Simultaneous authentication of species identity and geographical origin of shrimps: Untargeted metabolomics to recurrent biomarker ions

Proteomics integrated with metabolomics: Analysis of the internal mechanism underlying changes in meat quality in different muscles from bactrian camels

Knowledge about the quality of meat obtained from different muscles is crucial for developing high-quality camel meat for commercial use. Metabolomic and proteomic profiles of the longissimus thoracic (LT), semitendinosus (ST), and psoas major (PM) muscles of the bactrian camel, which significantly vary in aspects such as intramuscular fat (IMF) content and shear force, were comprehensively compared to evaluate the impact of these changes on meat quality. Compared with ST and PM muscles, LT muscles had higher IMF content, were more tender, and had a lower shear force. Proteomic analysis unveiled significant differences in metabolic enzymes and binding proteins among different muscles. Based on correlation analysis, 20 key proteins and metabolites closely related to meat quality were screened. Integration of proteomic and metabolomic data highlighted oxidative phosphorylation, TCA cycle, and glycolysis as key distinguishing pathways among different muscles. These results offer effective information for producing high-quality camel meat.

Direct analysis and identification of the intestinal microflora of shrimps for their geographical traceability via mass spectrometry and bacterial library searching

The expansion of the seafood market has led to an increased probability of food fraud. The development of rapid and reliable traceability methods for aquatic food products is of utmost importance. In this study, direct analysis and identification of the intestinal microbiota of aquatic foods were conducted. The validity of using BacteriaMS database searching for the identification of bacteria was assessed and demonstrated through analyzing prepared bacterial mixtures. We focused on shrimp as a model for aquatic food products and utilized matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze the intestinal microflora of Chinese shrimp (Fenneropenaeus chinensis) collected from three different aquaculture farms in China. It was found that the most dominant bacteria found in shrimps' intestines could serve as a basis for distinguishing shrimps' geographical origin. The most dominant bacteria in the intestines varied among shrimps from different origins but remained identical for shrimps from the same origin. The reliability of the method in tracing the geographic origin of aquatic products was further validated by analysis of black tiger shrimp (Penaeus monodon) from different origins. The findings show that the utilization of MALDI-TOF MS for the analysis of the microbial community in the intestines of shrimp samples combined with bacterial library searching can offer a rapid, accurate, and feasible method that can be employed for determining shrimps' geographical origin. The present protocol was successfully utilized for the traceability of origins of Chinese shrimp (Fenneropenaeus chinensis) and black tiger shrimp (Penaeus monodon). It is promising to extend the present protocol to other aquatic products with regional characteristics to help combat food fraud in the aquatic product market.

Foodomics as a Tool for Evaluating Food Authenticity and Safety from Field to Table: A Review

The globalization of the food industry chain and the increasing complexity of the food supply chain present significant challenges for food authenticity and raw material processing. Food authenticity identification now extends beyond mere adulteration recognition to include quality evaluation, label compliance, traceability determination, and other quality-related aspects. Consequently, the development of high-throughput, accurate, and rapid analytical techniques is essential to meet these diversified needs. Foodomics, an innovative technology emerging from advancements in food science, enables both a qualitative judgment and a quantitative analysis of food authenticity and safety. This review also addresses crucial aspects of fully processing food, such as verifying the origin, processing techniques, label authenticity, and detecting adulterants, by summarizing the omics technologies of proteomics, lipidomics, flavoromics, metabolomics, genomics, and their analytical methodologies, recent developments, and limitations. Additionally, we analyze the advantages and application prospects of multi-omics strategies. This review offers a comprehensive perspective on the food chain, food safety, and food processing from field to table through omics approaches, thereby promoting the stable and sustained development of the food industry.

Variations in metabolite fingerprints of Tinospora species targeting metabolic disorders: an integrated metabolomics and network pharmacology approach

INTRODUCTION

Metabolic disorders are a global health concern, necessitating the development of drugs with fewer side effects and more efficacy. Traditional Indian medicine uses Tinospora cordifolia and Tinospora sinensis, but their metabolite fingerprints and impact on geographical location remains unknown.

OBJECTIVE

The present study aimed to identify metabolite fingerprints from T. cordifolia and T. sinensis species from different geographic locations and also to identify potential quality markers for treating metabolic disorders.

METHODS

Non-targeted metabolite fingerprinting of T. cordifolia and T. sinensis was performed using HPLC-QTOF-MS/MS analysis. Network pharmacology, molecular docking and molecular dynamics simulation analysis were performed to identify potential quality markers, hub targets, and key pathways associated with metabolic disorders.

RESULTS

In this study, six potential marker compounds and twenty-five differential compounds were identified between T. cordifolia and T. sinensis. Based on geography, five and one metabolite marker compounds were identified in T. cordifolia and T. sinensis respectively. Network pharmacology, molecular docking, and molecular dynamics simulation analysis revealed trans piceid, crustecdysone in T. cordifolia, and gallic acid in T. sinensis as potential quality markers against metabolic disorder related hub targets.

CONCLUSION

Integration of non-targeted metabolomics and network pharmacology approach deciphers the pharmacological mechanism of action in terms of identifying potential quality markers from Tinospora species that can be used against metabolic disorders. However, further research is required to validate these findings in in vitro and in vivo studies for better assertion.

A review of the emerging technologies and systems to mitigate food fraud in supply chains

Food fraud has serious consequences including reputational damage to businesses, health and safety risks and lack of consumer confidence. New technologies targeted at ensuring food authenticity has emerged and however, the penetration and diffusion of sophisticated analytical technologies are faced with challenges in the industry. This review is focused on investigating the emerging technologies and strategies for mitigating food fraud and exploring the key barriers to their application. The review discusses three key areas of focus for food fraud mitigation that include systematic approaches, analytical techniques and package-level anti-counterfeiting technologies. A notable gap exists in converting laboratory based sophisticated technologies and tools in high-paced, live industrial applications. New frontiers such as handheld laser-induced breakdown spectroscopy (LIBS) and smart-phone spectroscopy have emerged for rapid food authentication. Multifunctional devices with hyphenating sensing mechanisms together with deep learning strategies to compare food fingerprints can be a great leap forward in the industry. Combination of different technologies such as spectroscopy and separation techniques will also be superior where quantification of adulterants are preferred. With the advancement of automation these technologies will be able to be deployed as in-line scanning devices in industrial settings to detect food fraud across multiple points in food supply chains.

Impact of the rearing environment on the metabolism of shrimps and tracing the origins and species of shrimps using specific metabolites

Herein, the link between rearing environmental condition and metabolism was explored. Metabolite fingerprint datasets of black tiger shrimp (Penaeus monodon) from three production sites were collected and studied using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and HPLC-MS/MS. Two compounds, benzisothiazolinone and hippuric acid, were identified to be potentially related to pollution in the rearing environment and showed different abundances in the analysed shrimp samples with different origins. Furthermore, metabolomic analysis on three shrimp species, black tiger shrimp, kuruma shrimp (Penaeus japonicus) and sword shrimp (Parapenaeopsis hardwickii), under an identical rearing environment was also conducted. Two compounds, diethanolamine and benzisothiazolinone, potentially linked with pollution in the rearing environment were identified. The present protocol holds promise to be extended to the studies of exploring the relationship between rearing environmental conditions and metabolism. Furthermore, the analysis of single-blind samples was conducted. The results show that specific metabolites can be utilized as markers for tracing the origins of shrimp samples. The present protocol holds potential for application in tracing the origin and species of certain seafoods.

Comparison of the Metabolomics of Different Dendrobium Species by UPLC-QTOF-MS

Dendrobium Sw. (family Orchidaceae) is a renowned edible and medicinal plant in China. Although widely cultivated and used, less research has been conducted on differential Dendrobium species. In this study, stems from seven distinct Dendrobium species were subjected to UPLC-QTOF-MS/MS analysis. A total of 242 metabolites were annotated, and multivariate statistical analysis was employed to explore the variance in the extracted metabolites across the various groups. The analysis demonstrated that D. nobile displays conspicuous differences from other species of Dendrobium. Specifically, D. nobile stands out from the remaining six taxa of Dendrobium based on 170 distinct metabolites, mainly terpene and flavonoid components, associated with cysteine and methionine metabolism, flavonoid biosynthesis, and galactose metabolism. It is believed that the variations between D. nobile and other Dendrobium species are mainly attributed to three metabolite synthesis pathways. By comparing the chemical composition of seven species of Dendrobium, this study identified the qualitative components of each species. D. nobile was found to differ significantly from other species, with higher levels of terpenoids, flavonoids, and other compounds that are for the cardiovascular field. By comparing the chemical composition of seven species of Dendrobium, these qualitative components have relevance for establishing quality standards for Dendrobium.

Identification of animal species of origin in meat based on glycopeptide analysis by UPLC-QTOF-MS

Adulteration of meat and meat products causes a concerning threat for consumers. It is necessary to develop novel robust and sensitive methods which can authenticate the origin of meat species to compensate for the drawbacks of existing methods. In the present study, the sarcoplasmic proteins of six meat species, namely, pork, beef, mutton, chicken, duck and turkey, were analyzed by one-dimensional gel electrophoresis. It was found that enolase could be used as a potential biomarker protein to distinguish between livestock and poultry meats. The glycosylation sites and glycans of enolase were analyzed by UPLC-QTOF-MS and a total of 41 glycopeptides were identified, indicating that the enolase N-glycopeptide profiles of different meats were species-specific. The identification models of livestock meat, poultry and mixed animal were established based on the glycopeptide contents, and the explanation degree of the three models was higher than 90%. The model prediction performance and feasibility results showed that the average prediction accuracy of the three models was 75.43%, with the animal-derived meat identification model showing superiority in identifying more closely related species. The obtained results indicated that the developed strategy was promising for application in animal-derived meat species monitoring and the quality supervision of animal-derived food.

Metabolomics as a tool for geographic origin assessment of roasted and green coffee beans

Coffee is widely consumed across the globe. The most sought out varieties are Arabica and Robusta which differ significantly in their aroma and taste. Furthermore, varieties cultivated in different regions are perceived to have distinct characteristics encouraging some producers to adopt the denomination of origin label. These differences arise from variations on metabolite content related to edaphoclimatic conditions and post-harvest management among other factors. Although sensory analysis is still standard for coffee brews, instrumental analysis of the roasted and green beans to assess the quality of the final product has been encouraged. Metabolomic profiling has risen as a promising approach not only for quality purposes but also for geographic origin assignment. Many techniques can be applied for sample analysis: chromatography, mass spectrometry, and NMR have been explored. The data collected is further sorted by multivariate analysis to identify similar characteristics among the samples, reduce dimensionality and/or even propose a model for predictive purposes. This review focuses on the evolution of metabolomic profiling for the geographic origin assessment of roasted and green coffee beans in the last 21 years, the techniques that are usually applied for sample analysis and also the most common approaches for the multivariate analysis of the collected data. The prospect of applying a wide range of analytical techniques is becoming an unbiased approach to determine the origin of different roasted and green coffee beans samples with great correlation. Predictive models worked accurately for the geographic assignment of unknown samples once the variety was known.

Comprehensive Metabolite Profiling of Two Edible Garcinia Species Based on UPLC-ESI-QTOF-MSE Coupled with Bioactivity Assays

In China, the endemic species Garcinia yunnanensis and native Garcinia xanthochymus are known as edible and medicinal plants. However, a systematic metabolomic and bioactivity evaluation of different plant parts from both species is lacking. In this study, comprehensive investigations of 11 plant parts of G. yunnanensis and 10 of G. xanthochymus employing UPLC-ESI-QTOF-MS^E-based metabolomic analysis in conjunction with three bioactivity assays were undertaken. A customized chemotaxonomic-based in-house library containing 6456 compounds was constructed and coupled to the Progenesis QI informatic platform for metabolite annotations. From these two species, a total of 235 constituents were characterized using multiple criteria. Differences in metabolite profiles between the plant parts within each species were uncovered using multivariate analysis. Based on orthogonal partial least-squares discriminant analysis (OPLS-DA), 23 markers were identified as highly differential metabolites from G. xanthochymus and 20 from G. yunnanensis. Comparative assessment of the biological assays revealed the activity variations among different plant parts. The seeds of both species and G. yunnanensis latex exhibited excellent cytotoxic and antibacterial activities, while G. xanthochymus roots and G. yunnanensis arils showed strong anti-inflammatory effects. S-plot analysis identified 26 potential biomarkers for the observed activities, including the known cytotoxic agent cycloxanthochymol and the anti-inflammatory compound garcimultiflorone B, which likely explains some of the potent observed bioactivity.

The use of various statistical methods for authenticity and detection of adulteration in fish and seafood

Various methodologies including genetic analyses, morphometrics, proteomics, lipidomics, metabolomics, etc. are now used or being developed to authenticate fish and seafood. Such techniques usually lead to the generation of enormous amounts of data. The analysis and interpretation of this information can be particularly challenging. Statistical techniques are therefore commonly used to assist in analyzing these data, visualizing trends and differences and extracting conclusions. This review article aims at presenting and discussing statistical methods used in studies on fish and seafood authenticity and adulteration, allowing researchers to consider their options based on previous successes/failures but also offering some recommendations about the future of such techniques. Techniques such as PCA, AMOVA and FST statistics, that allow the differentiation of genetic groups, or techniques such as MANOVA that allow large data sets of morphometric characteristics or elemental differences to be analyzed are discussed. Furthermore, methods such as cluster analysis, DFA, CVA, CDA and heatmaps/Circos plots that allow samples to be differentiated based on their geographical origin are also reviewed and their advantages and disadvantages as found in past studies are given. Finally, mathematical simulations and modeling are presented in a detailed review of studies using them, together with their advantages and limitations.

Discrimination of Geographical Origin of Agricultural Products From Small-Scale Districts by Widely Targeted Metabolomics With a Case Study on Pinggu Peach

Geographical indications of agricultural products are characterized by high quality and regional attributes, while they are more likely to be counterfeited by similar products from nearby regions. Accurate discrimination of origin on small geographical scales is extremely important for geographical indications of agricultural products to avoid food fraud. In this study, a widely targeted metabolomics based on ultra-high-performance liquid chromatography-tandem mass spectrometry combined with multivariate statistical analysis was used to distinguish the geographical origin of Pinggu Peach of Beijing and its two surrounding areas in Heibei province (China). Orthogonal partial least squares-discriminant analysis (OPLS-DA) based on 159 identified metabolites showed significant separation from Pinggu and the other adjacent regions. The number of the most important discriminant variables (VIP value >1) was up to 62, which contributed to the differentiation model. The results demonstrated that the metabolic fingerprinting combined with OPLS-DA could be successfully implemented to differentiate the geographical origin of peach from small-scale origins, thus providing technical support to further ensure the authenticity of geographical indication products. The greenness of the developed method was assessed using the Analytical GREEnness Metric Approach and Software (ARGEE) tool. It was a relatively green analytical method with room for improvement.

Comparative metabolite fingerprinting of chia, flax and sesame seeds using LC-MS untargeted metabolomics

Chia, flax, and sesame seeds are well known for their nutritional quality and are commonly included in bakery products. So far, the development of methods to verify their presence and authenticity in foods is a requisite and a raised need. In this work we applied untargeted metabolomics to propose authenticity markers. Seeds were analyzed by HPLC-MS/MS and 9938 features in negative mode and 9044 in positive mode were obtained by Mzmine. After isotopes grouping, alignment, gap-filling, filtering adducts, and normalization, PCA was applied to explore the dataset and recognize pre-existent classification patterns. OPLS-DA analysis and S-Plots were used as supervised methods. Twenty-five molecules (12 in negative mode and 13 in positive mode) were selected as discriminant for the three seeds, polyphenols and lignans were identified among them. To the best of our knowledge, this is the first approach using non-target HPLC-MS/MS for the authentication of chia, flax and sesame seeds.

Application of the Metabolomics Approach in Food Authentication

The authentication of food products is essential for food quality and safety. Authenticity assessments are important to ensure that the ingredients or contents of food products are legitimate and safe to consume. The metabolomics approach is an essential technique that can be utilized for authentication purposes. This study aimed to summarize food authentication through the metabolomics approach, to study the existing analytical methods, instruments, and statistical methods applied in food authentication, and to review some selected food commodities authenticated using metabolomics-based methods. Various databases, including Google Scholar, PubMed, Scopus, etc., were used to obtain previous research works relevant to the objectives. The review highlights the role of the metabolomics approach in food authenticity. The approach is technically implemented to ensure consumer protection through the strict inspection and enforcement of food labeling. Studies have shown that the study of metabolomics can ultimately detect adulterant(s) or ingredients that are added deliberately, thus compromising the authenticity or quality of food products. Overall, this review will provide information on the usefulness of metabolomics and the techniques associated with it in successful food authentication processes, which is currently a gap in research that can be further explored and improved.

Current State of Metabolomics Research in Meat Quality Analysis and Authentication

In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.

High performance liquid chromatography fingerprint and headspace gas chromatography-mass spectrometry combined with chemometrics for the species authentication of Curcumae Rhizoma

Curcumae Rhizoma (Ezhu), a multi-origin Chinese medicine, originates from the dry rhizomes of C. kwangsiensis, C. phaeocaulis and C. wenyujin. The three species have great variation in chemical components and therapeutic effects. To improve safety and effectiveness in clinical use, a strategy integrating chromatographic analysis and chemometrics for the species authentication of Ezhu was proposed. Firstly, systematic analysis of chemical compositions in Ezhu was achieved using high performance liquid chromatography (HPLC) fingerprint and headspace gas chromatography-mass spectrometry (HS-GC-MS). HPLC fingerprints showed that seventeen peaks in common for C. kwangsiensis and eleven peaks in common for C. wenyujin both presented a good similarity (> 0.9, only several samples < 0.8). Eleven common peaks in C. phaeocaulis and the similarity values of most samples were higher than 0.700. Additionally, there were ten common peaks in all Ezhu samples and they had relatively poor similarity with the correlation coefficients ranging from 0.364 to 0.881. For HS-GC-MS, thirty-six volatile components were identified in the three species of Ezhu, mainly monoterpenes and sesquiterpenes. Subsequently, chemometrics including unsupervised principal component analysis (PCA), supervised linear discriminant analysis (LDA), K-nearest neighbors (KNN), back propagation neural network (BP-NN) and orthogonal partial least squares-discrimination analysis (OPLS-DA) was applied to extract useful information from chromatographic profiles. Based on HPLC fingerprint data, PCA could hardly differentiate Ezhu with the three species, and LDA, KNN and BP-NN models provided more than 85 % correct identification. With HS-GC-MS data, PCA could only distinguish C. wenyujin from the other two species, and LDA, KNN, BP-NN and OPLS-DA models achieved excellent classification with 100 % accuracy. Finally, five volatile components (eucalyptol, humulene, β-elemene, (+)-2-bornanone and linalool) with variable importance for the projection (VIP) values higher than 1 in the OPLS-DA model were selected as potential chemical markers for the species authentication of Ezhu. And the constructed OPLS-DA model using these markers obtained 100 % accuracy. Consequently, a rapid, precise and feasible strategy was established for the discrimination and quality control of Ezhu with different species.

The use of molecular markers in the verification of fish and seafood authenticity and the detection of adulteration

The verification of authenticity and detection of food mislabeling are elements that have been of high importance for centuries. During the last few decades there has been an increasing consumer demand for the verification of food identity and the implementation of stricter controls around these matters. Fish and seafood are among the most easily adulterated foodstuffs mainly due to the significant alterations of the species' morphological characteristics that occur during the different types of processing, which render the visual identification of the animals impossible. Even simple processes, such as filleting remove very important morphological elements and suffice to prevent the visual identification of species in marketed products. Novel techniques have therefore been developed that allow identification of species, the differentiation between species and also the differentiation of individuals that belong to the same species but grow in different populations and regions. Molecular markers have been used during the last few decades to fulfill this purpose and several improvements have been implemented rendering their use applicable to a commercial scale. The reliability, accuracy, reproducibility, and time-and cost-effectiveness of these techniques allowed them to be established as routine methods in the industry and research institutes. This review article aims at presenting the most important molecular markers used for the authentication of fish and seafood. The most important techniques are described, and the results of numerous studies are outlined and discussed, allowing interested parties to easily access and compare information about several techniques and fish/seafood species.

Untargeted Metabolomics and Targeted Quantitative Analysis of Temporal and Spatial Variations in Specialized Metabolites Accumulation in Poria cocos (Schw.) Wolf (Fushen)

Poria cocos (Schw.) Wolf is a saprophytic fungus that grows around the roots of old, dead pine trees. Fushen, derived from the sclerotium of P. cocos but also containing a young host pine root, has been widely used as a medicine and food in China, Japan, Korea, Southeast Asian countries, and some European countries. However, the compound variations at the different growth periods and in the different parts of Fushen have not previously been investigated. In this study, an untargeted metabolomics approach based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) and targeted quantitative analysis was utilized to characterize the temporal and spatial variations in the accumulation of specialized metabolites in Fushen. There were 119 specialized metabolites tentatively identified using the UPLC-Q/TOF-MS. The nine growth periods of Fushen were divided into four groups using partial least squares discrimination analysis (PLS-DA). Four different parts of the Fushen [fulingpi (FP), the outside of baifuling (BO), the inside of baifuling (BI), and fushenmu (FM)] were clearly discriminated using a PLS-DA and orthogonal partial least squares discrimination analysis (OPLS-DA). Markers for the different growth periods and parts of Fushen were also screened. In addition, the quantitative method was successfully applied to simultaneously determine 13 major triterpenoid acids in the nine growth periods and four parts. The quantitative results indicated that the samples in January, March, and April, i.e., the late growth period, had the highest content levels for the 13 triterpenoid acids. The pachymic acid, dehydropachymic acid, and dehydrotumulosic acid contents in the FM were higher than those in other three parts in March, whereas the poricoic acid B, poricoic acid A, polyporenic acid C, dehydrotratrametenolic acid, dehydroeburicoic acid, and eburicoic acid in FP were higher beginning in October. These findings reveal characteristics in temporal and spatial distribution of specialized metabolites in Fushen and provide guidance for the identification of harvesting times and for further quality evaluations.

Comprehensive Comparison of Two Color Varieties of Perillae Folium Using Rapid Resolution Liquid Chromatography Coupled with Quadruple-Time-of-Flight Mass Spectrometry (RRLC-Q/TOF-MS)-Based Metabolic Profile and in Vivo/in Vitro Anti-Oxidative Activity

Perillae Folium (PF), which is extensively used as a dietary vegetable and medicinal herb, contains two varietal forms corresponding to purple perilla leaf (Perilla frutescens var. crispa) and green perilla leaf (Perilla frutescens var. frutescens). However, the components and efficacy of different PF varieties remain underexplored so far. In the present work, a nontargeted rapid resolution liquid chromatography coupled with quadruple-time-of-flight mass spectrometry (RRLC-Q/TOF-MS)-based metabolomics approach was developed to investigate the difference in the chemical compositions between green PF and purple PF. A total of 71 compounds were identified or tentatively identified, among which 7 phenolic acids, 10 flavonoids, and 9 anthocyanins were characterized as differential metabolites. In addition, heatmap visualization and ultraperformance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry (UPLC-TQ-MS/MS)-based quantitative analysis revealed that flavonoids and anthocyanins especially had higher contents in purple PF. Furthermore, the anti-oxidative activities of two varietal PFs were evaluated in vivo zebrafish and in vitro human umbilical vein endothelial cells (HUVECs). The results showed that the purple PF had more pronounced anti-oxidative activities than did the green PF, which may be due to the presence of anthocyanins and a higher concentration of flavonoids in its phytochemical profile. The outcome of the present study is expected to provide useful insight on the comprehensive utilization of a PF resource.

Integration of mass spectral fingerprinting analysis with precursor ion (MS1) quantification for the characterisation of botanical extracts: application to extracts of Centella asiatica (L.) Urban

INTRODUCTION

The phytochemical composition of plant material governs the bioactivity and potential health benefits as well as the outcomes and reproducibility of laboratory studies and clinical trials.

OBJECTIVE

The objective of this work was to develop an efficient method for the in-depth characterisation of plant extracts and quantification of marker compounds that can be potentially used for subsequent product integrity studies. Centella asiatica (L.) Urb., an Ayurvedic herb with potential applications in enhancing mental health and cognitive function, was used as a case study.

METHODS

A quadrupole time-of-flight analyser in conjunction with an optimised high-performance liquid chromatography (HPLC) separation was used for in-depth untargeted fingerprinting and post-acquisition precursor ion quantification to determine levels of distinct phytochemicals in various C. asiatica extracts.

RESULTS

We demonstrate the utility of this workflow for the characterisation of extracts of C. asiatica. This integrated workflow allowed the identification or tentative identification of 117 compounds, chemically interconnected based on Tanimoto chemical similarity, and the accurate quantification of 24 phytochemicals commonly found in C. asiatica extracts.

CONCLUSION

We report a phytochemical analysis method combining liquid chromatography, high resolution mass spectral data acquisition, and post-acquisition interrogation that allows chemical fingerprints of botanicals to be obtained in conjunction with accurate quantification of distinct phytochemicals. The variability in the composition of specialised metabolites across different C. asiatica accessions was substantial, demonstrating that detailed characterisation of plant extracts is a prerequisite for reproducible use in laboratory studies, clinical trials and safe consumption. The methodological approach is generally applicable to other botanical products.

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

Exploring the Potential of the Microbiome as a Marker of the Geographic Origin of Fresh Seafood

Geographic food fraud – misrepresenting the geographic origin of a food item, is very difficult to detect, and therefore this type of fraud tends to go undetected. This potentially negatively impacts the health of Canadians and economic success of our seafood industry. Surveillance studies have shown that up to a significant portion of commercially sold seafood items in Canada are mislabeled or otherwise misrepresented in some way. The current study aimed to determine if the microbiome of fresh shellfish could be used as an accurate marker of harvest location. Total DNA was extracted from the homogenate of 25 batches of fresh soft-shell clams (Mya arenaria) harvested in 2015 and 2018 from two locations on the East Coast of Canada and the microbiome of each homogenate was characterized using 16S rRNA targeted amplicon sequencing. Clams harvested from Nova Scotia in both years had a higher abundance of Proteobacteria and Acidobacteria (p < 0.05), but a lower abundance of Actinobacteria (p < 0.05) than those from Quebec. Alpha-diversity also differed significantly between sites. Samples harvested from Nova Scotia had greater diversity (p < 0.0001) than those from Quebec. Beta-diversity analysis showed that the microbial community composition was significantly different between the samples from Nova Scotia and Quebec and indicated that 16S rRNA targeted amplicon sequencing might be an effective tool for elucidating the geographic origin of unprocessed shellfish. To evaluate if the microbiome of shellfish experiences a loss of microbial diversity during processing and storage – which would limit the ability of this technique to link retail samples to geographic origin, 10 batches of retail clams purchased from grocery stores were also examined. Microbial diversity and species richness was significantly lower in retail clams, and heavily dominated by Proteobacteria, a typical spoilage organism for fresh seafood, this may make determining the geographic origin of seafood items more difficult in retail clams than in freshly harvested clams.

Peptides as Potential Biomarkers for Authentication of Mountain-Cultivated Ginseng and Cultivated Ginseng of Different Ages Using UPLC-HRMS

The growth conditions and age of Panax ginseng are vital for determining the quality of the ginseng plant. However, the considerable difference in price according to the cultivation method and period of P. ginseng leads to its adulteration in the trade market. We herein focused on ginseng peptides and the possibility of these peptides to be used as biomarker(s) for discrimination of P. ginseng. We applied an ultraperformance liquid chromatography-high resolution mass spectrometry-based peptidomics approach to characterize ginseng peptides and discover novel peptide biomarkers for authentication of mountain-cultivated ginseng (MCG). We identified 52 high-confidence peptides and screened 20 characteristic peptides differentially expressed between MCG and cultivated ginseng (CG). Intriguingly, 6 differential peptides were expressed significantly in MCG and originated from dehydrins that accumulated during cold or drought conditions. In addition, 14 other differential peptides that were significantly expressed in CG derived from ginseng major protein, an essential protein for nitrogen storage. These biological associations confirmed the reliability and credibility of the differential peptides. Additionally, we determined several robust peptide biomarkers for discrimination of MCG through a precise selection process. These findings demonstrate the potential of peptide biomarkers for identification and quality control of P. ginseng in addition to ginsenoside analysis.

Untargeted metabolomics coupled with chemometric analysis reveals species-specific steroidal alkaloids for the authentication of medicinal Fritillariae Bulbus and relevant products

Authentication of original species is embedded in the quality control system of herbal medicines. In this work, ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics coupled with chemometric analysis was utilized for the precise authentication of the Fritillaria species for both raw materials and commercial products. First, a stepwise difference-enlarging chemometric analysis strategy was proposed to analyze eight medicinal Fritillaria species. Subsequently, 21 species-specific markers were discovered and the specificity was investigated under different sample preparation methods. Finally, the obtained species-specific markers were successfully utilized to identify the Fritillaria species in commercially relevant products. This work is the first to report robust and specific markers for authentication of Fritillaria products, showing promise for tracking the supply chain of herbal suppliers.