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1. Multiplexed Detection of Foodborne Pathogens from. 1. Contaminated Lettuces Using a Handheld Multistep. 2. Lateral Flow Assay Device. 3. Joong Ho S...
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Multiplexed Detection of Foodborne Pathogens from Contaminated Lettuces Using a Handheld Multistep Lateral Flow Assay Device Joong Ho Shin, Jisoo Hong, Hyeyun Go, Juhwan Park, Minsuk Kong, Sangryeol Ryu, Kwangpyo Kim, Eunjung Roh, and Je-Kyun Park J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b03582 • Publication Date (Web): 02 Dec 2017 Downloaded from http://pubs.acs.org on December 4, 2017

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Journal of Agricultural and Food Chemistry is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

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Journal of Agricultural and Food Chemistry

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Multiplexed Detection of Foodborne Pathogens from

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Contaminated Lettuces Using a Handheld Multistep

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Lateral Flow Assay Device

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Joong Ho Shin,†,⊥ Jisoo Hong,‡, ⊥ Hyeyun Go,† Juhwan Park,† Minsuk Kong,§ Sangryeol Ryu,§

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Kwang-Pyo Kim,ǁ Eunjung Roh*,‡ and Je-Kyun Park*,†

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Technology (KAIST), Daejeon 34141, Republic of Korea

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Department of Bio and Brain Engineering, Korea Advanced Institute of Science and

Microbial Safety Team, National Institute of Agricultural Sciences, Rural Development

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Administration, Wanju-gun 55365, Republic of Korea

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§

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of Korea

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ǁ

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Republic of Korea

Department of Agricultural Biotechnology, Seoul National University, Seoul 08826, Republic

Department of Food Science and Technology, Chonbuk National University, Jeonju 54896,

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Corresponding Authors:

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*Fax: +82-63-238-3840. Phone: +82-63-238-3406. E-mail: [email protected] (E.R).

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*Fax: +82-42-350-4310. Phone: +82-42-350-4315. E-mail: [email protected] (J.-K.P).

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ABSTRACT: This paper presents a handheld device that is capable of simplifying multistep

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assays to perform sensitive detection of foodborne pathogens. The device is capable of

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multiplexed detection of Escherichia coli (E. coli) O157:H7, Salmonella typhimurium (S.

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typhimurium), Staphylococcus aureus and Bacillus cereus. The limit of detection for each

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bacterium was characterized and then the detection of bacteria from contaminated fresh lettuces

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was demonstrated for two representative foodborne pathogens. We employed a sample

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pretreatment protocol to recover and concentrate target bacteria from contaminated lettuces,

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which can detect 1.87 × 104 CFU of E. coli O157:H7 and 1.47 × 104 CFU of S. typhimurium per

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gram of lettuce without an enrichment process. Lastly, we demonstrated that the limit of

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detection can be reduced to 1 CFU of E. coli O157:H7 and 1 CFU of S. typhimurium per gram of

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lettuce by including a 6-h enrichment of contaminated lettuces in growth media before

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pretreatment.

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Keywords: contaminated lettuces; foodborne pathogens; handheld device; lateral flow assay;

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multiplexed detection

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INTRODUCTION

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Foodborne illness is a serious problem that causes a number of problems such as nausea,

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diarrhea, hospitalization and even death. In the United States, estimates of more than 9 million

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foodborne illnesses are reported each year.1 Although it is known that the use of proper heat in

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meat and poultry cooking prevents infection, such a heating process is skipped if fresh products

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such as fruits and vegetables are to be consumed fresh. With the increased consumption of fresh

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products for the prevention of chronic diseases, the number of foodborne outbreaks from the

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consumption of fresh products has also increased.2,3 Furthermore, globalization and increasing

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trade, along with a faster distribution of food products also increase the risk of outbreaks.4 Thus,

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a rapid detection process needs to be developed that can be applied to the food industry in order

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to prevent future outbreaks.

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The current detection method for fresh products, which is considered as “gold standard,” is a

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culture-based method.5,6 The method requires a series of processes that involves stomaching,

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enrichment, bacteria culture, and identification of target bacteria. First, to remove bacteria

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present on the surface of and also deep within the food sample, the sample is put in a sterile

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plastic bag with bacteria growth medium and put into a stomacher machine. The machine

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vigorously pounds the outer surface of the plastic bag, repeatedly and violently compressing and

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shearing the food sample.7 Then the extracts are collected into sterile tubes and are put in a 37 °C

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incubator over a long period of time, usually between 18 and 24 h to enrich and increase the

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number of bacteria. This process usually ends up containing non-target bacteria and it is

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impossible to identify the presence of target bacteria in this state. The enriched sample is then

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streaked and incubated for another 24 h on an agar plate for colony analysis. Then, a colony has

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to be isolated to ensure purity and an additional incubation is required. The purified colonies can

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be identified visually in this state, however, a combination of assays such as agglutination assay,

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additional culture on special media, enzyme/biochemical tests and target-specific selective gram

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staining are required to confirm the identity of the colony. This whole process is labor intensive,

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requires proper lab equipment and takes several days (3–5 days) for the analysis result.

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Many methods of rapid detection have been attempted as an alternative to the time consuming

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culture-based method. Some of the methods include the use of enzyme-linked immunosorbent

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assay (ELISA), polymerase chain reaction (PCR),8 bioluminescence signal,9 flow cytometry,10

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and latex bead agglutination test.11 ELISA is reported to detect bacteria in the order of 104

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colony-forming unit (CFU) per mL,12 and PCR provides highly sensitive and highly specific

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detection results due to the amplification of the target fragment. Although both ELISA and PCR

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can provide sensitive detection results, they are both complicated, require a trained technician, as

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well as expensive and bulky equipment, which hinders them from being applied for on-site

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detection. For on-site analysis purposes, a lateral flow test (LFT) is one of the most promising

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methods due to its convenience, quick readout (10–20 min),13 and the signal that can be

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interpreted with the naked eye. The operation starts by loading a liquid sample into the sample

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pad. The sample flows forward and rehydrates pre-dried labeling agents and forms

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immunocomplexes. The immunocomplexes continue to flow through the strip by capillary force,

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and they are captured by antibodies on the test line. The flow is sustained by the absorbent pad

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and the result appears as a visible line with the naked eye. LFT kits for various pathogens exist

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on the market today, but there is still room for improvement in terms of the limit of detection.

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One way to simplify and improve the detection limit of LFT is to add an additional reagent

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loading step and perform a multistep assay on LFT. By increasing the size of the gold

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nanoparticles (AuNPs) as signaling probes with enhancers after completion of an assay, the

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signal intensity can be increased and a 100-fold improvement of the detection limit was

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demonstrated.14−16 Enzyme-linked immunoreactions were also performed on LFTs by first

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applying a sample flow along the length of the strip and then flowing a substrate across the width

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of the strip for enzyme-substrate-based signal generation.17,18 The processes however require

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manual reconfiguration of multiple pads and wait for the primary reaction to finish before

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performing a secondary reaction. Although such requirements are not suitable for on-site

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detection purposes, the multistep assays have demonstrated sensitive analyte detection, and in

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order to simplify the assay process, customized packaging technologies are being developed to

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perform the sequential tasks with ease.19−21

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With the recent advancement in paper-based fluidics and by utilizing fluid delay phenomena,

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an engineered paper network with multiple channels of different fluidic path lengths was

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developed.22,23 Fluids travel longer time in the longer channel, thus arrives at the test zone much

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later as compared to fluids that flow through shorter channel. The device exploits this

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mechanism to perform the sequential flow of samples, buffers and enhancing solution to increase

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the sensitivity of an assay. However, such a format requires up to 1 h due to the fluidic resistance

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that increases with increasing channel length; and the use of single wicking pad, whose

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absorption rate saturates over time.24

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Our group recently developed a rotary type device that offers solution to the abovementioned

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problem. It was used to simplify the process required for ELISA on LFT and was able to detect

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Escherichia coli (E. coli) O157:H7 in 22 min.25 In this paper, we modified the design of the

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handheld device and expanded the number of test strips for multiplexed detection. In order to

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reduce and simplify the assay steps, we utilized AuNP and enhancer instead of enzyme-substrate

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pair for colorimetric signal. The device consists of four test lines that indicate the presence of E.

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coli O157:H7, Staphylococcus aureus (S. aureus), Salmonella typhimurium (S. typhimurium) and

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Bacillus cereus (B. cereus), thereby allowing multiplexed detection. We used the device to detect

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bacteria from contaminated lettuce, and then demonstrated increased detection sensitivity by

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incorporating a bacteria enrichment step.

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MATERIALS AND METHODS

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Design and Fabrication. The proposed device is designed to simplify the complicated and

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laborious multistep assays while simultaneously detecting up to four pathogenic bacteria with

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high sensitivity. As shown in Figure 1A, it is equipped with two test strips: the left strip is used

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to detect E. coli O157:H7 (ATCC 35150) and S. aureus (ATCC 25923); the right strip is used to

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detect S. typhimurium (ATCC 14028) and B. cereus (ATCC 10987). EC, SA, ST and BC stands

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for E. coli, S. aureus, S. typhimurium and B. cereus, respectively. The device consists of a

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stationary part (bottom piece) and a rotating part (top piece). Sample pads (S1–S3) and their

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corresponding absorbent pads are contained in the top piece and nitrocellulose (NC) test strip is

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contained in the bottom piece. S21 contains a mixture of AuNPs that label E. coli O157 and S.

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aureus antibodies, while S22 contains a mixture of AuNPs that label S. typhimurium, as well as

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AuNPs for B. cereus.

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A patterned OHP transparency film, which has through-holes, is attached to the bottom of the

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top piece (Figure 1B). This enables a direct contact between the sample pad and the test strip as

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well as between the test strip and the absorbent pad. The top and bottom pieces were made of 3

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mm-thick poly(methyl methacrylate) (PMMA) plates, which were patterned and etched with a

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laser cutter (C40-60W; Coryart, Anyang, Korea). The diameter of the handheld device was 8 cm.

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The through-holes were patterned on the OHP film with a laser cutter, and then adhered to the

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top piece with a double-sided tape.

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1 mg/ml anti-S. aureus antibody (ab20002; Abcam) and 1 mg/ml anti-E. coli O157 antibody

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(ab20976; Abcam) was immobilized parallel to each other on 15 µm pore NC strip as two test

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lines (SA, EC), respectively, and 1 mg/ml anti-mouse IgG antibody (M4155; Sigma Aldrich,

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MO, USA) was dispensed as a control line (CL 1) for the left strip. After the antibodies were

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dried, the NC strip was cut into 4 × 25 mm strips. 10 µL blocking buffer (2% skim milk and 0.15

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% Tween-20 in phosphate buffered saline (PBS)) was dropped on the center of each strip and

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dried at room temperature. This strip was used as a left strip for S. aureus and E. coli O157:H7

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detection. A cell wall binding domain (CBD) of an endolysins produced by a B. cereus phage

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was prepared for B. cereus detection as previously described.26 1 mg/ml anti-S. typhimurium

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antibody (ab8274; Abcam) and 1.5 mg/ml CBD against B. cereus were immobilized on 15 µm

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pore NC strip as two test lines (ST, BC) for the right strip, respectively. CBD was diluted with

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PBS containing 5% BSA (Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA) prior to

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immobilization to minimize the nonspecific signal and increase the detection signal-to-noise

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ratio.27 1 mg/ml anti-mouse IgG antibody were dispensed as the first control line (CL 1) and 1

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mg/ml anti-glutathione-S-transferase (GST) antibody (A190-122A; Bethyl) was dispensed as the

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second control line (CL 2).

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Gold Nanoparticle Preparation. AuNPs for the labeling of E. coli O157:H7, S. aureus and S.

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typhmurium are conjugated with antibodies. For the AuNP-antibody conjugation, the pH of the

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AuNP (20 nm diameter) solution was adjusted to 9 by adding 3 µL of K2CO3 (0.2 M) per 150 µL

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of AuNP (753610; Sigma-Aldrich). The stock concentration (1×) was 6.54 × 1011 particles/ml.

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Then, 1 µg antibody per 150 µL was added to the AuNP and incubated at room temperature for

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20 min. Thereafter, to block the surfaces of antibody conjugated AuNPs, 100 µL of PBS

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containing 3% BSA was added and incubated for 20 min. The AuNP was then centrifuged at

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7,000 × g for 30 min to remove unbound antibodies. The supernatant was removed and the

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AuNP was resuspended in a PBS solution containing 3% BSA and 0.05% Tween-20.

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AuNPs for the labeling of B. cereus are conjugated with CBD proteins. For the AuNP-CBD

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conjugation, 1 M Tris-Cl buffer (pH 9.0) was added to 1 mL of an AuNP (20 nm diameter)

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solution suspended in citrate buffer (741965; Sigma-Adrich). 5 µL of Cys-GST-tagged CBD

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protein solution was added to the AuNP solution and incubated for 1 h at room temperature. To

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block the surfaces of the CBD-conjugated AuNP, 100 µL of 2 mM PEG (dissolved in 10 mM

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Tris-Cl, pH 9) (SunBio, Anyang, Korea) was added and incubated for 1 h at room temperature.

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The solution was then centrifuged at 8,000 × g for 30 min to remove unbound proteins. The

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supernatant was removed and the AuNP pellet was resuspended in a PBS solution containing 3%

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BSA and 0.05% Tween-20.

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Device Operation. Prior to starting the detection process, 40 µL AuNP mixtures were loaded

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into their respective AuNP pads: AuNP-E. coli O157 antibody mixed with AuNP-S. aureus

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antibody was loaded into S21 and AuNP-S. typhimurium antibody mixed with AuNP-CBD is

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loaded into S22. Then, 80 µL enhancer was loaded into S3. To begin the assay, 260 µL of

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bacteria sample suspended in 2% BSA containing PBS was loaded into S1. As shown in the

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scheme in Figure 1C, the assay first requires delivery of the sample to the NC strip for the

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bacteria capture step. After 10 min of sample flow, the top piece was rotated counterclockwise to

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deliver AuNPs to label the captured bacteria. After 6 min of AuNP labeling, an enhancer solution

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(GoldEnhance EM; Nanoprobes, Yaphank, NY, USA) was delivered to amplify the AuNP signal

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intensity. The gold enhancer solution consists of an enhancer, activator, initiator, and buffer,

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which are mixed prior to use. As mentioned in previous publications,28,29 the gold enhancer has

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the ability to decrease the limit of detection and help distinguish unclear signals, which can

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prevent false negative detection results. After 3 min of enhancement, the top layer was detached

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from the device and pictures of the test lines were taken and analyzed. The sequential delivery

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for the aforementioned multistep assay was easily performed simply by incrementally rotating

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the top piece of the device with the hands.

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Detection of Bacteria from Contaminated Lettuce. To determine whether the developed

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device can be applied for bacteria detection from contaminated fresh vegetables samples, fresh

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lettuces were inoculated with different amounts of E. coli O157:H7 and S. typhimurium. Bacteria

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were grown in tryptic soy broth (TSB) (BD Difco, Sparks, MD, USA), centrifuged at 3,000 × g

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for 20 min and resuspended in PBS, then diluted to the target inoculation number by measuring

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the optical density (OD) of the bacteria suspension. The target inoculation amounts were 104,

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105, 106 CFU per 10 g of lettuce. However, it is technically difficult to measure the exact target

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CFU of the bacteria sample and dilute it to the exact target concentrations based on the OD

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measurement alone, a portion of the diluted samples were dotted (10 µL of samples were spotted

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on the agar plate after further log-dilution) on agar plate. The actual number of inoculated

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bacteria was calculated by counting the number of bacteria from the agar plate the next day when

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the colonies were visible. 100 µL of the diluted bacteria solutions were dropped on different

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spots of the lettuces, which were then dried for 5 min, and put into a plastic bag. 90 mL of PBS

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were poured into each plastic bag, and then the bags were put into a stomacher machine

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(BagMixer 400; Interscience, Saint Nom, France) for 1 min to homogenize the solution and

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retrieve the bacteria from the lettuce. The solution from each bag was poured into two 50 mL

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tubes and centrifuged at 3,000 × g for 20 min. The supernatants were decanted and the sample

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were resuspended in 150 µL PBS. From the suspension, 10 µL was log-diluted and dotted on

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agar plate to measure the retrieved number of bacteria, which was counted the next day. From

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the remaining solution, 130 µL was taken and diluted to a final volume of 260 µL sample

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containing 2% BSA in PBS, which was loaded into the device for detection.

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Bacteria Enrichment. Fewer number of bacteria (in the order of 101, 102, 103 CFU per 10 g of

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lettuce) were inoculated on the lettuce. After the contaminated lettuces were put in the bag, 90

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mL growth media were poured into the bag instead of pouring PBS. The bag was then incubated

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in an incubator at 37 °C for 6 h. After enrichment, the sample was put into a stomacher machine,

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centrifuged and concentrated as described previously.

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RESULTS AND DISCUSSION

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Optimization of Gold Nanoparticle Concentration and Duration. The concentration of

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AuNP-Ab used to label the captured bacteria is related to the total amount of AuNP and antibody

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used, which is directly related to the total cost of an assay. Moreover, the duration of AuNP flow

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is related to the total time required to perform each assay so that both the duration of AuNP flow

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and the concentration of AuNP need to be optimized in order to reduce the total cost and time.

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Antigen–antibody binding is a reversible interaction with the association and dissociation of

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antigen–antibody complexes. The total number of antigen–antibody complex, which determines

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the signal intensity, depends on both the concentration of bacteria and the concentration of

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AuNP. Theoretically, using a higher concentration of AuNP would result in a stronger signal.

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However, to develop an economically efficient rapid detection system, the device was optimized

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to use the lowest AuNP concentration that allows the signal to appear at the lowest bacteria

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concentration as possible.

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The test line’s intensity using several concentrations of AuNP were screened by captured S.

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typhimurium (107 CFU/mL flowed for 10 min). The concentrations of antibody-conjugated

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AuNP were 2×, 1×, 0.50×, and 0.25× with 1× being 6.54 × 1011 particles/mL. As shown in

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Figure 2A, the intensity of detection signal increases over time, and the detection signal

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generated with a higher concentration of AuNPs saturates at a higher intensity (Figure 2B).

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According to the graph, the use of 2× AuNP and the flow duration for 14 min would result in a

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highest signal intensity. Before reducing the AuNP concentration and the flow duration, the limit

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of detection of S. typhimurium with 2× AuNP and 14 min flow duration was determined to be

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105 CFU/mL with an enhancement step (Figure S1 of the Supporting Information). Thus,

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additional experiments were performed to reduce the AuNP concentration and the flow duration

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while maintaining the limit of detection.

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To find an optimum condition, the AuNP flow duration was varied with a fixed AuNP

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concentration (2×). 6, 10, and 14 min of AuNP flow durations were tested and the pictures show

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that 6 min is sufficient to generate a detection signal of 105 CFU/mL S. typhimurium (Figure 2C).

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Although the intensity of the detection signal is stronger after flowing for 10 min, a prolonged

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AuNP flow is not necessary to generate a visible signal. It is interesting to note that the flowing

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for 14 min results in a reduced signal intensity. The reason behind the decreased signal intensity

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is unclear. It is assumed that a long duration causes dissociation of bacteria from the capture

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antibodies, thereby resulting in a reduction in the total number of captured bacteria, which would

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also reduce the signal intensity.

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Lastly, the AuNP flow duration was fixed at 6 min while the AuNP concentration was varied.

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The detection signals of 105 CFU/mL S. typhimurium show that no signal is visible below 1×

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AuNP concentration and 1× AuNP is sufficient to generate a visible signal (Figure 2D). This data

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indicates that the minimum AuNP concentration required to generate a visible signal of lowest

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bacteria concentration is 1×. Thus, the optimal labeling condition for the rest of the experiments

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in this study was determined to be 6 min AuNP flow at 6.54 × 1011 particles/mL.

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Double-Strip Device Detection Specificity. The specificity of the device was tested while being

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equipped with two strips. First, a PBS sample containing only 2% BSA (negative control) was

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tested and showed no signal from the test lines (Figure 3A). This is very important for the

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negative control to avoid any background noise because a higher background noise results in a

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low signal-to-noise ratio and can potentially increase the limit of detection. Then, a sample

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containing all four species of bacteria (each species was 107 CFU/mL) was loaded into the

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device. As shown in Figure 3B, detection signals from all test lines indicate no significant

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problem caused by clogging or interference among the bacteria. One of the most crucial features

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of the multiple detection sensor is that signals must appear only when the specific target exists.

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Thus, a sample containing 107 CFU/mL of each species was loaded into the device to test its

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specificity. Figure 3C–F shows that test lines only appear when the target bacterium exists. This

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confirms that the device is capable of performing a specific detection of bacteria and that there is

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no cross-reactivity or background noise.

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Assessment of Limit of Detection. Individual bacterial species were serially diluted (log-

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dilution in each step) in a concentration ranging from 103 to 107 CFU/mL. As shown in Figure

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4A–D, E. coli O157:H7, S. aureus, S. typhimurium and B. cereus’ limits of detection were

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determined to be 105 CFU/mL, 106 CFU/mL, 105 CFU/mL, and 105 CFU/mL, respectively. In

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general, the detection signal increases as the bacteria concentration increases.

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Detection of Bacteria Recovered from Contaminated Lettuce. Experiments were performed

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to validate that the device can be actually used to detect bacteria from fresh vegetables. As a

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demonstration, lettuce was chosen and contaminated with varying concentration of E. coli

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O157:H7 and S. typhimurium separately. Bacteria were recovered from the contaminated lettuces

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and concentrated into a small volume so that it can be loaded into the device. The amount of

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recovered bacteria has a significant impact on the detection result. If the majority of bacteria are

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lost during recovery, the detection result may show false negative despite the sample

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contaminated with a sufficient amount of pathogens for detection. Thus, the bacteria count

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before and after the recovery process was measured. Figure 5A shows the relationship between

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the recovered bacteria from 10 g of lettuce versus the initial inoculation amount. The trend of

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both E. coli O157:H7 and S. typhimurium shows linear relationships between the inoculated and

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the recovered bacteria (R2 values were 0.99 for both). The average bacteria recovery rate from

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contaminated lettuce was 41.80 ± 3.61% for E. coli O157:H7 and 24.47 ± 4.10% for S.

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typhimurium.

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The recovered samples were loaded into the sample pad and the detection was performed with

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lettuces contaminated with three different concentrations of bacteria. The amount of bacteria

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used for contamination, recovered bacteria count, loaded sample concentration, and signal

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appearance are shown in Table S1 of the Supporting Information. As shown in Figures 5B–E, the

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rotary device is able to detect lettuces contaminated with E. coli O157:H7 above 1.87 × 105

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CFU/10 g and S. typhimurium above 1.47 × 105 CFU/10 g. When the bacteria from these

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samples are concentrated, their concentrations are 2.88 × 105 and 1.13 × 105 CFU/mL,

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respectively. These concentrations are within the same order of magnitude of the previously

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characterized limit of detection from spiked samples in PBS (Figure 4). The device, however,

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cannot detect bacteria if the lettuces are contaminated with fewer number of bacteria. It is

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difficult to conclude whether the detection limits are meaningful for practical uses for all target

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bacteria because the infective dose are different for each species. For example, for B. cereus, the

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infective dose is about 105–108 cells per gram of food in order to produce sufficient toxins,30

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which means that the current system has no problem to detect the bacteria. On the other hand, as

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few as 10 CFU of E. coli O157:H7 can cause infection in human,31 which means any E. coli

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O157:H7 that exists below the current limit of detection can cause harm even if the detection

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result is negative. For bacteria whose infective dose is below the limit of detection in the rotary

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device, the bacteria need to be enriched in order to increase their number and also to increase the

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concentration for successful detection.

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Detection of Bacteria after Enrichment. In order to detect bacteria that exist below the limit

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of detection, the contaminated lettuce sample needs to be enriched with growth media and the

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bacteria count must be increased. According to the previous data, the recovered and concentrated

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sample needs to be at least 105 CFU/mL before loading into the device. Considering the final

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volume of the concentrated sample that is loaded into the device (260 µL), the total number of

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recovered bacteria from 10 g of lettuce needs to be at least 2.6 × 104 CFU, or 2.6 × 103 CFU/g.

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This means that, regardless of the initial contaminated amount, as long as at least 2.6 × 104 CFU

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bacteria can be recovered from 10 g of contaminated lettuce after enrichment, the device can

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theoretically detect the contamination. For practical applications, it is important to determine the

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minimum time required to enrich the bacteria to reach the sufficient amount required for

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detection.

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Experiments were performed to measure the bacteria growth over time. The lettuces were

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contaminated with a varying number of E. coli O157:H7 and S. typhimurium that range from 101

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to 103 CFU per 1 gram of lettuce, and the number of recovered bacteria was measured

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immediately after, 3 h after, and 6 h after enrichment in growth media. As expected, the graphs

314

in Figure 6A,B show that recovering E. coli O157:H7 and S. typhimurium from the lettuce

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immediately after the contamination results in a loss, which is also below the limit of detection

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(indicated by red dotted line). After 3 h, the lettuces contaminated with 101 and 102 CFU per

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gram do not reach the minimum number of bacteria required for detection, while the initial

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contamination of 103 CFU/g does reach the minimum number of bacteria for both species. 6 h

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enrichment is enough to enrich all levels of contamination to reach the minimum threshold for

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detection. On the basis of these results, it is concluded that as few as 101 CFU/g of contamination

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can be theoretically detected after 6 h of enrichment.

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To verify the enrichment process allowing for more sensitive detection of bacteria, bacteria

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contaminations were also tested in the following ranges; 0, 1–101, 101–102, 102–103 CFU/g for

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E. coli O157:H7 and 0, 1–101, 101–102 CFU/g for S. typhimurium (Table S2 of the Supporting

325

Information). As shown in Figure 6C,D the detection signals were visible for all tested

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concentrations except for the negative control. It is worth noting that even the lettuces

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contaminated with as low as 1 CFU/1 g shows a positive detection result for both E. coli

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O157:H7 and S. typhimurium after 6 h of enrichment. This can be explained by the fact that the

329

concentrations of the concentrated samples loaded into the device for detection were all above

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105 CFU/mL, which was above the characterized the limit of detection for both species. This

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result indicates that 6 h of enrichment is enough for detection of as few as 1 bacterium in 1 gram

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of lettuce, which is equivalent to about five bacteria per single lettuce leaf.

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In this paper, a handheld device capable of simplifying multistep assays was used to perform

334

sensitive detection of foodborne pathogens. The result shows that contamination can be detected

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as long as the concentrated sample contains bacteria above 105 CFU/mL, which translates to the

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initial contamination amount of 2.6 × 103 CFU per 1 g of lettuce. To further improve the limit of

337

detection, the contaminated sample were incubated in growth media and as few as 1 CFU of E.

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coli O157:H7 or S. typhimurium per 1 g of lettuce was able to be detected after 6 h of

339

enrichment. Such sensitivity is comparable to that of more expensive and complicated molecular

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detection methods such as PCR, which often involves a 24-h enrichment.8

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The recovery and enrichment experiments with lettuce confirm that the device can actually be

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applied to detect pathogens from contaminated fresh vegetable samples. One of the biggest

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problems in the detection of food products are the debris and chunks that exist within the sample

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solution after the pretreatment process, which are known to interfere with assays. In our study,

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although food dye and some debris were observed between the sample pad and the NC strip (at

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the contact zone), they had no detrimental effect on the assay results.

347

The combination of the sample enrichment process along with the use of a rotary device can

348

determine the presence of target bacteria much more quickly than previous methods. In general,

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pathogen identification by selective growth media, PCR or LFT requires 18 to 24 h of

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enrichment and sample pretreatment prior to testing. After enrichment, identification by selective

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growth media along with biochemical tests requires additional 2 to 3 days; PCR needs 2 – 3 h for

352

amplification; and LFT takes about 20 min to complete the test. After enrichment and sample

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treatment, our device takes about 19 min to perform a multiplexed detection, which is much

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shorter than the time required for PCR amplification and biochemical tests. Furthermore, we

355

were able to demonstrate that 6 h enrichment is enough for detection of as low as 1 CFU of

356

pathogen per gram of sample. Considering the time required for sample enrichment, pretreatment

357

and detection, the entire test can be performed within 7 h using our protocol, which is a realistic

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time frame that can be applied for fresh product distribution. The proposed detection protocol

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can possibly be used in food processing facilities where raw materials need to be screened prior

360

to processing and packaging. Such processes may include the packaging for ready-to-eat salads

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and assorted fresh vegetables. Furthermore, it is expected to be used for regular screening of

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fresh vegetables before distribution and help prevent food poisoning and foodborne pathogen

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outbreaks before they occur, potentially saving many lives.

364 365

ASSOCIATED CONTENT

366

Supporting Information

367

The Supporting Information is available free of charge on the ACS Publications website at

368

DOI: 10.1021/acs.jafc.#######.

369

Assessment of limit of detection (Figure S1), the average number of contaminated and

370

recovered bacteria, and loaded sample concentration for the recovery experiment (Table S1), and

371

the number of contaminated and recovered bacteria after enrichment, and loaded sample

372

concentration for the enrichment experiment (Table S2) (PDF).

373 374

AUTHOR INFORMATION

375 376

Corresponding Authors

377

*Fax: +82-63-238-3840. Phone: +82-63-238-3406. E-mail: [email protected] (E.R).

378

*Fax: +82-42-350-4310. Phone: +82-42-350-4315. E-mail: [email protected] (J.-K.P).

379

ORCID

380

Je-Kyun Park: 0000-0003-4522-2574

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Author Contributions

382



383

Funding

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This research was supported by the Rural Development Administration of Korea (Grant No.

Joong Ho Shin and Jisoo Hong contributed equally to this work.

385

PJ009842)

and

the

National

Research

Foundation

386

2016R1A2B3015986) funded by the Ministry of Science and ICT.

387

Notes

388

The authors declare no competing financial interest.

of

Korea

(Grant

No.

NRF-

389

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Journal of Agricultural and Food Chemistry

REFERENCES

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FIGURE CAPTIONS

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Figure 1. Working principle of a handheld multistep lateral flow assay device for the detection

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of pathogens. (A) Photo of the double-strip rotary detection device with two test strips and a

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schematic showing the test line layout for multiple detection of pathogens. The right test strip has

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two control lines because AuNP conjugated with antibody and AuNP conjugated with CBD both

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have to be captured. (B) An exploded view of the rotary device showing its components and its

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layers. (C) Schematic showing each step of AuNP-based detection involving bacteria capture,

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AuNP labeling, and AuNP signal enhancement steps.

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Figure 2. Screening result of AuNP concentrations and flow duration. (A) Graph showing the

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intensity of detection signal of 107 CFU/mL S. typhimurium over time for different

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concentrations of AuNP used (n = 3). (B) Pictures showing the saturated intensity of the

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detection signal after 16 min of AuNP flow. (C) Pictures and quantified intensities of 105

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CFU/mL S. typhimurium with varying duration of 2× AuNP flow (n = 3). (D) The enhanced

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detection signal generated with varying concentrations of AuNP after 6 min flow. Red arrows

464

indicate the visible signals. The data points and error bars represent the mean and standard

465

deviation of the mean.

466 467

Figure 3. Photos showing the detection specificity of multiple detection of all four species of

468

bacteria. (A) Negative control result shows that there is no background signal. (B) All signals are

469

present with a sample containing all four samples (the concentration of each species in the

470

sample is 107 CFU/mL). (C–F) Sample containing 107 CFU/mL of each species results in

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appearance of their respective test line, indicating detection specificity. Red arrows indicate

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positive test lines.

473 474

Figure 4. Test signal intensity versus bacteria concentration for each species. Photos of detection

475

results and graphs showing the quantified signal intensity of (A) E. coli O157:H7 (n = 3), (B) S.

476

aureus (n = 3), (C) S. typhimurium (n = 3) and (D) B. cereus (n = 3). The limits of detection of E.

477

coli O157:H7, S. aureus, S. typhimurium and B. cereus were determined to be 105 CFU/mL, 106

478

CFU/mL, 105 CFU/mL, and 105 CFU/mL, respectively. The data points and error bars represent

479

the mean and standard deviation of the mean.

480 481

Figure 5. A bacteria recovery rate and corresponding signal intensity from contaminated lettuce.

482

(A) Graph showing the recovered bacteria counts versus the number of inoculated bacteria per 10

483

g of lettuce (n = 3). (B) Photos and (C) quantified signal intensity of recovered E. coli O157:H7

484

from contaminated lettuce (n = 3). (D) Photos and (E) quantified signal intensity of recovered S.

485

typhimurium from contaminated lettuce (n = 3). The data points and error bars represent the

486

mean and standard deviation of the mean.

487 488

Figure 6. Graph showing the number of bacteria after varying enrichment time for (A) E. coli

489

O157:H7 (n = 3) and (B) S. typhimurium (n = 3) with varying bacteria count of initial

490

contamination. Red dotted line indicates the minimum amount of recovered bacteria required for

491

detection (2.6 × 103 CFU/g). Pictures showing the detection results of (C) E. coli O157:H7 and

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(D) S. typhimurium after enrichment with different amounts of initial bacteria inoculation. The

493

data points and error bars represent the mean and standard deviation of the mean.

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Table of Contents artwork

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(1st: Food Safety and Toxicology; 2nd: Analytical Methods; 3rd: Agricultural and Environmental Chemistry)

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