 CFU/mL were dropped onto 3D substrates and their SERS spectra between 620 and 1720 cm−1 were recorded under 785 nm laser excitation. Bacteria samples on bare filter paper-based 3D SERS substrate were also scanned.
3. Results and discussion 3.1. Characterization of BP-Au filter paper-based 3D SERS substrate As shown in Fig. S1, single and few-layered BP nanosheets were successfully obtained via liquid exfoliation in NMP from BP crystal. The average lateral size of BP nanosheets was between 300 nm and 1 μm. After in situ reduction of HAuCl4, BP-Au nanosheets were synthesized, which was evidenced by the massive coated Au nanoparticles with an average size of 30 nm on the surface of BP nanosheets (Fig. S2). These Au nanoparticles could generate abundant “hot spots” between the gap of two neighboring nanostructures, showing great potential to serve as excellent SERS substrates. The EDX image of BP-Au spectrum also confirmed the existence of Au and P in BP-Au nanosheets (Fig.S3). The characteristic absorption peak at 530 nm in UV-VIS spectra of BP-Au NP also suggested the successful attachment of AuNPs in BP NSs. After several immersion-rinsing-drying cycles, BP-Au filter paper-based 3D SERS substrate was synthesized. SEM characterization of the 3D SERS substrate was shown in Fig. 1. It could be seen that the BP-Au nanosheets were distributed in the filter paper, and the elemental mapping of Au, P and O in the selected region matched well with BP-Au nanosheets, demonstrating the successful fabrication of BP-Au filterpaper 3D SERS substrates. As can be seen in Fig. 2, three distinct Raman peaks located at 361 cm−1, 437 cm−1 and 465 cm−1 were revealed from the Raman spectra of BP NSs, which represents one out-of-plane phonon mode (A1g) and two in-plane modes (B2g and A2g), respectively [39]. Compared with BP, BP-Au exhibited a significant red shift in its Raman spectra due to the presence of Au NPs, which further verifying that the BP-Au NPs was successfully prepared. The optical fiber spectrometer characterization of BP-Au filter paper-based 3D SERS substrate was also performed. The characteristic absorption peak at 530 nm and the enhanced absorption in NIR region of BP-Au filter paper indicated that BP-Au was coated onto the surface of filter paper.
2.5. Electromagnetic field distribution simulations Finite-difference time domain (FDTD) simulations were performed by using FDTD Solutions software (Lumerical Solutions Inc.) to analyze the plasmonic nanostructures of Au NPs and BP-Au NSs. The diameter of the AuNPs and the thickness of BP NSs was set according to the average size measured from the experimental results. A total-field scattered-field light source with a wavelength of 785 nm was chosen. Perfectly matched layer (PML) boundary conditions was used to XYZ axis directions around the AuNPs. The mesh size between BP and AuNPs was set as 0.2 nm. 2.6. Data analysis The SERS spectra data analysis were conducted using GraphPad Prism 8.0.1 for Windows (GraphPad Software, San Diego, California, 3
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Fig. 1. Characterization of BP-Au filter paper-based SERS substrate. (a) SEM image of filter paper; (b-d) SEM images with different magnification and (e) EDS image of BP-Au filter paper-based SERS substrate; (f-h) EDS mapping of element O, Au and P in BP-Au filter paper-based SERS substrate, respectively.
1370 cm−1, 1178 cm−1 and 916 cm−1 were attributed to the N-phenyl stretching vibration mode, CeH bending vibration and the skeleton vibration of the ring, respectively. The characteristic peaks at 1539 cm−1, 1588 cm−1 and 1620 cm−1 were assigned to the CeC stretching vibration of the aromatic ring. In comparison with Au filter paper-based substrate, BP-Au filter paper-based substrate displayed obviously enhanced Raman signal, indicating excellent SERS activity of BP-Au filter paper-based 3D SERS substrates. The superior SERS performance of BP-Au filter paper-based 3D substrates can be attributed to the following reasons. Firstly, the dotted BP-Au NPs in the 3D nanostructures of filter paper formed a large number of “hot spots”. “Hot spots” are highly localized regions of greatly enhanced electromagnetic fields caused by localized surface plasmon resonance (LSPR) from the
3.2. SERS activity of BP-Au filter paper-based 3D substrate In order to find the optimal BP-Au filter paper-based 3D substrates for further SERS detection, the SERS enhancement effects on 1 μM CV based on a group of BP-Au filter paper-based 3D substrates prepared by adjusting the ratio of the amount of HAuCl4 to BP NSs were investigated (Fig. 3a–b). The substrate 2 had the superior SERS activity and was used in the following experiments. Subsequently, crystal violet (CV) was used as a Raman probe molecule to explore the SERS performance of BP-Au filter paper-based 3D substrate due to its confirmed and unique Raman peak. As shown in Fig. 3c, Raman signal of CV could be significantly enhanced when BP-Au filter paper-based 3D substrate was served as SERS substrate. The typical characteristic bands located at 4
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Fig. 2. (a) Raman spectra of BP NSs and BP-Au NSs; (b) Absorbance spectra of BP-filter paper, Au NPs-filter paper and BP-Au NPs-filter paper substrate.
BP-Au NPs in filter paper could produce synergistic enhancement effect between EM from Au NPs and additional CM from BP NSs. It is recognized that there are two main mechanisms for SERS enhancement, EM dependent on metal nanoparticles and CM based on charge transfer between substrate and analyte. Generally, these two mechanisms usually coexist in reality, with the EM enhancement playing dominate role. In order to verify the combined SERS enhancement mechanism from BP-Au, FDTD simulation of the electromagnetic field enhancement
noble metals such as Au and silver, and usually occurs in the gaps or sharp tips of plasmonic materials. Once the analytes are very close to “hot spots” of the SERS substrates, a strong SERS enhancement effect will be achieved [40]. In the BP-Au filter paper-based 3D substrates, BPAu NSs has massive Au NPs closely aligned on the BP NSs, which makes “hot spots” be generated without any aggregation process. Secondly, the analytes adsorption ability of the 3D SERS substrates was greatly improved due to its large specific surface area. Thirdly, the scattered
Fig. 3. (a) Raman spectra of bare filter paper and different BP-Au NPs filter paper-based SERS substrate; (b) SERS spectra of 1 μM CV with different BP-Au NPs filter paper SERS substrate; (c) SERS spectra of CV on filter paper, Au NPs filter paper, BP-Au NPs filter paper-based SERS substrate, respectively; (d) SERS spectra of CV with different concentrations on BP-Au NPs filter paper-based SERS substrate. 5
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3.3. Reproducibility and stability of BP-Au filter paper-based SERS substrate
of Au NPs and BP-Au NSs was performed. As shown in Fig. S5a, the results indicated that a strong electromagnetic field was localized between adjacent Au NPs from Au NPs array as well as BP-Au array. Moreover, there was also a greatly enhanced electromagnetic field between Au NPs and BP NSs, which may lead to the enhanced SERS effect of BP-Au compared with Au NPs. On the other hand, chemical states analysis of BP-Au NSs were performed by XPS characterization to elucidate the interaction between the absorbed CV molecules and BP-Au substrate. It can be seen from Fig. S5b and c that BP-Au NSs exhibited characteristic P 2p3/2 (129.8 eV) and P 2p1/2 (130.6 eV) bands, as well as a sub-band (134.59 eV) of phosphorus oxide [41]. However, this phosphorus oxides band shifted to 134.22 eV in the XPS spectra of BPAu/CV, implying moderate charge transfer between absorbed CV and phosphorus oxides from BP-Au. In addition, the Au 4f7/2 and 4f5/2 doublet pair only shifted less than 0.1 eV, which can be considered no charge transfer happened between Au and CV. These results confirmed that the CM enhancement may mainly originate from the interaction between BP NSs and CV. Furthermore, the SERS performance of BP-Au and Au NPs substrates was also explored in Fig. 5Sd and e. It was found that the SERS enhancement effect of BP-Au was more superior than Au NPs, which may be ascribed to the above listed two reasons. In order to analyze the SERS effect of the 3D substrate quantitatively, we calculated its enhancement factor (EF) according to the following formula: EF = (ISERS / CSERS) / (IRaman / CRaman). CSERS, ISERS IRaman and CRaman represent the concentration of SERS probe molecule, the intensity of SERS signals, the intensity of normal RS signals and the concentration of probe molecule used in normal RS assay, respectively. The EF value of 3D BP-Au filter paper-based substrate was calculated to be 2.4 × 104, which is 12 times as high as the Au filter paper-based substrate whose EF value was 2.0 × 103, demonstrating better SERS activity than Au filter paper-based substrate. It also can be seen from Fig. 3d that the SERS signal intensity of CV decreased with the decrease of CV concentration. However, the characteristic peaks of CV could still be identified clearly even when the CV concentration decreased to 1 nM. The SERS effects of 3D substrates on two opposite charged probe dye molecules including a cationic dyes malachite green (MG) and an anionic dye ponceau S (PS) were evaluated. As can be seen from Fig. 4, although both of Au filter paper-based and BP-Au filter paper-based 3D substrate showed significantly SERS effect on two dyes with opposite charges, BP-Au filter paper-based 3D substrate revealed more preferred SERS activity with equivalent amount of Au NPs in two substrates. It is worth noting that the enhancement effect of BP-Au filter paper 3D substrate on negatively charged PS was distinct weaker than that on positively charged MG. This phenomenon could be attributed to the absorption capacity of the negative-charged BP in BP-Au filter paper 3D substrate to positive charged groups in the PS.
In practical application, the stability and reproducibility of the SERS substrate is of vital importance for analytes detection. We dropped exactly the same concentration of CV solution to BP-Au filter paperbased 3D substrates and randomly selected eight points on each substrate for SERS measurement. It can be seen from Fig. 5 that the characteristic peak and intensity of the obtained SERS spectra were similar to each other. To quantitatively evaluate the repeatability of the SERS spectra, we selected three characteristic peak of CV (811 cm−1, 1370 cm−1 and 1620 cm−1) as model reference to calculated their relative standard deviation (RSD) values. The calculated results were 9.4%, 9.1% and 4.2%, respectively, which can be proved that the SERS substrate has high reproducibility. Then, we further explored the stability of BP-Au filter paper-based 3D substrate by SERS experiment. The 3D SERS substrate prepared in the same batch was stored in a refrigerator at 4 °C for 12 days. CV aqueous solution of 1 mM concentration was added to the 3D substrate for SERS assay every 3 days. There results showed no obvious changes among the five measured spectra. Moreover, the intensity of characteristic peak of CV at 1178 cm−1 stored for 12 days was analyzed and the signal intensity displayed a decline of 6.2%, indicating that the BP-Au filter paper-based 3D substrate has reasonable stability (Fig. 6). 3.4. SERS Spectra and classification analysis of foodborne bacteria In order to verify the SERS effect on three types of foodborne bacteria with BP-Au filter paper-based 3D SERS substrate, the Raman spectra of three bacteria with filter paper were recorded firstly. As shown in Fig. 7a, the bacteria on the bare filter paper showed no distinguished Raman signals. After being added onto the BP-Au filter paper-based 3D SERS substrate, the Raman spectra of three bacteria exhibited remarkably enhanced Raman signals (Fig. 7b-d). The average spectra of three foodborne bacteria were distinct and the intensity of the Raman peaks were greatly improved than with filter paper substrate, demonstrating that the above three foodborne bacteria could be detected with BP-Au filter paper served as SERS substrate. To confirm the SERS spectra reproducibility of BP-Au filter paper-based SERS substrate, SERS spectra of Escherichia coli, Staphylococcus aureus and Listeria monocytogenes on BP-Au filter paper-based substrate from five randomly selected points were shown in Fig. 7 and showed good reproducibility. As shown in Fig. 7b–d, the SERS spectra located between 620 cm−1 to 1720 cm−1 of Escherichia coli, Listeria monocytogenes and Staphylococcus aureus showed a little difference between each other. By comparison of SERS spectra of three bacteria, distinctions of their
Fig. 4. (a) SERS spectra of a cationic dyes malachite green (a) and an anionic dye ponceau S (b) at the concentration of 1 mM with filter paper, Au NPs filter paperbased SERS substrate and BP-Au NPs filter paper-based SERS substrate, respectively. 6
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Fig. 5. (a) SERS spectra of CV with BP-Au NPs filter paper-based SERS substrate at randomly selected eight positions; (b–d) SERS intensity distribution of the above eight spectra in the bands of 811 cm−1, 1370 cm−1 and 1620 cm−1 of CV, respectively.
characteristic Raman bands were collected for further bacteria discrimination (Table S1). The SERS spectra characteristic peaks of Escherichia coli with were observed at 690, 790, 850, 920, 1001, 1053, 1097, 1161, 1168, 1220, 1305, 1317, 1382, 1418, 1474, 1543 and 1621 cm−1. The SERS spectra of Staphylococcus aureus displayed characteristic peaks at 668, 727, 785, 859, 919, 999, 1058, 1151, 1319, 1331, 1389, 1482, 1543 and 1621 cm−1. The typical Raman bands of Listeria monocytogenes were mainly located at 678, 735, 791, 859, 921, 996, 1098, 1064, 1138, 1151, 1161, 1228, 1310, 1391, 1476, 1546, 1597 and 1630 cm−1. The Raman fingerprint information can mainly be assigned to proteins, phospholipids, nucleic acids, lipopolysaccharides, carbohydrates, peptidoglycan in the cell structural components of bacteria. Through spectral match, we could acquire special structural information of different bacteria, thus differentiating the bacteria. As shown in Fig. 7b–d, the Raman peaks at 727–735, 860, 1098, 1151 and 1621–1630 cm−1 were similar among three species bacteria spectra, which could be assigned to the components of bacteria cell wall (727–735 cm−1 for peptidoglycan structure of the bacterial cell wall, 860 cm−1 for CeC stretch skeletal protein, 1098 cm−1 for CeC and CeO stretch in carbohydrates, 1151 cm−1 for = C-C = unsaturated fatty acids in lipids and CeN aromatic amino acids in proteins,
Fig. 6. SERS stability of BP-Au NPs filter paper-based SERS substrate within12 days.
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Fig. 7. (a) SERS spectra of three foodborne pathogens including Escherichia coli, Staphylococcus aureus and Listeria monocytogenes on filter paper substrate. SERS spectra of (b) Escherichia coli, (c) Staphylococcus aureus and (d) Listeria monocytogenes on BP-Au filter paper-based substrate from five randomly selected points.
1621–1630 cm-1 for amide II, CeN stretch and NeH bend). The tentative assignment of Raman bands from the SERS spectra of three foodborne bacteria were listed in Table. S1. The intensity of Raman bands at 623, 668, 860, 1000, 1098, 1389 cm−1 were stronger in Staphylococcus aureus S. aureus and Escherichia coli, which are assigned to aromatic ring skeletal, COO– deformation of guanine, CeC stretch of skeletal proteins, “Breathing” in aromatic rings of phenylalanine, CeC and CeO stretching in carbohydrates, COO-stretching of proteins, respectively. The Raman bands were more distinct for Listeria monocytogenes at 735 and 1064 cm−1, which are assigned to glycosidic ring mode of adenine and CeC and CeO stretching in carbohydrates, respectively. The SERS peaks of 927 and 1123 cm−1 were not found in Staphylococcus aureus, and the band of 999 cm−1 did not appear in Listeria monocytogenes. The differences among SERS spectra from three type of bacteria originating from their different composition and structure make it possible to classify various bacteria when combined with statistical analysis. Although the relative characteristic peaks intensities of three SERS spectra are different, the majority spectral bands of Escherichia coli, Listeria monocytogenes and Staphylococcus aureus exhibit little difference. Therefore, it is essential that chemometric method be used to discriminate different bacteria accurately and automatically. The combination of Principal component analysis (PCA)-Linear discriminative analysis (LDA) has been proved to be a robust method for identifying different biological systems. PCA is widely used as a multivariable analysis method allowing the reduction of multidimensional data sets to several principal components (PCs) to identify and differentiate various spectral groups with similar spectra [42]. LDA is carried out on transformed data after PCA calculations for spectra group classification. By using this method, the minimum intra-class distance and
the maximum inter-class distance of projected pattern sample can be achieved, which means that the pattern sample has the best separability in this space. Considering that it was difficult to classify three bacteria based on similar SERS spectra, the potential application of PCA-LDA for differentiating SERS spectra acquired from three species of food borne bacteria samples were studied in this work. For PCA-LDA analysis, the input SERS spectra from three bacteria were served as PCA model and were projected into transformed space. Then, LDA was performed to find out the variances of SERS spectra and establish models for differentiating three bacteria based on the PCA calculations. As can be seen from Fig. 8a, PCA scores plot of the first two PCs for Escherichia coli, Staphylococcus aureus and Listeria monocytogenes were displayed. The PCA plot showed three separated clusters of SERS spectra originating from the three foodborne bacteria samples, indicating the possibility of bacteria discrimination. Furthermore, we can see the LDA results (Fig. 8b) that the differences among three groups can be determined and the SERS spectra can mainly be categorized into three clusters which is consistent with the PCA results, demonstrating the successfully classification of three foodborne bacteria samples. The discrimination accuracy of three bacteria calculated by LDA is 98.68%. ROC curve was also plotted to evaluate the applicability of PCA-LDA method (Fig. 8c). The integrated area under the curve (AUC) of the ROC was 0.76, 1 and 1, respectively, implying good performance of this classification method. These results indicated that PCA-LDA analysis combined with BP-Au filter paper-based SERS method has a great potential for rapid detection and discrimination of foodborne bacteria.
4. Conclusions In summary, a novel 3D SERS substrate based on BP-Au filter paper 8
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Fig. 8. (a) PCA scores plot of Escherichia coli, Staphylococcus aureus and Listeria monocytogenes. (b) PCA-LDA plots of three foodborne bacteria categories calculated from SERS spectra. (c) ROC curve of the SERS classification result using PCA-LDA method.
with high SERS activity, good reproducibility and stability was successfully prepared by a simple green synthesis method. The 3D SERS substrate was used for the detection of three common foodborne bacteria (Escherichia coli, Listeria monocytogenes and Staphylococcus aureus) for the first time. Remarkable enhancement effect of this 3D SERS substrate on bacteria was proved. Moreover, PCA combined with LDA was employed to classify and identify the three bacteria based on their similar SERS spectra. The results showed that PCA-LDA could successfully differentiate SERS spectra obtained from three bacterial samples. As the whole assay time takes only a few minutes, we suppose that BPAu filter paper-based 3D substrate combined with PCA-LDA can be used for low-cost, rapid and accurate detection of foodborne bacteria. However, it is still challenging to detect pathogens in complicated food matrices using SERS. By integrating the methods of bacteria separation from food with SERS techniques, as well as chemometrics methods, the detection of foodborne pathogen would be more beneficial to practical application in food safety.
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Acknowledgments This work was supported by the National Natural Science Foundation of China (11874021, 61675072, 21505047, 61505055, 61275187, 81500361 and 81670417), the Natural Science Foundation of Guangdong Province of China (2017A030313813 and 2014A030311024), the Science and Technology Project of Guangdong Province of China (2017A020215059), the China Postdoctoral Science Foundation (2018M633065) and the Scientific Research Cultivation Fund for Young Teachers of South China Normal University (18KJ16). Appendix A. Supplementary data TEM image of BP nanosheets (Fig. S1); TEM image of BP-Au nanosheets (Fig. S2); EDS image of BP-Au nanosheets (Fig. S3); UV-Vis spectra of Au NPs, BP and BP-Au NPs (Fig. S4a); UV-Vis spectra of BPAu NPs with different concentrations (Fig. S4b); FDTD simulations of the electromagnetic field enhancement of Au NPs and BP-Au NSs, highresolution P 2p and Au 4f XPS spectra of BP-Au and BP-Au/CV, SERS spectra of CV with Au NPs and BP-Au NSs substrate (Fig. S5). Supplementary data to this article can be found online at https://doi. org/10.1016/j.apsusc.2019.143825. References [1] L. Chen, W. Alali, Editorial: recent discoveries in human serious foodborne pathogenic bacteria: resurgence, pathogenesis, and control strategies, Front. Microbiol. 9 (2018) 2412. [2] X. Zhao, C.W. Lin, J. Wang, D.H. Oh, Advances in rapid detection methods for foodborne pathogens, J. Microbiol. Biotechnol. 24 (3) (2014) 297–312. [3] X.H. Zhao, J.L. Zhong, C.J. Wei, C.W. Lin, T. Ding, Current perspectives on viable but non-culturable state in foodborne pathogens, Front. Microbiol. 8 (2017). [4] E. Eriksson, A. Aspan, Comparison of culture, elisa and pcr techniques for salmonella detection in faecal samples for cattle, pig and poultry, BMC Vet. Res. 3
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