SERS-Based Lateral Flow Strip Biosensor for Simultaneous Detection

Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology & Business University (BTBU), Beijing 100048, China. J. Agr...
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A SERS-based lateral flow strip biosensor for simultaneous detection of Listeria monocytogenes and Salmonella enterica serotype Enteritidis Hai-bin Liu, Xin-jun Du, Yu-xuan Zang, Ping Li, and Shuo Wang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b03957 • Publication Date (Web): 02 Nov 2017 Downloaded from http://pubs.acs.org on November 3, 2017

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Journal of Agricultural and Food Chemistry

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A SERS-based lateral flow strip biosensor for simultaneous detection of Listeria

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monocytogenes and Salmonella enterica serotype Enteritidis

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Hai-bin Liu, * Xin-jun Du, * Yu-Xuan Zang, * Ping Li, * Shuo Wang*†‡

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*Key Laboratory of Food Nutrition and Safety, Ministry of Education, Tianjin

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University of Science and Technology, Tianjin 300457, China

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Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing

Technology & Business University (BTBU), Beijing 100048, China.

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Corresponding author: Key Laboratory of Food Nutrition and Safety, Ministry of

10

Education, Tianjin University of Science and Technology, Tianjin 300457, China.

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Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing

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Technology & Business University (BTBU), Beijing 100048, China.

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Tel.: +86 22 60912484; Fax: +86 22 60912484.

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E-mail address: [email protected] (S. Wang)

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ABSTRACT

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Rapid, sensitive, point-of-care detection of bacteria is extremely important in food

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safety. To address this requirement, we developed a new surface-enhanced Raman

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scattering (SERS)-based lateral flow (LF) strip biosensor combined with recombinase

27

polymerase

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monocytogenes and Salmonella enterica serotype Enteritidis. AuMBA@Ag core-shell

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nanoparticles were used in this SERS-LF. Highly sensitive quantitative detection is

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achieved by measuring the characteristic peak intensities of SERS tags. Under optimal

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conditions, the SERS intensities of MBA at 1077 cm-1 on test lines are used to

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measure S. Enteritidis (y=1980.6x-539.3, R2=0.9834) and L. monocytogenes

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(y=1696.0x -844, R2=0.9889), respectively. The limit of detection is 27 CFU/mL for S.

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Enteritidis and 19 CFU/mL for L. monocytogenes. Significantly, this SERS-LF has

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high specificity and applicability in the detection of L. monocytogenes and S.

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Enteritidis in food samples. Therefore, the SERS-LF is a feasible method for the rapid

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and quantitative detection of a broad range of bacterial pathogens in real food

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samples.

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KEYWORDS: recombinase polymerase amplification (RPA), foodborne pathogen,

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surface-enhanced Raman scattering (SERS), food safety

amplification

(RPA)

for

simultaneous

detection

of

Listeria

2

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Journal of Agricultural and Food Chemistry

INTRODUCTION

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Foodborne illness caused by microorganisms have attracted world-wide attention

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in the food industry and scientific research.1,2 The most common prevalent foodborne

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pathogens are Salmonella enterica, Staphylococcus aureus, Listeria monocytogenes

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and Bacillus cereus.3 Salmonella is one of the most common enteric pathogens and

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can cause salmonellosis in humans who consume contaminated poultry, meat, and

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eggs.4 One of the most common serotypes related to salmonellosis is S. enterica

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serovar Enteritidis.5 Listeria monocytogenes is associated with listeriosis and is more

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likely to lead to death.6 Most human listeriosis cases were caused by consumption of

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contaminated food. Meat, poultry, milk, and vegetables are the most frequently food

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associated with foodborne illnesses. Therefore, feasible and accurate detection

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methods are urgently required for the identification and control of the two pathogens.

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The current standard method for the detection of pathogens is based on culturing

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and includes sequential steps of pre-enrichment, selective enrichment and biochemical

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identification; this generally takes 2-3 days to complete.7 Many new methods have

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been established for foodborne pathogen detection, such as real-time polymerase

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chain reaction (RT-PCR),8 enzyme-linked immunosorbent assays (ELISAs),9

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electrochemical immunosensors10 and polymerase chain reaction (PCR). However,

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RT-PCR and electrochemical immunosensors are complicated and require skilled

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technicians.11 The main disadvantage of ELISAs is a complicated washing procedure.

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PCR is considered a sensitive method for pathogen detection and could amplify low

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levels of target DNA to detectable levels in a few hours.12 However, it requires a 3

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temperature cycling instrument and relies on a highly trained operator, which limits it

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use in the field.

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To circumvent the limitations of PCR, several isothermal amplification

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techniques to amplify nucleic acids have been established to avoid the requirement for

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thermal cycling equipment. Recombinase polymerase amplification (RPA) is one

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representative isothermal amplification technique with great potential in point-of-use

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detection. RPA has been applied to develop detection methods for intestinal

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protozoa,13 plant pathogens,14 group B streptococcus15 and human noroviruses.16 RPA

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is based on a recombinase enzyme to facilitate the insertion and binding of the

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forward and the reverse primers to their complementary sequence within the

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template.17 RPA could react at a constant temperature (37 C–42 C) in short time

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( 2)4

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than the average signal of negative control. At the concentrations of 1.9101 CFU/mL

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of L. monocytogenes and 2.7101 CFU/mL of S. Enteritidis, the SERS intensity of test

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line 1 and test line 2 was 1857.6 and 1362.2, respectively, 3.4- and 2.5-fold higher

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than the negative control, with a SERS intensity of 549.0 calculated at 1077 cm-1.

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Therefore, the detection limit of RPA-LF-SERS was 1.9101 CFU/mL of L.

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monocytogenes and 2.7101 CFU/mL of S. Enteritidis.

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Specificity of the RPA-LF-SERS assay. To evaluate the specificity of the

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SERS-based strip assay, four strains of L. monocytogenes, four strains of S. Enteritidis,

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and nine other foodborne strains at OD0.6 were applied to the RPA-LF-SERS assay;

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the results are displayed in Fig. 3. As expected, only the L. monocytogenes and S.

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Enteritidis strains displayed positive results (Fig. 3B), and no obvious color changes 14

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were observed when testing other bacterial strains (Fig. 3C).

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Application to selected food samples. Milk, chicken breast, and beef were

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collected for L. monocytogenes and S. Enteritidis detection. The samples were spiked

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with different concentrations of L. monocytogenes and S. Enteritidis, and the genomic

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DNAs of each tested samples were directly extracted without enrichment and tested

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with our RPA-LF-SERS. As shown in Table 3 and Fig. 6, the recoveries of L.

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monocytogenes in milk, chicken breast, and beef were 94.65-113.86 %. Meanwhile,

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the recoveries of S. Enteritidis in milk, chicken breast, and beef were 90.46-109.90%.

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The RPA-LF-SERS biosensor has a detection limit of S. Enteritidis in milk, chicken

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breast, and beef of 31, 35, and 35 CFU/mL. The detection limit of L. monocytogenes

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in milk, chicken breast, and beef is 36, 29, and 22 CFU/mL. The detection limit of

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bacteria in food samples is slightly higher than in a pure bacterial solution.

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Reproducibility of the RPA-LF-SERS assay. Two LF strips with L.

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monocytogenes and S. Enteritidis concentrations at 1.9106 CFU/mL and 2.7106

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CFU/mL or at 1.9102 CFU/mL and 2.7102 CFU/mL were tested. The SERS

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intensities at 1077 cm-1 from ten parallel spots on the middle of the test lines were

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measured and displayed in Fig. 7. Within each strip, the RSD values of the 10

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different spots on each test lines were 5.99%, 4.26%, 5.81%, and 11.07%, indicating

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the high precision of the SERS signal.

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DISCUSSION

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A SERS-based lateral flow strip composed of two test lines and one control line

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was developed for simultaneous detection of two pathogens, S. Enteritidis and L. 15

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monocytogenes. The capture antibodies (McAb-digoxin and McAb-FITC) and control

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antibodies (McAb-streptavidin) were dispensed on the test lines (test line 1 and test

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line 2) and control line of the NC membrane, respectively. In the three tested NC

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membranes, HF135 was found to be the appropriate one in SERS-LF detection and

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this might because HF135 could provide a suitable capillary flow rate giving a

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suitable antigen-antibody interaction time. The antibodies were immobilized on the

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NC membrane via electrostatic interactions, achieved by interactions between the

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dipoles of the nitrate group in the NC membrane and the dipoles of the peptide bonds

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in the antibody.33 In the conjunction pad, the streptavidin with positive charges is

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passively attached to AuMBA@Ag via electrostatic interaction34 to form monodisperse

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AuMBA@Ag-streptavidin. The multiplex RPA was used to generate numerous biotin-

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and digoxin-labeled or biotin- and FITC-labeled duplex DNAs. The product solution

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migrated toward the absorption pad by capillary force,32 passed through the

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conjunction pad, and rehydrated the streptavidin-coated AuMBA@Ag. The biotin on

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the duplex DNA reacted with the streptavidin on the surface of the AuMBA@Ag to

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form

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DNA-biotin-streptavidin-AuMBA@Ag, which was then captured by the anti-digoxin

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antibody on test line 1 or the anti-FITC antibody on test line 2. Two visual bands

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appeared in the test zone because the immunoreaction led to increased AuMBA@Ag.

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Excess AuMBA@Ag- streptavidin complex continued to migrate and was then captured

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by the mouse anti-streptavidin monoclonal antibody on the control line, which was

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used as a control to determine whether the LF strip worked properly. Regardless of the

digoxin-duplex

DNA-biotin-streptavidin-AuMBA@Ag

or

FITC-duplex

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presence of target bacteria, the control line always appeared. In the presence of S.

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Enteritidis and L. monocytogenes, two visible orange-yellow lines in the test zone

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appeared (Fig. 3A). If only S. Enteritidis or L. monocytogenes is present in the sample,

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one orange-yellow line forms (Fig. 3B). Moreover, the addition of various

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concentrations of RPA products could result in corresponding amounts of AuMBA@Ag

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captured by the test line. Consequently, the Raman intensity of MBA can be expressed

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as different concentrations of RPA product, proportional to the concentration of target

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DNA.4,35 Therefore, it is possible to achieve a quantitative result by measuring the

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characteristic SERS peak intensities of the test lines.24

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Raman active AuMBA@Ag nanoparticles were used in the SERS-based LF strip,

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and the Raman enhancement effect of Au@Ag colloids is stronger than that for pure

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Au or Ag.28 MBA absorbed on Au serves as a SERS donor, and the Raman signal of

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MBA was intensified due to the formation of SERS “hot spots” in the gap between Au

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and Ag. Therefore, Au@Ag greatly enhanced the sensitivity of the LF-SERS assay.

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Uniform Au@Ag NPs were synthesized by a two-step reaction. The AuNP colloid

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was first prepared, and ascorbic acid reduced silver nitrate to Ag metal. Because of the

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similarity of the crystalline lattice between Au and Ag, the Ag shell continuously

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adhere to the surface of Au core. Core-shell Au@Ag with an obvious color change

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from the wine red of AuNPs to orange-yellow was synthesized and characterized by

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TEM and UV-vis (Fig. 2). Au@Ag NPs with 8.48-nm silver shells are highly

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monodisperse and possess two plasmon resonance frequencies of Au and Ag (Fig. 2A

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red line). Au@Ag with 8.48-nm silver shells has a wide, strong plasmon resonance 17

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that is responsible for the maximum Raman enhancement effect. With an increased Ag

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shell thickness of 10 nm (Fig. 2D), the plasmon resonance of the Au core decreased

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and the two resonances merged into a single peak at a wavelength similar to that for

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the AgNPs (Fig. 2A blue line).

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Numerous methods have been established to detect pathogenic bacteria in food

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samples, such as the use of electrochemical immunosensors,10 immunomagnetic

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separation38 and surface plasmon resonance.37-40 However, these methods employ

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complicated operations, requiring time-consuming procedures that severely limit their

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suitability for point-of-use detection. DNA amplification methods such as PCR can

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amplify trace DNA to detectable levels.13 Although PCR is regarded as a sensitive and

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specific method for the detection of pathogenic bacteria, it requires specialized

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thermal

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technicians.40 A number of isothermal amplification methods have been developed to

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eliminate the use of thermal cycling equipment, including helicase-dependent

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amplification, rolling circle amplification and loop-mediated isothermal amplification.

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Among these methods, RPA shows significant advantages such as a short incubation

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time, lower and single incubation temperatures (35°C–45°C) and high tolerance to

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sample impurities. However, the established methods combined with RPA have

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mostly been used in the detection of a single target. In this study, we exploit the

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potency of RPA for the simultaneous amplification of multiple DNA of pathogenic

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bacteria. According to our study, RPA can successfully amplify S. Enteritidis and L.

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monocytogenes DNA in one tube to detectable levels, decreasing sample consumption,

cycling

equipment,

complicated

sample

pretreatment

and

trained

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reducing the cost per assay and improving throughput of detection. To the best of our

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knowledge, this is the first time that simultaneous detection of S. Enteritidis and L.

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monocytogenes has given a quantification result.

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The RPA-LF-SERS strip was developed for the highly sensitive and quantitative

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detection of pathogenic bacteria. This assay can simultaneously detect as few as

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1.9101 CFU/mL of L. monocytogenes or 2.7 101 CFU/mL of S. Enteritidis with

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Raman intensity of 1362.2 and 1857.5, which is at least 2-fold higher than (S/N>2)

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the average SERS signal for negative control with SERS signal intensity of 549

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calculated at 1077 cm-1. This detection limit is equivalent to that of LAMP-SERS for

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the quantification detection of S. Enteritidis,4 lower than that of a flow colloidal gold

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immunoassay strip for simultaneous detection of Shigella boydii and Escherichia

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coli,41 and lower than that of multiplexed RPA for the detection of protozoa.13 This

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high detection sensitivity can be attributed to the high amplification efficiency of RPA,

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the Raman enhancement of Au@Ag and the single-molecule level of SERS detection.

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According to the SEM (SEM, JEOL-IT300, Akishima, Japan) image of the positive

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result on the test line (Fig. 8B), AuMBA@Ag clusters in the fiber pores created many

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interparticle gaps and produced a strong SERS signal.42 Furthermore, the detection

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limit of LF with two test lines was almost the same as that of the LF with only one

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test line (Fig. S4), demonstrating that the sensitivity of RPA-LF was not affected by

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the addition of the second test line. In addition, quantitative analysis could be obtained

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by measuring the SERS signal intensity at 1077 cm-1. In the absence of target bacteria,

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immunocomplexes did not appear on the test line (Fig. 8A), and the SERS intensity 19

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was extraordinarily weak. However, in the presence of target

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immunocomplexes captured by the test line produced strong SERS signals.

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bacteria,

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The RPA-LF-SERS biosensor is suitable for point-of-use detection by the naked

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eye since the entire detection result could be obtained within 30 min. Furthermore,

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quantitative analysis was achieved by detection of the SERS intensity of the test lines.

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Although this additional SERS analysis leads to slightly greater complexity compared

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to the naked eye-based LF strip and requires more operation time, SERS detection

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improved the detection sensitivity, eliminated the enrichment step and gave

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quantifiable results.

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AUTHOR INFORMATION

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Corresponding Author

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E-mail: [email protected] (S. Wang); Phone: +86 22 60912484; Fax: +86 22

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60912484

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Funding

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This work was supported by The National Key Research and Development Program

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of China (2017YFD0400704), Ministry of Science and Technology of the People’s

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Republic of China (Project No. 2014BAD04B03), and The Excellent Doctoral Fund

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Project (No. 2016003).

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Notes

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The authors declare no competing financial interest.

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ABBREVIATIONS USED

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SERS, surface-enhanced Raman scattering; LF, lateral flow; RPA, recombinase 20

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polymerase amplification; TL, test line; RT-PCR, real-time polymerase chain reaction;

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ELISAS, enzyme-linked immunosorbent assays; DNA, deoxyribonucleic acid; MBA,

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4-mercaptobenzoic acid; FITC, fluorescein isothiocyanate; AgNO3, sliver nitrate; PBS,

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phosphate-buffered saline; PEG, polyethylene glycol; BSA, bovine serum albumin;

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mAb, monoclonal antibody; K2CO3, potassium carbonate; CFU, colony-forming unit;

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LB broth, luria bertani broth; AGE, agarose gel electrophoresis; RSD, relative

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standard deviation

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B. Nanoscale 2016, 8, 11418-11425.

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28 . Wang, X.; Choi, N.; Cheng, Z.; Ko, J.; Chen, L.; Choo, J., Simultaneous

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Detection of Dual Nucleic Acids Using a SERS-Based Lateral Flow Assay

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Biosensor. Anal. Chem. 2016, 89, 1163-1169.

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29. Liu, B.; Han, G.; Zhang, Z.; Liu, R.; Jiang, C.; Wang, S.; Han, M.-Y., Shell

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Thickness-Dependent Raman Enhancement for Rapid Identification and Detection of

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Pesticide Residues at Fruit Peels. Anal. Chem. 2012, 84, 255-261.

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30. Karn-orachai, K.; Sakamoto, K.; Laocharoensuk, R.; Bamrungsap, S.; Dharakul,

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T.; Miki, K., SERS-based immunoassay on 2D-arrays of Au@ Ag core–shell

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nanoparticles: influence of the sizes of the SERS probe and sandwich

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immunocomplex on the sensitivity. RSC Adva. 2017, 7, 14099-14106. 25

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31. Yang, L.; Li, Y., Simultaneous detection of Escherichia coli O157∶ H7 and

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Salmonella Typhimurium using quantum dots as fluorescence labels. Analyst

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2006, 131, 394-401.

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32. Toubanaki, D. K.; Christopoulos, T. K.; Ioannou, P. C.; Flordellis, C. S.,

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Identification of Single-Nucleotide Polymorphisms by the Oligonucleotide Ligation

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Reaction: A DNA Biosensor for Simultaneous Visual Detection of Both Alleles. Anal.

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Chem. 2009, 81, 218-224.

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33. Low, S. C.; Shaimi, R.; Thandaithabany, Y.; Lim, J. K.; Ahmad, A. L.; Ismail, A.,

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Electrophoretic interactions between nitrocellulose membranes and proteins:

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Biointerface analysis and protein adhesion properties. Colloid. Surface. B. 2013, 110,

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248-253.

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34. Lai, Y. H.; Koo, S.; Oh, S. H.; Driskell, E. A.; Driskell, J. D., Rapid screening of

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antibody-antigen binding using dynamic light scattering (DLS) and gold nanoparticles.

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Anal. Methods 2015, 7, 7249-7255.

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35. de la Escosura‐Muñiz, A.; Baptista‐Pires, L.; Serrano, L.; Altet, L.; Francino, O.;

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Sánchez, A.; Merkoçi, A., Magnetic Bead/Gold Nanoparticle Double‐Labeled Primers

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for Electrochemical Detection of Isothermal Amplified Leishmania DNA. Small 2016,

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12, 205-213.

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36. Pandey, A.; Gurbuz, Y.; Ozguz, V.; Niazi, J. H.; Qureshi, A., Graphene-interfaced

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electrical biosensor for label-free and sensitive detection of foodborne pathogenic E.

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coli O157:H7. Biosens.Bioelectron. 2017, 91, 225-231.

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37. Suaifan, G. A. R. Y.; Alhogail, S.; Zourob, M., Paper-based magnetic 26

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nanoparticle-peptide probe for rapid and quantitative colorimetric detection of

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Escherichia coli O157:H7. Biosens. Bioelectron. 2017, 92, 702-708.

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38. Yang, X.; Zhou, X.; Zhu, M.; Xing, D., Sensitive detection of Listeria

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monocytogenes based on highly efficient enrichment with vancomycin-conjugated

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brush-like magnetic nano-platforms. Biosens. Bioelectron. 2017, 91, 238-245.

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39. Vaisocherová-Lísalová, H.; Víšová, I.; Ermini, M. L.; Špringer, T.; Song, X. C.;

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Mrázek, J.; Lamačová, J.; Lynn, N. S.; Šedivák, P.; Homola, J., Low-fouling surface

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plasmon resonance biosensor for multi-step detection of foodborne bacterial

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pathogens in complex food samples. Biosens. Bioelectron. 2016, 80, 84-90.

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40. Eriksson, E.; Aspan, A., Comparison of culture, ELISA and PCR techniques for

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salmonella detection in faecal samples for cattle, pig and poultry. BMC Vet. Res. 2007,

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3, 21-21.

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41. Song, C. M.; Liu, C.; Wu, S. Y.; Li, H. L.; Guo, H. Q.; Yang, B.; Qiu, S.; Li, J. W.;

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Liu, L.; Zeng, H. J.; Zhai, X. Z.; Liu, Q., Development of a lateral flow colloidal gold

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immunoassay strip for the simultaneous detection of Shigella boydii and Escherichia

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coli O157:H7 in bread, milk and jelly samples. Food Control 2016, 59, 345-351.

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42. Sun, Y.; Han, Z.; Liu, H.; He, S.; Yang, L.; Liu, J., Three-dimensional hotspots in

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evaporating nanoparticle sols for ultrahigh Raman scattering: solid-liquid interface

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effects. Nanoscale 2015, 7, 6619-6626.

588

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FIGURE CAPTIONS

590

Figure 1. Schematic illustration of the preparation of AuMBA@Ag-streptavidin (A)

591

and the multiplex RPA-LF-SERS assay (B)

592

Figure 2. UV-vis (A) and TEM of Au@Ag with different Ag shell thicknesses of 0

593

nm (B), 8.48 nm (C), and 10 nm (D)

594

Figure 3. (A) Sensitivity results of multiplex lateral flow strips for the detection of S.

595

Enteritidis (test line 1) and L. monocytogenes (test line 2). Test lines could be

596

observed by the naked eye at a concentration of 1.9102 CFU/mL of L.

597

monocytogenes and 2.7102 CFU/mL of S. Enteritidis. The SERS signal of the test

598

lines could be obtained at a concentration of 1.9101 CFU/mL of L. monocytogenes

599

and 2.7101 CFU/mL of S. Enteritidis; Molecular specificity of the RPA-LF assay for

600

three L. monocytogenes, three S. Enteritidis bacteria (B) and nine other bacteria (C). 1:

601

Salmonella paratyphi-A, 2: Salmonella cholerae-suis var. kunzendorf, 3: Escherichia

602

coli O157:H7, 4: Shigella flexneri, 5: Escherichia coli, 6: Staphylococcus aureus, 7:

603

Shigella sonnei, 8: Enterobacter aerogenes and 9: Campylobacter jejuni subsp. jejuni.

604

Figure 4. Raman spectra from MBA on test line 1 (A for detection of S. Enteritidis)

605

and test line 2 (B for detection of L. monocytogenes) with RPA products of different

606

concentrations of S. Enteritidis and L. monocytogenes. The SERS peak intensity

607

centered at 1077 cm-1 was used for quantitative analysis of S. Enteritidis and L.

608

monocytogenes. The bacterial concentration of L. monocytogenes and S. Enteritidis

609

ranged from 1.9100 CFU/mL to 1.9106 CFU/mL and from 2.7100 CFU/mL to

610

2.7106 CFU/mL, respectively. 28

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611

Figure 5. Standard curve of Raman intensity on a SERS-based lateral flow strip for

612

the detection of S. Enteritidis (■) and L. monocytogenes (•) Error bars indicate

613

standard deviations calculated from three parallel measurements.

614

Figure 6. Detection of different concentrations of S. Enteritidis and L. monocytogenes

615

in simulated food samples using a multiplex lateral flow strip: 1, 2, 3 and 4 represent

616

milk inoculated with 7.6104 CFU/mL, 8.2103 CFU/mL, 9.8102 CFU/mL and

617

3.1101 CFU/mL of S. Enteritidis and 8.5104 CFU/mL, 6.9103 CFU/mL, 5.6102

618

CFU/mL and 3.6101 CFU/mL of L. monocytogenes; 1, 2, 3 and 4 represent chicken

619

breast inoculated with 1.9105 CFU/mL, 1.49104 CFU/mL, 8.5102 CFU/mL and

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3.5101 CFU/mL of S. Enteritidis and 9.2104 CFU/mL, 1.5104 CFU/mL, 7.3102

621

CFU/mL and 2.9101 CFU/mL of L. monocytogenes; 1, 2, 3 and 4 represent beef

622

inoculated with 1.2105 CFU/mL, 1.3104 CFU/mL, 2103 CFU/mL and 3.5101

623

CFU/mL of S. Enteritidis and 1.6105 CFU/mL, 8.6103 CFU/mL, 1103 CFU/mL

624

and 2.2102 CFU/mL of L. monocytogenes; NC represents the negative control.

625

Figure 7. SERS intensities of MBA at 1077 cm-1 from 10 different spots in the middle

626

of test line 1 (A, for detection of S. Enteritidis) and middle of test line 2 (B, for

627

detection of L. monocytogenes)

628

Figure 8. SEM images of SERS-based lateral flow strips in the absence (A) and

629

presence (B) of target bacteria.

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Figure S1. Electrophoresis images of primers specific for S. Enteritidis and L.

631

monocytogenes using four of S. Enteritidis (A S1-S4), four of L. monocytogenes (A

632

L1-L4) and nine of other bacteria. Lane M: 2000 bp DNA ladder, NC: negative 29

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control (without DNA template), lane S1: Salmonella enteritidis, lane S2: Salmonella

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enterica subsp. enterica, lane S3: Salmonella Enteritidis ATCC13076, lane S4:

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Salmonella enteritidis 160609; B: lane L: L. monocytogenes, lane S: Salmonella

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enteritidis, lane 1: Salmonella paratyphi-A, lane 2: Salmonella cholerae-suis var.

637

kunzendorf, lane 3: Escherichia coli O157:H7, lane 4: Shigella flexneri, lane 5:

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Escherichia coli, lane 6: Staphylococcus aureus, lane 7: Shigella sonnei, lane 8:

639

Enterobacter aerogenes, lane 9: Campylobacter jejuni subsp. jejuni.

640

Figure S2. Optimization the type of NC membrane (A) and the type of running buffer

641

(B). A: 1: HF90, 2: HF135, 3: HF180; B: 1: PBS (pH=7.4), 2: PBS (pH=5.7), 3: PBS

642

(pH=8.5), 4: PBS with 0.05%Tween 20, 5: Tris-HCl buffer (pH=7.4)

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Figure S3. Sensitivity of RPA-AGE for simultaneous detection of S. Enteritidis and L.

644

monocytogenes. Lane M: D2000 DNA ladder marker; lane 1: 2.7 × 106 CFU/mL of S.

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Enteritidis and 1.9 × 106 CFU/mL of L. monocytogenes; lane 2: 2.7 × 105 CFU/mL of

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S. Enteritidis and 1.9 × 105 CFU/mL of L. monocytogenes; lane 3: 2.7 × 104 CFU/mL

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of S. Enteritidis and 1.9 × 104 CFU/mL of L. monocytogenes; lane 4: 2.7 × 103

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CFU/mL of S. Enteritidis and 1.9 × 103 CFU/mL of L. monocytogenes; lane 5: 2.7 ×

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102 CFU/mL of S. Enteritidis and 1.9 × 102 CFU/mL of L. monocytogenes; lane N:

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negative control (without DNA template). L. monocytogenes and S. Enteritidis

651

produced two visual bands at 180 bp and 267 bp, respectively.

652

Figure S4. Sensitivity results of RPA-LF for the detection of L. monocytogenes (A)

653

and S. Enteritidis (B). L. monocytogenes and S. Enteritidis concentrations ranged from

654

2.7 × 106 CFU/mL to 2.7 × 100 CFU/mL and 1.9 × 106 CFU/mL to 1.9 × 100 CFU/mL, 30

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respectively.

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Table 1 Primers of multiplex recombinase polymerase amplification used in this study Target

Primer name

Sequence (5’-3’)

Forward primer

GCATCCGCACAGATAAAT-Digoxin

Reverse primer

TACACCACCAGATACCGAAGCCCCT-Biotin

Forward primer

GTAAGTGGGAAATCTGTCTCAGGTGATGTAG-FITC

Reverse primer

ACTCCTGGTGTTTCTCGATTAAAAGTAGCA-Biotin

S. enteritidis

L. monocytogenes

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Table 2 Bacterial strains used in our study Species

Source

Listeria monocytogenes

CICC21633

Listeria monocytogenes

ATCC19115

Listeria monocytogenes

ATCC7644

Listeria monocytogenes

ATCC19111

Salmonella enteritidis

CMCC50041

Salmonella enterica subsp. enterica

CICC10982

Salmonella enteritidis

ATCC13076

Salmonella enteritidis

160609

Salmonella paratyphi-A

CICC21501

Salmonella cholerae-suis var. kunzendorf

CICC21494

Escherichia coli O157:H7

ATCC35150

Shigella flexneri

CICC10865

Escherichia coli

CICC10305

Staphylococcus aureus

ATCC25923

Shigella sonnei

CICC21535

Enterobacter aerogenes

CICC10293

Campylobacter jejuni subsp. jejuni

ATCC33560

33

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Table 3 The recoveries of S. Enteritidis and L. monocytgenes in selected food samples by SERS-LF Sample

Milk

Chicken breast

beef

S. Enteritidis concentration in spiked samples

Recovery

L. monocytegenes concentration Recovery

(CFU/mL)

(%, n=3)

in spiked samples (CFU/mL)

(%, n=3)

7.6104

91.34

8.5104

105.63

8.2103

90.46

6.9103

107.68

9.8102

109.90

5.6102

113.86

3.1101

95.63

3.6101

103.55

1.9105

106.16

9.2104

104.44

1.49104

91.76

1.5104

96.80

8.5102

92.76

7.3102

94.65

3.5101

93.27

2.9101

95.30

1.2105

104.09

1.6105

100.94

1.3104

96.78

8.6103

103.83

34

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2103

105.57

1103

97.21

3.5101

95.27

2.2101

96.21

35

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