Application of next generation semiconductor based sequencing for species identification and analysis of within-species mitotypes useful for authentication of meat derived products

Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents

Modern food chain supply management necessitates the dire need for mitigating food fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent and systematic review analyses (2018-2023) revealed both destructive and non-destructive methods to demarcate a rational approach for food fraud detection in various countries. These intricate hygiene standards and AI-based technology are also summarized for further prospective research. Chemometrics or AI-based techniques for extensive food fraud detection are demanded. A systematic assessment reveals that various methods to detect food fraud involving multiple substances need to be simple, expeditious, precise, cost-effective, eco-friendly and non-intrusive. The scrutiny resulted in 39 relevant experimental data sets answering key questions. However, additional research is necessitated for an affirmative conclusion in food fraud detection system with modern AI and machine learning approaches.

Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin? A systematic review

Food authentication using molecular techniques is of great importance to fight food fraud. Metabarcoding, based on the next-generation sequencing (NGS) technologies, allowing large-scale taxonomic identification of complex samples via massive parallel sequencing of fragments (called DNA barcodes) simultaneously, has become increasingly popular in many scientific fields. A systematic review to answer the question "Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin?" is presented. The inclusion criteria were focused on the selection of scientific papers (SPs) only applying metabarcoding to foodstuff of animal origin collected on the market. The 23 included SPs were first analyzed with respect to the metabarcoding phases: library preparation (target genes, primer pairs, and fragment length), sequencing (NGS platforms), and final data analysis (bioinformatic pipelines). Given the importance of primer selection, the taxonomic coverage of the used primers was also evaluated. In addition, the SPs were scored based on the use of quality control measures (procedural blanks, positive controls, replicates, curated databases, and thresholds to filter the data). A lack of standardized protocols, especially with respect to the target barcode/s and the universal primer/s, and the infrequent application of the quality control measures, leads to answer that metabarcoding is not ripe enough for authenticating foodstuff of animal origin. However, the observed trend of the SP quality improvement over the years is encouraging. Concluding, a proper protocol standardization would allow a wider use of metabarcoding by both official and private laboratories, enabling this method to become the primary for the authentication of foodstuffs of animal origin.

"Omics" Techniques Used in Marine Biofouling Studies

Biofouling is the growth of organisms on wet surfaces. Biofouling includes micro- (bacteria and unicellular algae) and macrofouling (mussels, barnacles, tube worms, bryozoans, etc.) and is a major problem for industries. However, the settlement and growth of some biofouling species, like oysters and corals, can be desirable. Thus, it is important to understand the process of biofouling in detail. Modern "omic" techniques, such as metabolomics, metagenomics, transcriptomics, and proteomics, provide unique opportunities to study biofouling organisms and communities and investigate their metabolites and environmental interactions. In this review, we analyze the recent publications that employ metagenomic, metabolomic, and proteomic techniques for the investigation of biofouling and biofouling organisms. Specific emphasis is given to metagenomics, proteomics and publications using combinations of different "omics" techniques. Finally, this review presents the future outlook for the use of "omics" techniques in marine biofouling studies. Like all trans-disciplinary research, environmental "omics" is in its infancy and will advance rapidly as researchers develop the necessary expertise, theory, and technology.

Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding

DNA-metabarcoding is becoming more widely used for routine authentication of meat-based food and feed products. Several methods validating species identification methods through amplicon sequencing have already been published. These use a variety of barcodes and analysis workflows, however, no methodical comparison of available algorithms and parameter optimization are published hitherto for meat-based products' authenticity. Additionally, many published methods use very small subsets of the available reference sequences, thereby limiting the potential of the analysis and leading to over-optimistic performance estimates. We here predict and compare the ability of published barcodes to distinguish taxa in the BLAST NT database. We then use a dataset of 79 reference samples, spanning 32 taxa, to benchmark and optimize a metabarcoding analysis workflow for 16S rDNA Illumina sequencing. Furthermore, we provide recommendations as to the parameter choices, sequencing depth, and thresholds that should be used to analyze meat metabarcoding sequencing experiments. The analysis workflow is publicly available, and includes ready-to-use tools for validation and benchmarking.

Omics-Based Analytical Approaches for Assessing Chicken Species and Breeds in Food Authentication

Chicken is known to be the most common meat type involved in food mislabeling and adulteration. Establishing a method to authenticate chicken content precisely and identifying chicken breeds as declared in processed food is crucial for protecting consumers' rights. Categorizing the authentication method into their respective omics disciplines, such as genomics, transcriptomics, proteomics, lipidomics, metabolomics, and glycomics, and the implementation of bioinformatics or chemometrics in data analysis can assist the researcher in improving the currently available techniques. Designing a vast range of instruments and analytical methods at the molecular level is vital for overcoming the technical drawback in discriminating chicken from other species and even within its breed. This review aims to provide insight and highlight previous and current approaches suitable for countering different circumstances in chicken authentication.

Application of Next Generation Semiconductor-Based Sequencing for the Identification of Apis mellifera Complementary Sex Determiner (csd) Alleles from Honey DNA

Simple Summary

Honey contains traces of the DNA of the honey bees that produced it. This environmental DNA can therefore be used to investigate the genome of the honey bees. In this study, we used a next generation sequencing technology to analyze the variability of a key gene of Apis mellifera L., the complementary sex determiner (csd) gene, using honey environmental DNA as a source of honey bee DNA. This gene determines the sex of the bees. Two different alleles at this locus are needed to produce females whereas males have only one copy of this gene as they are haploid. In case two identical alleles are present in a diploid individual, the larvae are not vital and are discarded by the workers. Therefore, there is an advantage in maintaining a large csd diversity in honey bee populations. In light of the recent decline in honey bee populations, it is important to monitor the allele variability at this gene. The applied methodology provided a new strategy to disclose the genetic diversity at the csd gene at the population-wide level and identify most, if not all, csd alleles present in the colonies in a single analysis.

Abstract

The complementary sex determiner (csd) gene plays an essential role in the sex determination of Apis mellifera L. Females develop only if fertilized eggs have functional heterozygous genotypes at this gene whereas males, being haploids, are hemizygous. Two identical csd alleles produce non vital males. In light of the recent decline in honey bee populations, it is therefore important to monitor the allele variability at this gene. In this study, we tested the application of next generation semiconductor-based sequencing technology (Ion Torrent) coupled with environmental honey DNA as a source of honey bee genome information to retrieve massive sequencing data for the analysis of variability at the hypervariable region (HVR) of the csd gene. DNA was extracted from 12 honey samples collected from honeycombs directly retrieved from 12 different colonies. A specifically designed bioinformatic pipeline, applied to analyze a total of about 1.5 million reads, identified a total of 160 different csd alleles, 55% of which were novel. The average number of alleles per sample was compatible with the number of expected patrilines per colony, according to the mating behavior of the queens. Allele diversity at the csd could also provide information useful to reconstruct the history of the honey.

Application of DNA barcoding and metabarcoding for species identification in salmon products

Mislabelling is a significant manifestation of food fraud. Traditional Sanger sequencing technology is the gold standard for seafood species identification. However, this method is not suitable for analysing processed samples that may contain more than one species. This study tested the feasibility of next-generation sequencing in identifying mixed salmon products. Salmon samples containing up to eight species were amplified using 16S rRNA mini-barcode primers, and sequenced on an Illumina HiSeq2500 platform. All species were accurately identified, and mixtures as low as 1% (w/w) could be detected. Furthermore, this study conducted a market survey of 32 products labelled as salmon. For pure and mixed fish products, Sanger and next-generation sequencing techniques were respectively used for species identification, and for NGS results, we also used real-time PCR method to cross-validate the mixed products to further verify the accuracy of the DNA metabarcoding technology established in this study. DNA barcoding and metabarcoding of commercial salmon food products revealed the presence of mislabelling in 16 of 32 (50%) samples. The developed DNA barcoding and metabarcoding methods are useful for the identification of salmon species in food and can be used for quality control of various types of salmon products.

Detection of porcine-derived ingredients from adulterated meat based on real-time loop-mediated isothermal amplification

Increasingly globalized and complex food supply chains contribute to a growing problem of meat fraud. Meat adulteration with pork is especially exceptionable to the global population for health concern and religious faith reasons. To prevent unfair competition and protect consumer rights, an efficient and rapid assay to identify the species of meat products is crucial. In this study, a real-time loop-mediated isothermal amplification (real-time LAMP) assay was developed for the detection of a porcine gene in meat products. The designed primers were highly selective for the porcine gene. The amplification showed no cross-reactivity with 11 other meats. The established method required 20 min with an initial amplification curve of approximately 10 min and demonstrated a detection limit of 1.76 pg/μL porcine DNA, which is 1000 times more sensitive than PCR. This study is the first attempt at detecting porcine-derived ingredients using a real-time LAMP assay in commercial products. This method meets specificity, rapidness, robustness, and sensitivity criteria; its practical application will greatly aid in battling adulteration in the food industry.

Current analytical methods for porcine identification in meat and meat products

Authentication of meat products is critical in the food industry. Meat adulteration may lead to religious apprehensions, financial gain and food-toxicities such as meat allergies. Thus, empirical validation of the quality and constituents of meat is paramount. Various analytical methods often based on protein or DNA measurements are utilized to identify meat species. Protein-based methods, including electrophoretic and immunological techniques, are at times unsuitable for discriminating closely related species. Most of these methods have been replaced by more accurate and sensitive detection methods, such as DNA-based techniques. Emerging technologies like DNA barcoding and mass spectrometry are still in their infancy when it comes to their utilization in meat detection. Gold nanobiosensors have shown some promise in this regard. However, its applicability in small scale industries is distant. This article comprehensively reviews the recent developments in the field of analytical methods used for porcine identification.