Development and optimization of an efficient qPCR system for olive authentication in edible oils

Development and Application of a TaqMan RT-qPCR for the Detection of Foot-and-Mouth Disease Virus in Pigs

The global livestock industry is facing a serious threat from a widespread foot-and-mouth disease virus (FMDV) epidemic. The timely detection of FMDV can significantly mitigate its harmful effects. This study aimed to establish and evaluate a TaqMan fluorescence quantitative PCR assay to assess its sensitivity, specificity, reproducibility, and stability. The standard curve equation range is 6.43 × 109-6.43 × 101 copies/µL, with an R2 value of 0.996 and a standard curve equation of y = -3.586x + 36.245. The method successfully detected 64.3 copies/µL of the target gene for FMDV and exhibited high specificity for FMDV. Repeatability tests demonstrated low coefficients of variation within and between groups (<2%), indicating good reproducibility. The clinical samples analyzed using this method showed results consistent with those of the SYBR Green I RT-qPCR assay, confirming the reliability of the method. Overall, the developed test method displayed high sensitivity, specificity, reproducibility, and stability, making it suitable for the rapid diagnosis of foot-and-mouth disease in clinical settings.

Detection of Hazelnut and Almond Adulteration in Olive Oil: An Approach by qPCR

Virgin olive oil (VOO), characterized by its unique aroma, flavor, and health benefits, is subject to adulteration with the addition of oils obtained from other edible species. The consumption of adulterated olive oil with nut species, such as hazelnut or almond, leads to health and safety issues for consumers, due to their high allergenic potential. To detect almond and hazelnut in olive oil, several amplification systems have been analyzed by qPCR assay with a SYBR Green post-PCR melting curve analysis. The systems selected were Cora1F2/R2 and Madl, targeting the genes coding the allergenic protein Cor a 1 (hazelnut) and Pru av 1 (almond), respectively. These primers revealed adequate specificity for each of the targeted species. In addition, the result obtained demonstrated that this methodology can be used to detect olive oil adulteration with up to 5% of hazelnut or almond oil by a single qPCR assay, and with a level as low as 2.5% by a nested-qPCR assay. Thus, the present research has shown that the SYBR-based qPCR assay can be a rapid, precise, and accurate method to detect adulteration in olive oil.

Study on detection of soybean components in edible oil with ladder-shape melting temperature isothermal amplification (LMTIA) assay

A ladder-shape melting temperature isothermal amplification (LMTIA) assay was established and used to detect soybean components in edible oils. LMTIA primers were designed with the sequence of the internal transcribed spacer (ITS) gene as the target, the reaction temperatures were optimized, the sensitivity was determined, and the suitability of the DNA extraction method for edible oil was assessed, with H₂O and genomic DNA (gDNA) from corn, rapeseed, cottonseed, sesame, chili, chicken, pork, beef, and mutton as negative controls to test the false positives of the LMTIA assay. The established LMTIA assay gave a sensitivity of 1 pg at an optimal temperature of 57 °C. The Edible Oil DNA Extraction Kit was suitable for the LMTIA assay to detect soybean components in refined plant oil. No false positives occurred from all negative controls. This study successfully established the LMTIA assay for the detection of soybean ITS genes in edible oils, which could be used to detect soybean components in edible oils.

Stepwise Optimization of Real-Time RT-PCR Analysis

Quantitative real-time reverse transcription PCR (qRT-PCR) analysis has been used routinely to quantify gene expression levels. Primer design and the optimization of qRT-PCR parameters are critical for the accuracy and reproducibility of qRT-PCR analysis. Computational tool-assisted primer design often overlooks the presence of homologous sequences of the gene of interest and the sequence similarities between homologous genes in a plant genome. This sometimes results in skipping the optimization of qRT-PCR parameters due to the false confidence in the quality of the designed primers. Here we present a stepwise optimization protocol for single nucleotide polymorphisms (SNPs)-based sequence-specific primer design and sequential optimization of primer sequences, annealing temperatures, primer concentrations, and cDNA concentration range for each reference and target gene. The goal of this optimization protocol is to achieve a standard cDNA concentration curve with an R² ≥ 0.9999 and efficiency (E) = 100 ± 5% for the best primer pair of each gene, which serves as the prerequisite for using the 2^-ΔΔCT method for data analysis.

Integration of lipidomics and metabolomics for the authentication of camellia oil by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry coupled with chemometrics

The integration of lipidomics and metabolomics approaches, based on UPLC-QTOF-MS technology coupled with chemometrics, was established to authenticate camellia oil adulterated with rapeseed oil, peanut oil, and soybean oil. Lipidomics revealed that the glyceride profile provides a prospective authentication of camellia oil, but no characteristic markers were available. Sixteen characteristic markers were identified by metabolomics. For camellia oil, all six markers were sapogenins of oleanane-type triterpene saponins. Lariciresinol, sinapic acid, doxercalciferol, and an unknown compound were identified as markers for rapeseed oil. Characteristic markers in peanut oil were formononetin, sativanone, and medicarpin. In the case of soybean oil, the characteristic markers were dimethoxyflavone, daidzein, and genistein. The established OPLS-DA and OPLS prediction models were highly accurate in the qualitative and quantitative analyses of camellia oil adulterated with 5% other oils. These results indicate that the integration of lipidomics and metabolomics approaches has great potential for the authentication of edible oils.

An optimized protocol for stepwise optimization of real-time RT-PCR analysis

Computational tool-assisted primer design for real-time reverse transcription (RT) PCR (qPCR) analysis largely ignores the sequence similarities between sequences of homologous genes in a plant genome. It can lead to false confidence in the quality of the designed primers, which sometimes results in skipping the optimization steps for qPCR. However, the optimization of qPCR parameters plays an essential role in the efficiency, specificity, and sensitivity of each gene's primers. Here, we proposed an optimized approach to sequentially optimizing primer sequences, annealing temperatures, primer concentrations, and cDNA concentration range for each reference (and target) gene. Our approach started with a sequence-specific primer design that should be based on the single-nucleotide polymorphisms (SNPs) present in all the homologous sequences for each of the reference (and target) genes under study. By combining the efficiency calibrated and standard curve methods with the 2^-ΔΔCt method, the standard cDNA concentration curve with a logarithmic scale was obtained for each primer pair for each gene. As a result, an R² ≥ 0.9999 and the efficiency (E) = 100 ± 5% should be achieved for the best primer pair of each gene, which serve as the prerequisite for using the 2^-ΔΔCt method for data analysis. We applied our newly developed approach to identify the best reference genes in different tissues and at various inflorescence developmental stages of Tripidium ravennae, an ornamental and biomass grass, and validated their utility under varying abiotic stress conditions. We also applied this approach to test the expression stability of six reference genes in soybean under biotic stress treatment with Xanthomonas axonopodis pv. glycines (Xag). Thus, these case studies demonstrated the effectiveness of our optimized protocol for qPCR analysis.

Authentication of olive oil based on DNA analysis

Olive oil, which has been produced mainly in the Mediterranean area since the ancient times, has a high nutritional value linked to many health benefits. Extra virgin, which is the purest form of olive oil, has excellent quality and premium prices. Many cases of adulteration and fraud necessitate the development of reliable and accurate methods for olive oil authentication. DNA-based methods analyze the residual DNA extracted from olive oil and use molecular markers for genetic identification of different species, subspecies or cultivars because these markers act as signs which reflect distinct genetic profiles. This study reviews the process by which DNA from olive oil is extracted and analyzed by the most recently used markers in the authentication of olive oil, such as Simple Sequence Repeats (SSR) or microsatellites and the single nucleotide polymorphisms (SNPs). Methods of analysis such as qPCR and digital PCR are also discussed with a special emphasis placed on the method of High-Resolution Melting (HRM), a post-polymerase chain reaction method, which enables rapid, high performing identification of genetic variants in the DNA regions of interest without sequencing, and may differentiate very similar cultivars which differ in only one nucleotide in a specific locus.

Varietal Authentication of Extra Virgin Olive Oils by Triacylglycerols and Volatiles Analysis

In recent years, there is an increasing interest in high-quality extra virgin olive oils (EVOOs) produced from local cultivars. They have particular chemical/organoleptic characteristics and are frequently subjected to fraud, whereby the control of quality requires a powerful varietal check. In the present research, triacylglycerols (TAGs) and volatiles have been studied as chemical markers for the authentication of EVOO samples from four Italian varieties of Olea europea (Dolce Agogia, Frantoio, Leccino, and Moraiolo). The monocultivar EVOO samples have been subjected to a chemical⁻enzymatic chromatographic method in order to perform a stereospecific analysis, an important procedure for the characterization of TAG of food products. The results, combined with chemometric analysis (linear discriminant analysis, LDA), were elaborated in order to classify Italian EVOO monocultivar samples. In accordance with the total and intrapositional fatty acid (FA) composition of TAG fraction, the results were allowed to carry out a varietal discrimination. In addition, volatile compounds were also determined by solid-phase micro-extraction gas chromatography⁻mass spectrometry analysis. All EVOO samples were correctly classified when TAG stereospecific data and volatile results were elaborated by the LDA procedure, even if volatile compounds showed a higher discriminant power.

Hue Parameter Fluorescence Identification of Edible Oils with a Smartphone

Food fraud can be highly lucrative, and high accuracy authentication of various foodstuffs is becoming essential. Olive oil is one of the most investigated food matrices, due to its high price and low production globally, with recent food fraud examples showing little or no high quality olive oil in the tested oils. Here a simple method using a 405 nm LED flashlight and a smartphone is developed for edible oil authentication. Identification is fingerprinted by intrinsic fluorescent compounds in the oils, such as chlorophylls and polyphenols. This study uses the hue parameter of HSV-colorspace to authenticate 24 different edible oils of 9 different types and 15 different brands. For extra virgin olive oil, all nine samples are well separated from the other oil samples. The rest of the samples were also well type-distinguished by the hue parameter, which is complemented by hue-histogram analysis. This opens up opportunities for low-cost and high-throughput smartphone field-testing of edible oils on all levels of the production and supply chain.