Patent Application
20220326209
Mycotoxins are toxic chemicals produced by fungi that infect crops. It is reported that typically more than 25% of the harvested crops have been contaminated with mycotoxin (1). More than 200 species of trichothecene, which are divided into four groups, have been found so far (2). Vomitoxin is one of the trichothecene mycotoxin produced by Fusarium (3). The main compounds of vomitoxin consist of deoxynivalenol (DON), 3-acetyl deoxynivalenol, and 15-acetyl deoxynivalenol, which are widely present in cereals such as wheat, barley, and corn (4). Vomitoxin contaminations pose threats to the health of humans and animals, especially to immune functions (5-7). Specifically, the ingestion of foods contaminated with vomitoxins can cause immunosuppression or immune overstimulation, resulting in some acute poisoning symptoms such as anorexia (8), vomiting (9), diarrhea (10), fever, and unresponsiveness (11). In severe cases, vomitoxin could damage the hematopoietic system and cause death (12). Due to the toxic effects of vomitoxins on the health of humans and animals, there are currently 37 countries in the world that have relevant limits for vomitoxins in foods or feeds. The USFDA stipulates that the safety standard for vomitoxins in foods is 1 ppm (13). The safety standards for vomitoxins in the feeds are animal species-dependent, for example, it is lower than 1 ppm for swine and 5 ppm for ruminant and poultry (14). Vomitoxin is represented in more than 90% of all mycotoxin-contaminated samples, and its presence usually indicates that other mycotoxins are also present (15). The laboratory detection methods for vomitoxin mainly consist of high-performance liquid chromatography (HPLC), enzyme-linked immunosorbent assay (ELISA), and liquid chromatography-tandem mass spectrometry (LC-MS), whose pre-processing steps are cumbersome and analysis time is long. The high cost and low efficiency of these laboratory methods makes them difficult to be widely used in food or feed quality supervision and control.
Rapid, sensitive and accurate methods for vomitoxin quantification in a non-laboratory environment are essential for toxicological analysis and risk assessment of foods or feed products. At present, the lateral flow immunoassay (LFIA), also known as immunochromatographic assay (ICA) or strip test, is currently used for qualitative, semi-quantitative, or quantitative monitoring of vomitoxin in a non-laboratory environment. Sandwich and competitive targeting methods could be used for immunoassays. Sandwich immunoassays are commonly used to measure large analytes with multiple epitopes, while competitive immunoassays are the choice for quantification of small analytes which have low molecular weight or only a single specific epitope (16). As vomitoxin is a small molecule and does not exhibit more than one epitope, the competitive method is used for qualitative and quantitative detection of vomitoxins. Specifically, an indicator (labeled with vomitoxin or vomitoxin antibody) reacts with capturing molecules (vomitoxin antibody or vomitoxin) deposited in the test area (17-19). Vomitoxin in the sample competes for the binding sites with the capturing molecules (vomitoxin antibody or vomitoxin) on the test area, leading to non-aggregation of indicators in the test area.
Due to heterogeneous distribution of vomitoxins in the same batch of food or feed products, density-based sampling and replicate detections are needed for assessment of mycotoxin contamination, which increases the detection cost (20). Many commercial immunocolloidal gold rapid detection kits have been developed for detecting vomitoxins in foods or feed products. However, these commercial kits are relatively high priced and not sensitive for on-site vomitoxin detection. Microfluidic analytical devices have been considered as a promising alternative to the traditional tests. Various materials can be used for fabricating microfluidic devices such as polymers, thermoplastic, glass, cloth, and paper (21). Among them, the microfluidic paper based analytical device (μPAD) offers the benefits of low-cost, easy fabrication, and self-powered fluidic transport by capillary force (22). The μPAD can control fluidic transport within hydrophilic channels defined by hydrophobic barriers (23). Recently, μPAD has been increasingly used for various chemical, biochemical, and biological applications (24-26).
In the present study, we developed a μPAD-based immunoassay for rapid and low-cost detection of DON, called DON-Chip. We chose DON for this initial assay because this vomitoxin is present in more than 90% of all mycotoxin-contaminated samples, and its presence is usually a good indicator that other mycotoxins are also present. The paper-based microfluidic immunoassay was realized by competitive immunoreaction leveraged gold nanoparticle-based colorimetric signals. These signals were captured using a portable USB microscope. The developed DON-Chip was successfully validated by DON standards and different food, feed and feed ingredient samples. The useful features of this DON-Chip are fast testing (within 12 min), low-cost (<2 US dollars of material cost per test), high reproducibility, and integration with a portable imaging system for easy signal readout. Overall, the DON-Chip provides an excellent example of microfluidic paper-based technology for rapid and low-cost detection of mycotoxins in foods and feed products.
According to a first aspect of the invention, there is provided a method for detecting levels of deoxynivalenol in a sample comprising:
providing an assay support comprising a sample loading area connected by a channel to a first test area and a second test area;
said sample loading area comprising a quantity of anti-deoxynivalenol compound binding antibodies;
said first test area comprising a quantity of deoxynivalenol compound bound to a carrier;
said second test area comprising a quantity of anti-deoxynivalenol compound binding antibodies binding reagent;
wherein said sample flows from the sample loading area along the channel to the first test area and then along the channel to the second test area;
loading a sample to be tested for a deoxynivalenol compound onto the sample loading area such that contents of the sample interact with the quantity of anti-deoxynivalenol compound binding antibodies, a portion of said quantity of anti-deoxynivalenol compound binding antibodies forming anti-deoxynivalenol compound binding antibody:deoxynivalenol compound complexes, a remaining portion of the quantity of anti-deoxynivalenol compound binding antibodies remaining unbound anti-deoxynivalenol binding antibodies;
said sample comprising the anti-deoxynivalenol compound binding antibody:deoxynivalenol complexes and the unbound anti-deoxynivalenol compound binding antibodies flowing along the channel to the first test area, said unbound anti-deoxynivalenol compound binding antibodies binding to the quantity of deoxynivalenol compound bound to a carrier and being retained in the first test area;
said sample comprising the anti-deoxynivalenol compound binding antibody:deoxynivalenol compound complexes continuing to flow along the channel to the second test area, said anti-deoxynivalenol compound binding antibody:deoxynivalenol compound complexes binding to the quantity of anti-deoxynivalenol compound binding antibodies binding reagent and being retained in the second test area; and
measuring the deoxynivalenol compound level in the sample by detecting the anti-deoxynivalenol compound binding antibodies at the first test area and/or detecting the anti-deoxynivalenol compound binding antibodies at the second testing area.
According to another aspect of the invention, there is provided a method for manufacturing a device for detecting deoxynivalenol in a sample comprising:
providing an assay support comprising a sample loading area connected by a channel to a first test area and a second test area;
depositing a quantity of anti-deoxynivalenol compound binding antibodies at the sample loading area;
depositing a quantity of anti-deoxynivalenol compound bound to a carrier at the first test area; and
depositing a quantity of anti-deoxynivalenol compound binding antibody binding reagent at the second testing area.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, the preferred methods and materials are now described. All publications mentioned hereunder are incorporated herein by reference.
Mycotoxin contamination causes over 5 billion dollars of economic loss per year in the North American food and feed industry. A rapid, low-cost, portable and reliable method for on-site detection of deoxynivalenol (DON), a representative mycotoxin predominantly occurring in grains, would be helpful to control mycotoxin contamination. Herein, a paper-based microfluidic chip capable of measuring deoxynivalenol (DON-Chip) in foods, feeds and feed ingredients was developed. As discussed herein, the DON-Chip incorporated a colorimetric competitive immunoassay into a paper microfluidic device and used gold nanoparticles as a signal indicator. Furthermore, a novel ratiometric analysis method was used to improve signal resolvability at low concentrations of DON. Detection of DON in aqueous extracts from solid foods, feeds or feed ingredients was successfully validated with a detection range from 0.01-20 ppm (using dilution factors from 10-104). Compared with conventional methods, the novel DON-Chip greatly reduces the cost and time of mycotoxin detection in the food and feed industry.
As discussed herein, with careful optimizations in device design, reagent concentration and reaction conditions, the DON-Chip can be used for on-site measurement of DON concentration in real-world foods, feeds and feed ingredients within 12 min, with a detection range from 0.01-20 ppm. It is worth noting that the present DON-Chip is the first competitive immunoassay that combines the complementary signals of low and high DON concentration samples for a more complete and realistic measurement. Moreover, the ratiometric value between these two signals provide lower LODs and better resolvability at low concentrations. Overall, the DON-Chip offers a low-cost portable alternative for mycotoxin detection with strong implications for improving animal health and food safety.
According to an aspect of the invention, there is provided a method for detecting levels of deoxynivalenol in a sample comprising:
providing an assay support comprising a sample loading area connected by a channel to a first test area and a second test area;
said sample loading area comprising a quantity of anti-deoxynivalenol compound binding antibodies;
said first test area comprising a quantity of deoxynivalenol compound bound to a carrier;
said second test area comprising a quantity of anti-deoxynivalenol compound binding antibodies binding reagent;
wherein said sample flows from the sample loading area along the channel to the first test area and then along the channel to the second test area;
loading a sample to be tested for a deoxynivalenol compound onto the sample loading area such that contents of the sample interact with the quantity of anti-deoxynivalenol compound binding antibodies, a portion of said quantity of anti-deoxynivalenol compound binding antibodies forming anti-deoxynivalenol compound binding antibody:deoxynivalenol compound complexes, a remaining portion of the quantity of anti-deoxynivalenol compound binding antibodies remaining unbound anti-deoxynivalenol binding antibodies;
said sample comprising the anti-deoxynivalenol compound binding antibody:deoxynivalenol complexes and the unbound anti-deoxynivalenol compound binding antibodies flowing along the channel to the first test area, said unbound anti-deoxynivalenol compound binding antibodies binding to the quantity of deoxynivalenol compound bound to a carrier and being retained in the first test area;
said sample comprising the anti-deoxynivalenol compound binding antibody:deoxynivalenol compound complexes continuing to flow along the channel to the second test area, said anti-deoxynivalenol compound binding antibody:deoxynivalenol compound complexes binding to the quantity of anti-deoxynivalenol compound binding antibodies binding reagent and being retained in the second test area; and
measuring the deoxynivalenol compound level in the sample by detecting the anti-deoxynivalenol compound binding antibodies at the first test area and/or detecting the anti-deoxynivalenol compound binding antibodies at the second testing area.
In some embodiments of the invention, the anti-deoxynivalenol compound antibodies comprise a detectable label.
It is of note that any suitable detectable label known in the art for use with antibodies may be used within the invention. For example, the detectable label may be a gold-nanoparticle or a fluorescent microsphere.
In some embodiments of the invention, the anti-deoxynivalenol compound antibodies are labeled with gold nanoparticles.
As discussed herein, in these embodiments, the test is a colorimetric test. Accordingly, a wide variety of detection methods may be used, including for example a cell phone's camera.
In some embodiments, the assay support is a paper-based microfluidic chip.
For example, the paper-based microfluidic chip may be composed of nitrocellulose paper.
As will be appreciated by one of skill in the art, compared with the traditional well-plate-based assay, the use of a paper microfluidic device has several advantages: a) it has a faster reaction time. The nitrocellulose paper consists of large numbers of micropores (0.45 μm) that favor the contacts and reactions between antibody and antigens (all the reactions can be done in 10s, during the liquid flow). In a well plate-based ELISA assay, the molecules are all in Brownian motion within a microplate, and it takes a longer time (40 min in 37° C.) to finish the reaction. b) The reagents are preloaded in the chip thus the chip is self-sufficient for the assay, as discussed herein. c) Easy operation, as capillary force is used to drive the flow. d) Compared with the traditional lateral flow assay, the paper microfluidic device not only consumes fewer reagents and samples but one assay support could be easily developed to achieve multiplex detection, that is, to process multiple samples.
The sample may be a food sample or a feed sample. As will be appreciated by one of skill in the art, an ingredient of a food product or feed product would also be considered a food sample or feed sample.
As discussed herein, in some embodiments, the deoxynivalenol compound level is determined by detecting the anti-deoxynivalenol compound binding antibodies at the first test area and detecting the anti-deoxynivalenol compound binding antibodies at the second testing area.
As discussed below, because the total amount of anti-deoxynivalenol compound binding antibodies in the assay support is known, detecting the amount in either one test area or both can be used as a measurement of the level of the deoxynivalenol compound in the sample for example by using previously prepared calibration curves as discussed herein. It is of note that the calibration curves do not necessarily need to be repeated for each test.
As discussed herein, in some embodiments, the deoxynivalenol compound level is determined by the ratio of anti-deoxynivalenol compound binding antibodies at the first test area to the anti-deoxynivalenol compound binding antibodies at the second testing area.
As discussed herein, in some embodiments, the width of the channel may be from 1.0-2.0 mm and the length of the channel may be from 8 mm-16 mm.
As will be appreciated by one of skill in the art, the dimensions of the chip are closely associated with detection speed and cost. A chip with larger dimensions would consume more antibodies to get a proper signal intensity, while a smaller dimension limits the liquid flow speed which may be acceptable under certain circumstances.
In some embodiments of the invention, the channel has curved corners which achieves the best flow speed among the designs tested. As per above, in some embodiments, other arrangements are acceptable in certain circumstances.
The first testing area and the second testing area may be separated by a separation zone. As will be appreciated by one of skill in the art, without a separation between the two test areas, the reagents bound in the T1 area and T2 area may cross-contaminate and/or it may not be easy to distinguish the boundary of the distinct signals emitting from these two areas. In some embodiments, the separated area or separation zone has a different width, that is, has a larger width than the channel. For example, the separation zone may be 2 mm wide while the channel width may be 1.5 mm.
The “deoxynivalenol compound” as used herein refers to a compound selected from the group consisting of deoxynivalenol, 3-acetyl deoxynivalenol and 15-acetyl deoxynivalenol.
In some embodiments, the assay support further comprises an absorbent zone and the sample flows along the channel from the second test area to the absorbent zone. As will be appreciated by one of skill in the art, the absorbent zone at one end of the channel promotes flow from the sample loading area, past the first test area and the second test area.
The anti-deoxynivalenol compound binding antibodies binding reagents may be any suitable agent known in the art that will specifically bind the anti-deoxynivalenol compound binding antibodies. In some embodiments, these reagents are secondary antibodies. As is known to those of skill in the art, secondary antibodies are used in the art to bind to the primary antibody to assist in detection, sorting and purification of target antigens. To enable detection, the secondary antibody must have specificity for the antibody species and isotype of the primary antibody being used.
According to another aspect of the invention, there is provided a method for manufacturing a device for detecting deoxynivalenol in a sample comprising:
providing an assay support comprising a sample loading area connected by a channel to a first test area and a second test area;
depositing a quantity of anti-deoxynivalenol compound binding antibodies at the sample loading area;
depositing a quantity of anti-deoxynivalenol compound bound to a carrier at the first test area; and
depositing a quantity of anti-deoxynivalenol compound binding antibody binding reagent at the second testing area.
As discussed herein, within an ideal detecting environment (room temperature=24° C., pH value=6-8), all the parameters (T1, T2, T1/T2, and T2/T1) are accurate indicators for DON quantitation. According to our analysis from the raw data and these calibration curves, the ratiometric parameters (T1/T2, T2/T1) could achieve lower LODs (T1/T2 of 0.432 ng/mL vs T1 of 0.644 ng/mL), higher recovery ratio and higher resolution in the marginal concentration ranges.
For example, the immunoreactions both in T1 area and T2 area tend to be weaker in the morning due to a relatively low temperature, and it is expected that the signal intensity of both T1 and T2 will decrease by a similar percentage (For example, the T1 goes to be m*T1, and T2 goes to be n*T2, m, n<1). In this scenario, the ratiometric parameters (mT1/nT2, nT2/mT1) have a self-correcting capability by counteracting the errors from incomplete immunoreaction. The result from the values of mT1/nT2 and nT2/mT1 have better accuracy when compared with that from the sole signal values (m*T1 or n*T2).
Optimization of the DON-Chip. Speed, cost, reliability, and sensitivity are the most important parameters for an on-site detection system. We first optimized the DON-Chip to make a balance between these parameters through the following steps: 1) we chose an optimal channel dimension and pattern to achieve a fast speed for the sample flow; 2) we ensured an adequate amount of DON-BSA in the T1 area and secondary antibody in the T2 area, aiming to capture all the antibody-conjugated AuNPs; 3) we optimized the concentration of DON-BSA to ensure high sensitivity while reducing the cost; 4) we proposed an analysis method which combines the signals in T1 area and T2 area to generate the calibration curve and determine the DON concentration. The details of some optimizations are described as follows:
The effects of the channel dimension and pattern on the capillary flow speed are shown in
To optimize the concentration of DON-BSA, we deposited different concentrations of DON-BSA in the T1 area (ranging from 0 to 3.8 μg/μL) and assessed the signal after adding 2 uL of Anti-DON-AuNPs on the conjugate pad. As shown in
In each test, the volume of gold nanoparticles deposited in the DON-Chip was kept the same. Theoretically, the sum of the signals in T1 and T2 areas in one channel should be constant if all the antibody-conjugated gold nanoparticles were captured. We tested this hypothesis by summing the signals in T1 and T2 areas (T1+T2) in the channels after applying different concentrations of DON standards (0.0, 1.0, 2.0, 4.0, 8.0, 16.0, and 20.0 ng/mL). As shown in
Calibration of the DON-Chip. As discussed herein, in some embodiments, the saturated binding concentration of DON in this DON-Chip is nearby 20 ng/mL. In the present study, we used concentrations of 0.0, 1.0, 2.0, 4.0, 8.0, 16, 20 ng/mL as DON standards to determine calibration curves. The representative images of signals in T1 and T2 in the DON-Chip are shown in
We then compared the performances of these three calibration curves for calculating the DON concentration in actual samples. The calibration curves using values of the T1, T2 and T1/T2 are shown in
The USFDA stipulates that the safety standard for DON in foods is 1 ppm (13). The safety standards for DON in feeds are animal species-dependent, that is, lower than 1 ppm for swine and 5 ppm for ruminant and poultry (14). As will be appreciated by one of skill in the art, by applying different dilution factors from 10-1000, the detection range of this DON-Chip could be 0.01-20.0 ppm. The calculated LODs in the DON-Chip for the solid samples are 6.44 ppb, 4.68 ppb, and 4.35 ppb (dilute factor, 10) from the calibration curves of T1, T2, and T1/T2, respectively. As can be seen, the LODs for the DON-Chip are much lower than the LOD for a commercial ELISA kit (Table 7) and the safety standard for foods or feeds. These results indicate that DON-Chip has enough sensitivity and detection range to meet the safety regulations in food, feed and feed ingredient samples.
Stability of DON-Chip under different conditions. Considering that different pH values and many other species of mycotoxins occur in food, feed and feed ingredient samples, we tested the interferences of pH and ZEN, a frequent mycotoxin contaminant in cereals (27) on DON measurement using the DON-Chip. As shown in Table 1, adding ZEN (ranging from 1-15 ng/mL) in the standard samples did not affect the DON measurements.
As shown in Table 2, use of a dilution buffer having a pH ranging from 6.0-9.0 did not affect the DON measurements in the DON-Chip. However, the DON-Chip does not work in extreme acid (pH=3) or alkaline (pH=10) conditions. It is surmised that the ineffectiveness of these detections under extreme pH might be attributed to the denaturation of DON-antibody, and disassembly of anti-DON-AuNPs. It is of note that extreme pH conditions can be avoided by diluting the extracted supernatant into for example a PBS buffer before sample loading.
Efficacy of DON-Chip in spiked corn samples. To simulate DON detection in actual food or feed samples, we artificially added the DON standards to uncontaminated corn samples, and then extracted the DON from the spiked corn samples according to sample preparation and analytical procedures described in the methods section. As shown in Table 3, the recoveries of DON were in the range of 90-105%. All the CV values were lower than 10%, indicating good repeatability of this DON-Chip.
Applications of DON-Chip in food, feed and feed ingredient samples. To evaluate the capability of this DON-Chip in determining DON concentrations in real-world samples, the DON concentrations in 21 food, feed and feed ingredient samples were measured using the DON-Chip and a commercial DON ELISA kit. The samples were prepared using the same method described in the sample preparation section. A dilution factor of 100 was applied for the ELISA detections. A dilution factor of 1000 was applied for DDGS samples, 500 for corn, feed and unhusked rice samples, and 100 for wheat samples in DON-Chip detection. As shown in Table 4, the detection results from ELISA and DON-Chip for the same sample are quite similar (variation <15% between two methods). Only one data point from the DDGS sample (4) showed a significant difference (P<0.05) between these two methods.
The linear fit comparing the DON measurements obtained from ELISA and DON-Chip is shown in
Different DONs (deoxynivalenol, 3-acetyl deoxynivalenol, and 15-acetyl deoxynivalenol) have similar chemical structures, which presents a challenge to distinguish them using conventional immunoassays. However, the DON-Chip could be designed to leverage antibody cross-reactivity, such that one antibody capable of cross-reacting with all three common DONs in a sample could be detected to maximize efficiency and minimize overall cost. According to the data provided by the antibody provider, the values of cross reactivity between the DON-antibody to the deoxynivalenol, 3-acetyl deoxynivalenol, and 15-acetyl deoxynivalenol are 100%, 95% and 46%, respectively. Based on these values, all the three common DONs in the samples could be detected in the DON-Chip. Thus, the developed DON-Chip can be used as an effective tool to evaluate the total concentration of common DONs in commercial food and feed samples.
Comparison of DON-Chip to other methods. Table 7 shows the comparison of the DON-Chip with the ELISA kit and commercial strip in terms of LOD, assay time, detection range, cost, and on-site detection capability. The assay time of the DON-Chip is comparable with the commercial strip and both methods can be applied for on-site detection. Importantly, DON-Chip shows lowest LOD and cost. Therefore, the DON-Chip shows promise for on-site mycotoxin detection in the food and feed industry.
The invention will now be further explained and/or elucidated by way of examples; however, the invention is not necessarily limited to or by the examples.
Materials. Purified deoxynivalenol standard (RN51481-10-8, >98%) was purchased from Sigma-Aldrich (Saint Louis, Mo., USA). BSA conjugated deoxynivalenol and deoxynivalenol polyclonal antibody (cross reactivities 100% to deoxynivalenol, 95% to 3-acetyl deoxynivalenol, and 46% to 15-acetyl deoxynivalenol) were purchased from Unibiotest Co., Ltd (Wuhan, Hubei, China). The GOLD nanoparticle conjugation Kit (ab188215) was purchasedfrom Abcam (Cambridge, Mass., USA). Goat anti-mouse IgG (40121) was purchased from Alpha Diagnostic Intl. Inc (San Antonio, Tex., USA). Nitrocellulose paper (HF09004X SS), absorbent paper
Antibody-conjugated gold nanoparticles preparation. We conjugated the anti-DON antibody to the gold nanoparticles (AuNPs) according to the product manual and then purified the conjugations to remove the unconjugated antibody. Firstly, all the reagents were warmed to room temperature. The anti-DON antibody was diluted into the diluent buffer to a final concertation of 0.25 mg/mL. 120 μL of diluted anti-DON antibody was mixed with 420 μL reaction buffer thoroughly. 450 μL of the mixture was transferred to the AuNP vial and reconstituted the freeze-dried mixture by gently pipetting up and down for 20 min. Afterwards, 50 μL of quencher reagent was added to the vial and mixed gently. This process produced 500 μL of anti-DON antibody conjugated AuNPs (Anti-DON-AuNPs).
To remove the excess antibody, we washed the Anti-DON-AuNPs twice by 10 times volume of washing buffer and centrifuged the solution in a microfuge at 9,000 g for 30 minutes. The pellet was resuspended using 1:10 diluted quencher reagent and stored at 4° C. until use.
Paper-based device fabrication. As illustrated in
DON-BSA (0.1 μL at 1.9 μg/μL) was spotted at the test 1 (T1) area, and goat anti-mouse IgG (0.1 μL at 1.0 μg/μL) was deposited at the test 2 (T2) area. The spotted paper was dried overnight at room temperature. The dried paper was then blocked with 0.2% BSA in PBS for 20 minutes. A 2 μL working solution of Anti-DON-AuNPs was added to each conjugate pad. Conjugate pads were dried at room temperature and kept in 4° C. before use. The fully assembled DON-Chip consisted of the conjugate and absorbent pads attached to the patterned nitrocellulose paper as shown in
Sample preparation. Twenty-one naturally contaminated grain samples [distillers dried grains with soluble (DDGS), wheat, corn, feeds, and unhusked rice] were kindly provided by the Wallenstein Feed & Supply Ltd. (Wallenstein, ON, Canada). The samples were ground using a coffee grinder before mycotoxin extraction. One gram of each powder sample and 10.0 mL of water were added into a 50 mL Eppendorf tube and then mixed by a digital vortex mixer at 3000 times/min for 5 min. The solution was then centrifuged at 4,500 rpm for 5 min at 4° C., and 1 mL of the supernatant was transferred to an Eppendorf microcentrifuge tube for further analysis.
DON measurement using the DON-Chip. The operation and detection principles of the DON-Chip are illustrated in
Detection of DON in spiked samples. To validate the DON-Chip in detecting DON from real world samples, we artificially spiked the corn samples with a DON standard at different concentrations from 0.05 to 1.8 ppm and then conducted the DON detection using the DON-Chip. 0.5 gram of non-infected corn sample was ground and mixed in 1.0 ml of ethyl alcohol solution containing a suitable amount of DON standard. Then the spiked samples were subjected to dissolvent evaporation for 4 h at room temperature. The non-infected corn used in this study was obtained from local market, previously confirmed to contain undetectable levels of DON using the DON-Chip (signal changes in T1 and T2 area are both lower than three times of the standard deviation of blank signal values). The procedures of sample preparation and DON detection were described above.
Interference tests of other mycotoxin and pH. To test the specificity of DON-Chip, equal concentrations (ranging from 1.0-15 ng/mL) of zearalenone (ZEN) were added in the DON standard solutions before the test. The pH interference was tested by adjusting the PBS loading buffers to different pH levels (6.0, 7.2, 8.0 and 9.0).
Portable imaging system. A portable imaging system was developed to facilitate on-site signal reading using the DON-Chip. The system is composed of an XY stage to locate the signal areas, a Z-stage to adjust the focus, and a USB microscope to read the signal. Several custom parts were machined to mount these components on an optical breadboard.
Image capture and signal analysis. The images captured by the portable imaging system were analyzed using the Photoshop CS6 software (Adobe Systems Incorporated, CA, USA). A color image with 1280×1024 pixels that covers the detection areas was captured for signal measurement. The color of images was inverted and then split into three RGB channels and the green channel was used to calculate the signal intensity. Four areas of interest (AOIs) were selected for each channel: T1 area, T2 area, and two blank control area (blank area 1 and blank area 2) around the signal areas. In the histogram of each image, the average value of green channel and the number of pixels was recorded for each AOI. The signal intensities in T1 and T2 areas were calculated using the equation: signal intensity=[average value of AOI— (average value of blank area 1+average value of blank area2)/2]×the number of pixels. The signals from different concentrations (0.0, 1.0, 2.0, 4.0, 8.0, 16, 20 ng/mL) of DON standard were used to generate the calibration curves using four-parameter logistic regression. The signals from four channels (4 replicates, 2 chips) were applied for each detection. We generated three calibration curves from different signal values (T1, T2, T1/T2) and compared their performances. The DON concentration in unknown samples was calculated by fitting the measured signal to the calibration curves.
DON measurement with a commercial ELISA kit. The DON concentrations in the food, feed and feed ingredient samples were measured by a commercial DON ELISA Kit. The signal was read using a Synergy™ H4 Hybrid Multi-Mode Microplate Reader (BioTek, Winooski, Vt., USA) at 450 nm. Before the ELISA test, all the raw samples were initially prepared according to the sample preparation section. The procedures were strictly conducted according to the manufacturer's recommendation.
Statistical analysis. Statistical analyses were performed using GraphPad Prism 8.01 (San Diego, Calif., USA). The Student's t-test was used to compare the DON test data obtained from different conditions or methods. The difference between the two sets of data was considered statistically significant when P value<0.05. One-way ANOVA test was conducted to analyze the difference of total signaling intensity (T1+T2) among the DON standards detections (0.0, 1.0, 2.0, 4.0, 8.0, 16.0, and 20.0 ng/mL).
While the preferred embodiments of the invention have been described above, it will be recognized and understood that various modifications may be made therein, and the appended claims are intended to cover all such modifications which may fall within the spirit and scope of the invention.
1The Student's t-test was conducted to compare the DON test data under different concentrations of ZEN interference (0, 1, 5 and 15 ng/mL). P < 0.05 was considered a significant difference versus the blank group (0.0 ng/mL ZEN), and presented by
1The Student's t-test was conducted to compare the DON test data detecting in the different pH values (pH = 6, 7, 8 and 9). P < 0.05 was considered a significant difference versus the control group (pH = 7.2), and presented by
1Recovery ratio was calculated using the equation: Recovery (%) = (Means/concentration of DON standards) × 100%.
2CV, coefficient of variation of intra-assay was calculated using the equation: CV = (SD/Means) × 100%.
1A dilution factor of 1000 was applied for distillers dried grains with soluble (DDGS) samples, 500 for corn, feed and unhusked rice samples, and 100 for wheat samples during DON-chip detection.
2A dilution factor of 100 was applied for the ELISA detections.
3The Student's t-test was conducted to compare the DON test data obtained from the different methods. The results obtained from the two detection methods were considered significant different when P value < 0.05.
1Calibration equations for T1, T2 and T1/T2 are “Y = {130.62/[1 + (X/2.42)1.3] − 4.39}*104, R2 = 0.992”, Y = {130.07 − 113.57/[1 + (X/2.91)1.58]} *104, R2 = 0.995, and Y = 7.92/[1 + (X/0.68)1.57] − 0.016, R2 = 0.983, respectively.
2The resolvability on detecting low concentrations (0.5-1.0 ng/mL) of DON was calculated by the equation: Resolvability = |{[Y(n) − Y(n + 0.1)]/Y(n)} | × 100%.
The instant application claims the benefit of U.S. Provisional Patent Application 62/906,441, filed Sep. 26, 2019 and entitled “A paper-based microfluidic DON-Chip for rapid and low-cost deoxynivalenol quantification in foods, feeds and feed ingredients”, the entire contents of which are incorporated herein by reference for all purposes.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/CA2020/051289 | 9/28/2020 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 62906441 | Sep 2019 | US |
