Real-time PCR Detection Methods for Food Allergens (Wheat, Buckwheat, and Peanuts) Using Reference Plasmids

Development of a rapid and reliable method to simultaneously detect seven food allergens in processed foods using LC-MS/MS

Rapid analysis of multiple food allergens is required to confirm the appropriateness of food allergen labelling in processed foods. This study aimed to develop a rapid and reliable method to simultaneously detect trace amounts of seven food allergenic proteins (wheat, buckwheat, milk, egg, crustacean, peanut, and walnut) in processed foods using LC-MS/MS. Suspension-trapping (S-Trap) columns and on-line automated solid-phase extraction were used to improve the complex and time-consuming pretreatment process previously required for allergen analysis using LC-MS/MS. The developed method enabled the simultaneous detection of selected marker peptides for specific proteins derived from seven food ingredients in five types of incurred samples amended with trace amounts of allergenic proteins. The limit of detection values of the method for each protein were estimated to be <1 mg/kg. The developed analytical approach is considered an effective screening method for confirming food allergen labelling on a wide range of processed foods.

Resistance of Ascochyta rabiei isolates from chickpeas (Cicer arietinum L.) to fungicides

Ascochyta blight is a disease that causes significant yield losses in chickpea crops in Turkey under favorable environmental conditions. The fungal pathogen Ascochyta rabiei is the causative agent of this disease. The antifungal activity of previous fungicides against A. rabiei was not effective due to the heterothallic nature of the fungus. The aim of this study was to determine the sensitivity of A. rabiei to fungicides (25.2 g kg-1 boscalid + 12.8 g kg-1 pyraclostrobin; 50 % tebuconazole + 25 % trifloxystrobin; 62.5 g L-1 propiconazole + 37.5 g L-1 azoxystrobin; 80 % thiram; 80 % kükürt (sulphur); 80 % mancozeb; 80 % maneb) under in vitro and field conditions. Pure cultures of A. rabiei were isolated from infected chickpea plants collected in Boğazlayan, Sarıkaya, Sorgun, Merkez and Yerköy. A total of 14 A. rabiei isolates and 4 references were evaluated. The field test was conducted at Yozgat Bozok University, Yerköy Agricultural Application and Research Center Station. The trials began on March 14, 2021. The experimental area was divided into plots and the susceptible chickpea variety Sarı98 was used for the study. Two artificial inoculations were carried out approximately on the 40th and 80th days after sowing. Twenty-four hours after inoculation, the chickpea plants were sprayed with the fungicides Nativo® WG 75, Bellis®, Dikotan® M45 and Thiovit Jet® using a handheld sprayer. In vitro testing revealed that A. rabiei was resistant to kükürt (sulphur), thiram, maneb, and mancozeb. A field study showed that the percentage of A. rabiei isolates treated with the mancozeb fungicide was between 14 and 21 % of the control. Therefore, effective disease management strategies should include not only the use of fungicides, but also alternative approaches such as the use of resistant varieties. Moreover, the study focused on phenotypic resistance and suggests that future research should investigate the genetic and molecular mechanisms underlying A. rabiei resistance to enable better resistance management.

The gut microbiota intervenes in glucose tolerance and inflammation by regulating the biosynthesis of taurodeoxycholic acid and carnosine

Objective

This study aims to investigate the pathogenesis of hyperglycemia and its associated vasculopathy using multiomics analyses in diabetes and impaired glucose tolerance, and validate the mechanism using the cell experiments.

Methods

In this study, we conducted a comprehensive analysis of the metagenomic sequencing data of diabetes to explore the key genera related to its occurrence. Subsequently, participants diagnosed with impaired glucose tolerance (IGT), and healthy subjects, were recruited for fecal and blood sample collection. The dysbiosis of the gut microbiota (GM) and its associated metabolites were analyzed using 16S rDNA sequencing and liquid chromatograph mass spectrometry, respectively. The regulation of gene and protein expression was evaluated through mRNA sequencing and data-independent acquisition technology, respectively. The specific mechanism by which GM dysbiosis affects hyperglycemia and its related vasculopathy was investigated using real-time qPCR, Western blotting, and enzyme-linked immunosorbent assay techniques in HepG2 cells and neutrophils.

Results

Based on the published data, the key alterable genera in the GM associated with diabetes were identified as Blautia, Lactobacillus, Bacteroides, Prevotella, Faecalibacterium, Bifidobacterium, Ruminococcus, Clostridium, and Lachnoclostridium. The related metabolic pathways were identified as cholate degradation and L-histidine biosynthesis. Noteworthy, Blautia and Faecalibacterium displayed similar alterations in patients with IGT compared to those observed in patients with diabetes, and the GM metabolites, tauroursodeoxycholic acid (TUDCA) and carnosine (CARN, a downstream metabolite of histidine and alanine) were both found to be decreased, which in turn regulated the expression of proteins in plasma and mRNAs in neutrophils. Subsequent experiments focused on insulin-like growth factor-binding protein 3 and interleukin-6 due to their impact on blood glucose regulation and associated vascular inflammation. Both proteins were found to be suppressed by TUDCA and CARN in HepG2 cells and neutrophils.

Conclusion

Dysbiosis of the GM occurred throughout the entire progression from IGT to diabetes, characterized by an increase in Blautia and a decrease in Faecalibacterium, leading to reduced levels of TUDCA and CARN, which alleviated their inhibition on the expression of insulin-like growth factor-binding protein 3 and interleukin-6, contributing to the development of hyperglycemia and associated vasculopathy.

Detection of a Thermal Stable-Soluble Protein (TSSP) as a Marker of Peanut Adulteration Using a Highly Sensitive Indirect Enzyme-Linked Immunosorbent Assay based on Monoclonal Antibodies

Food allergy represents a severe problem for many societies, including sensitive populations, academies, health authorities, and the food industry. Peanut allergy occupies a special place in the food allergy spectrum. To prevent consumption by consumers suffering from a peanut allergy, a rapid and sensitive detection method is essential to identify unintended peanut adulteration in processed foods. In this study, we produced four monoclonal antibodies (MAbs; RO 3A1-12, PB 4C12-10, PB 5F9-23, and PB 6G4-30) specific to thermo-stable and soluble proteins (TSSPs) of peanut and developed an enzyme-linked immunosorbent assay (ELISA) based on the MAbs. Among them, PB 5F9-23 MAb was firmly bound to Ara h 1, and other MAbs strongly reacted to Ara h 3 in the Western blot analysis. An antibody cocktail solution of the MAbs was used to enhance the sensitivity of an indirect ELISA, and the limit of detection of the indirect ELISA based on the antibody cocktail solution was 1 ng/ml and improved compared to the indirect ELISA based on the single MAb (11 ng/ml). The cross-reaction analysis revealed the high specificity of developed MAbs to peanut TSSPs without cross-reaction to other food allergens, including nuts. Subsequently, analyzing processed foods by indirect ELISA, all foods labeled as containing peanuts in the product description were confirmed to be positive. The results indicate that the developed antibodies exhibit high specificity and sensitivity to peanuts and can be used as bio-receptors in immunoassays or biosensors to detect intentional or unintentional adulteration of peanuts in processed foods, particularly heat-processed foods.

Development of a simple and reliable LC-MS/MS method to simultaneously detect walnut and almond as specified in food allergen labelling regulations in processed foods

We developed a simple and reliable analytical method using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) to simultaneously detect walnut and almond as specified in regulations for food allergen labelling in processed foods. Five specific target peptides derived from walnut 2S albumin and 7S globulin and three target peptides from almond 11S globulin were selected by analysing several varieties of walnut and almond, eight kinds of other nuts, and ten kinds of major allergen ingredients or cereals. The limit of detection for the walnut 2S albumin peptide GEEMEEMVQSAR (m/z 698.3 [precursor] > 316.1 [product]) was 0.22 ± 0.02 μg/g, and that for almond 11S globulin peptide GNLDFVQPPR (m/z 571.8 [precursor] > 369.2 [product]) was 0.08 ± 0.02 μg/g when extracted walnut and almond protein were spiked into butter cookie chocolate ice cream. These peptides had good linearity (R2 > 0.999) for each calibration curve with a range of 0.1-50 μg/mL protein concentration in the sample solutions, and sufficient recovery rates (90.4-101.5%) from the spiked samples. The developed analytical approach is applicable to a wide variety of processed foods for food allergen labelling.

Development and Validation of a New Robust Detection Method for Low-Content DNA Using ΔΔCq-Based Real-Time PCR with Optimized Standard Plasmids as a Control Sample

Real-time polymerase chain reaction (PCR) is the gold standard for DNA detection in many fields, including food analysis. However, robust detection using a real-time PCR for low-content DNA samples remains challenging. In this study, we developed a robust real-time PCR method for low-content DNA using genetically modified (GM) maize at concentrations near the limit of detection (LOD) as a model. We evaluated the LOD of real-time PCR targeting two common GM maize sequences (P35S and TNOS) using GM maize event MON863 containing a copy of P35S and TNOS. The interlaboratory study revealed that the LOD differed among laboratories partly because DNA input amounts were variable depending on measurements of DNA concentrations. To minimize this variability for low-content DNA samples, we developed ΔΔCq-based real-time PCR. In this study, ΔCq and ΔΔCq are as follows: ΔCq = Cq (P35S or TNOS) – Cq (SSIIb; maize endogenous gene), ΔΔCq = ΔCq (analytical sample) – ΔCq (control sample at concentrations near the LOD). The presence of GM maize was determined based on ΔΔCq values. In addition, we used optimized standard plasmids containing SSIIb, P35S, and TNOS with ΔCq equal to the MON863 genomic DNA (gDNA) at concentrations near the LOD as a control sample. A validation study indicated that at least 0.2% MON863 gDNA could be robustly detected. Using several GM maize certified reference materials, we have demonstrated that this method was practical for detecting low-content GM crops and thus for validating GM food labeling. With appropriate standards, this method would be applicable in many fields, not just food.

Progress on aptamer-based SERS sensors for food safety and quality assessment: methodology, current applications and future trends

It is well known that food safety has aroused extensive attentions from governments to researchers and to food industries. As a versatile technology based on molecular interactions, aptamer sensors which could specifically identify a wide range of food contaminants have been extensively studied in recent years. Surface-enhanced Raman spectroscopy integrated aptamer combines the advantages of both technologies, not only in the ability to specifically identify a wide range of food contaminants, but also in the ultra-high sensitivity, simplicity, portable and speed. To provide beneficial insights into the evaluation techniques in the field of food safety, we offer a comprehensive review on the design strategies for aptamer-SERS sensors in different scenarios, including non-nucleic acid amplification methods ("on/off" mode, sandwich mode, competition model and catalytic model) and nucleic acid amplification methods (hybridization chain reaction, rolling circle amplification, catalytic hairpin assembly). Meanwhile, a special attention is paid to the application of aptamer-SERS sensors in biological (foodborne pathogenic, bacteria and mycotoxins) and chemical contamination (drug residues, metal ions, and food additives) of food matrix. Finally, the challenges and prospects of developing reliable aptamer-SERS sensors for food safety were discussed, which are expected to offer a strong guidance for further development and extended applications.

Recent advances in analytical strategies and microsystems for food allergen detection

Food allergies are abnormal immune responses that typically occur within short period after exposure of certain allergenic proteins in food or food-related resources. Currently, the means to treat food allergies is not clearly understood, and the only known prevention method is avoiding the consumption of allergen-containing foods. From the viewpoint of analytical methods, the effective detection of food allergens is hindered by the effects of various treatment processes and food matrices on trace amounts of allergens. The aim of this effort is to provide the reader with a clear and concise view of new advances for the detection of food allergens. Therefore, the present review explored the development status of various biosensors for the real-time, on-site detection of food allergens with high selectivity and sensitivity. The review also described the analytical consideration for the quantification of food allergens, and global development trends and the future availability of these technologies.

Development of triplex PCR for simultaneous detection of soybean and wheat

There is a constant demand for an effective detection method of major allergens, such as soybean (Glycine max) and wheat (Triticum aestivum). In this study, a triplex polymerase chain reaction (PCR) method was developed for rapid detection of soybean and wheat in processed food products. This triplex PCR contains soybean- and wheat-specific primer pairs and universal primer pair for plant species. Each primer pair was applied to 22 different plant species and showed high specificity with no amplification in non-target species. The sensitivity of triplex PCR for soybean and wheat was 10 pg. The detection limit for soybean and wheat in pea mixture was 0.1%. The developed triplex PCR showed high sensitivity and specificity and was applied to 21 different commercial products. The results were in accordance with the label. Thus, this method is expected to be useful in preventing allergy-related issues via accurate labeling of major allergens in food.

Instant and Multiple DNA Extraction Method by Microneedle Patch for Rapid and on-Site Detection of Food Allergen-Encoding Genes

DNA-based detection methods are highly promising for risk assessment in the food sector, such as tracing the existence of food allergens. However, due to the complexity of food matrices, cumbersome protocols are often needed to isolate the DNA components, which hinder the achievement of rapid and on-site detection. Herein, an instant and multiple DNA extraction method was developed based on the poly(vinyl alcohol) microneedle (MN) patch. With simple press and peel-off operations within 1 min, samples suitable for DNA-based analysis such as polymerase chain reaction (PCR) could be collected. By further combining with the recombinase polymerase amplification assay, rapid screening of the allergenic risks in complex samples such as shrimp ball and cheesecake could be achieved within 30 min. The MN-based DNA extraction method not only was a potential alternative to the traditional DNA extraction method but provided a transformative approach in realizing rapid, on-site detection of foodborne hazards in collaborating with fast DNA-based assays.

Selected Instrumental Techniques Applied in Food and Feed: Quality, Safety and Adulteration Analysis

This review presents an overall glance at selected instrumental analytical techniques and methods used in food analysis, focusing on their primary food science research applications. The methods described represent approaches that have already been developed or are currently being implemented in our laboratories. Some techniques are widespread and well known and hence we will focus only in very specific examples, whilst the relatively less common techniques applied in food science are covered in a wider fashion. We made a particular emphasis on the works published on this topic in the last five years. When appropriate, we referred the reader to specialized reports highlighting each technique's principle and focused on said technologies' applications in the food analysis field. Each example forwarded will consider the advantages and limitations of the application. Certain study cases will typify that several of the techniques mentioned are used simultaneously to resolve an issue, support novel data, or gather further information from the food sample.

Advances on the rapid and multiplex detection methods of food allergens

With the gradually increasing prevalence of food allergy in recent years, food allergy has become a major public health problem worldwide. The clinical symptoms caused by food allergy seriously affect people's quality of life; there are unknown allergen components in novel food and hidden allergens caused by cross contamination in food processing, which pose a serious risk to allergy sufferers. Thus, rapid and multiplex detection methods are required to achieve on-site detection or examination of allergic components, so as to identify the risk of allergy in time. This paper reviews the progress of high-efficiency detection of food allergens, including enhanced traditional detection techniques and emerging detection techniques with the ability high-throughput detection or screening potential food allergen, such as xMAP, biosensors, biochips, etc. focusing on their sensitivity, applicability of each method in food, along with their pretreatment, advantages, limitation in the application of food analysis. This paper also introduces the challenges faced by these high-efficiency detection technologies, as well as the potential of customized allergen screening methods and rapid on-site detection technology as future research directions.

Visible on-site detection of Ara h 1 by the switchable-linker-mediated precipitation of gold nanoparticles

Biosensors have been widely applied in tests for allergens, but on-site detection remains a challenge. Herein, we proposed a detection procedure for peanut Ara h 1 as a representative allergen, which was extracted from a cookie, thereby minimising the need for any complex pretreatment that was difficult to perform, and enabling the visual detection of the target without the use of analytical equipment. The extraction procedure was performed in less than 30 min using a syringe and filter (0.45 μm). The detection method for Ara h 1 was based on the aggregation of switchable linkers (SL) and gold nanoparticles (AuNP), and the presence of 0.19 mg peanut protein per 30 g of cookie could be confirmed within 30 min based on the AuNP/SL concentration ratio by the precipitation. This proposed procedure could be successfully applied to the detection of a wide range of food allergens.

Development of a simple and reliable high-performance liquid chromatography-tandem mass spectrometry approach to simultaneously detect grains specified in food allergen labeling regulation on processed food commodities

An analytical approach using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed to simultaneously detect Fagopyrum esculentum Moench (buckwheat) and cereals containing gluten (Triticum species including wheat and spelt, rye, barley, and oats) that were specified in regulations for food allergen labeling on processed foods. Trypsin-digested peptides were purified from different processed food commodities and heptapeptides derived from buckwheat 13S globulin (GFIVQAR, m/z 395.8 [precursor] > 177.0 [product]) and Triticum low molecular weight glutenin (QIPEQSR, m/z 429.3 [precursor] > 616.2 [product]) were specifically detected each species at levels as low as 0.050-0.056 µg/L and 0.028-0.032 µg/L, respectively. Detection of these synthetic peptides was quantitative to over 100 µg/L by reference to the synthetic peptide calibration curves and at recovery rates, 76.6 ± 4.1%-104.8 ± 17.1% and 82.4 ± 2.0%-105.8 ± 5.3%, for GFIVQAR and QIPEQSR, respectively, when 1-1,000 µg of these peptides were spiked into a retort tomato sauce for pasta or dried instant soup. In combination with LC-MS/MS detection methods specific to other cereals containing gluten (rye, barley, and oats), the developed analytical approach was applicable to a wide variety of processed food commodities for food allergen labeling.

Use of IHF-QD Microscopic Analysis for the Detection of Food Allergenic Components: Peanuts and Wheat Protein

The aim of the study was to analytically evaluate quantum dots in immunohistofluorescence (IHF-QD) microscopic imaging as detectors of food allergens—peanut and wheat. The experiment was designed as two in silico experiments or simulations: (a) models of pastry samples were prepared with the addition of allergenic components (peanut and wheat protein components) and without the addition of allergenic components, and (b) positive and negative commercial samples underwent food allergen detection. The samples from both simulations were tested by the ELISA and IHF-QD microscopic methods. The primary antibodies (secondary antibodies to a rabbit Fc fragment with labeled CdSe/ZnS QD) were labelled at 525, 585, and 655 nm emissions. The use of quantum dots (QDs) has expanded to many science areas and they are also finding use in food allergen detection, as shown in the study. The study indicated that differences between the ELISA and IHF-QD microscopic methods were not observable among experimentally produced pastry samples with and without allergenic components, although differences were observed among commercial samples. The important value of the study is certainly the differences found in the application of different QD conjugates (525, 585, and 655). The highest contrast was found in the application of 585 QD conjugates that can serve for the possible quantification of present food allergens—peanuts and wheat. The study clearly emphasized that QD can be used for the qualitative detection of food allergens and can represent a reliable analytical method for food allergen detection in different food matrixes.