Application of the Metabolomics Approach in Food Authentication

Metabolomics for dental caries diagnosis: Past, present, and future

Dental caries, a prevalent global infectious condition affecting over 95% of adults, remains elusive in its precise etiology. Addressing the complex dynamics of caries demands a thorough exploration of taxonomic, potential, active, and encoded functions within the oral ecosystem. Metabolomic profiling emerges as a crucial tool, offering immediate insights into microecosystem physiology and linking directly to the phenotype. Identified metabolites, indicative of caries status, play a pivotal role in unraveling the metabolic processes underlying the disease. Despite challenges in metabolite variability, the use of metabolomics, particularly via mass spectrometry and nuclear magnetic resonance spectroscopy, holds promise in caries research. This review comprehensively examines metabolomics in caries prevention, diagnosis, and treatment, highlighting distinct metabolite expression patterns and their associations with disease-related bacterial communities. Pioneering in approach, it integrates singular and combinatory metabolomics methodologies, diverse biofluids, and study designs, critically evaluating prior limitations while offering expert insights for future investigations. By synthesizing existing knowledge, this review significantly advances our comprehension of caries, providing a foundation for improved prevention and treatment strategies.

The Protein/Carbohydrate Ratio in the Diet Affects Zootechnical Performance and the Regulation of Intermediary Metabolism in Juveniles Tambaqui (Colossoma macropomum)

The use of carbohydrates in animal feed is a way to save protein in the diet. This study evaluated the effect of protein/starch ratio on the performance, hepatic metabolism, and body composition of juvenile tambaqui (Colossoma macropomum). Six isoenergetic experimental diets were formulated containing three levels of digestible protein (P: 230, 260 and 290 g kg- 1) and two levels of starch (S: 180 and 280 g kg- 1): P23S18, P23S28, P26S18, P26S28, P29S18 and P29S28. Juveniles tambaqui (N = 288; initial weight = 30.0 ± 3.8 g) were fed experimental diets for 90 days and the zootechnical performance was evaluated. Nine fish from each treatment group were sampled to determine somatic indices, blood metabolites, tissue energy reserves, body composition and activity of key hepatic enzymes. Blood triglycerides, hepatosomatic index, liver and muscle lipids, and hepatic glycogen increased significantly with starch while blood glucose, triglycerides and cholesterol, muscle lipids were significantly impacted by protein levels. Fish-fed S28 had increased feed intake (1714-1829 g; p < 0.0001) and fish-fed diet P26S18 had a higher protein efficiency rate (23.62%; p = 0.0356). Fish fed P23 had lower crude protein retention in the carcass (p = 0.0018) and high lipogenesis and lipid deposition in the muscle (p = 0.0069). These results suggest that dietary carbohydrates have a protein-sparing effect. Tambaqui adapted well to diets containing starch, even at higher levels, resulting in an overall increase in lipogenesis from S18 to S28. Thus, we recommend P26S18 as a cost-effective feed that ensures both zootechnical performance and quality of the final product.

How Machine Learning and Gas Chromatography-Ion Mobility Spectrometry Form an Optimal Team for Benchtop Volatilomics

This invited feature article discusses the potential of gas chromatography-ion mobility spectrometry (GC-IMS) as a point-of-need alternative for volatilomics. Furthermore, the capabilities and versatility of machine learning (ML) (chemometric) techniques used in the framework of GC-IMS analysis are also discussed. Modern ML techniques allow for addressing advanced GC-IMS challenges to meet the demands of modern chromatographic research. We will demonstrate workflows based on available tools that can be used with a clear focus on open-source packages to ensure that every researcher can follow our feature article. In addition, we will provide insights and perspectives on the typical issues of the GC-IMS along with a discussion of the process necessary to obtain more reliable qualitative and quantitative analytical results.

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.

An Integrated Metabolomics Study on Antidiabetic Activity of Christia vespertilionis Leaves Extract Using Chemometric and Molecular Docking Analysis

In disease treatment, the utilisation of medicinal plants has witnessed a discernible rise, driven by concerns over the adverse effects associated with synthetic drugs available in the market. Analyses of the plant Christia vespertilionis (L.f.) Bakh. F., indigenous to Malaysia, has suggested its antidiabetic property linked to α-glucosidase inhibition, but metabolites responsible for antidiabetic are unexplored. The metabolomics approaches and molecular docking simulations were integrated to identify the putative α-glucosidase inhibitors and their enzyme interaction. In this study, the crude leaves extracted from this plant were extracted using solvents of varying polarity, followed by gas and liquid chromatography coupled with mass spectrometry metabolomics. The highest inhibition activity in a mixture of n-hexane and ethyl acetate (1:1, v/v)) was observed. Six putative metabolites corresponding to antidiabetic activity were identified: palmitic acid (2), linolenic acid (4), 7-tetradecenal (5), aloeemodin-8-monoglucoside (14), bruceine I (15), and sanjidin B (16). The mechanism of action of all the identified compounds is competitive, mainly involving hydrophobic and hydrogen bonding interactions with the protein residues. Compounds 14, 15, and 16 exhibited strong binding capabilities with both enzyme crystal structures compared to the positive control, quercetin. The metabolites extracted from C. vespertilionis leaves have demonstrated promising antidiabetic effects. These antidiabetic compounds can potentially commercialise new drug candidates in managing diabetes conditions.

Integration of network-based approaches for assessing variations in metabolic profiles of alkalized and non-alkalized commercial cocoa powders

Cocoa can undergo an alkalization process to enhance its color and solubility. It reduces astringency and alters its composition, particularly in the phenolic compound content, which is related to cocoa health benefits. This study aimed to investigate the impact of alkalization on the composition of seven commercial cocoa powders. A liquid chromatography-based metabolomic approach was employed to assess the metabolic differences between alkalized and non-alkalized cocoa powders. Supervised orthogonal partial least squares discriminant analysis (OPLS-DA) was used to identify the most discriminating variables between groups. A feature-based molecular network (FBMN) was used to explore the chemical space. Three hundred forty-seven metabolites were obtained as the most discriminant, among which 60 were tentatively annotated. Phenolic compounds, lysophosphatidylethanolamines, amino acids, and their derivatives were significantly reduced in alkalized cocoas. In contrast, fatty acids and their derivatives significantly increased with alkalization. Despite the variability among commercial cocoas, chemometrics allowed the elucidation of alterations induced specifically by alkalization in their composition.

Development of real-time polymerase chain reaction for analysis of rat meat (Bandicota bengalensis) in beef meatballs for halal authentication

Background

Consumer awareness of food adulteration is increasing nowadays. Motivated by economic gain, unethical meat producers try to blend halal meat such as beef with non-halal meat like rat meat (RM).

Aim

This study aims to develop a real-time polymerase chain reaction (RT-PCR) analysis method to analyze the presence of RM in beef meatballs.

Methods

This research was carried out in the following stages: primer design, DNA isolation, analysis of DNA isolates, the optimization of primer annealing temperature, primer specificity test, sensitivity, and repeatability. The validated RT-PCR method was then used to analyze the marketed meatball samples.

Results

The result showed that the designed primer targeting on ND2 gene set rat mt-DNA (forward: ACTCCATATCTCTCACCATATTTCC; reverse: GGGTTAGGGTACTTAGGATTGTTAG), had good specificity at an optimal annealing temperature of 56.3oC over the other eight species. The developed RT-PCR method produces a limit detection value of 195.31 pg, coefficient of determination (R 2) for linearity of 0.983, amplification efficiency (E) of 100%, and CV value for amplification response of 1.8%. The result showed that the developed RT-PCR method did not detect the presence of RM DNA in eight marketed beef meatball samples.

Conclusion

The developed method meets the acceptance criteria for RT-PCR and can be used as a halal authentication method to identify the presence of RM in beef meatballs.

Advances in detection technology for authentication of vegetable oils: A comprehensive review

Biomarkers are specific indicators that can be used to authenticate vegetable oils by reflecting unique characteristics such as variety or geographical origin. Biomarkers can originate from the primary components of the vegetable oil itself or from contaminants and trace substances linked to processing methods or adulterants. The review highlights the key findings in the identification of novel biomarkers for vegetable oil authentication. Various analytical techniques have proven effective in distinguishing unique biomarkers associated with specific vegetable oil varieties or geographical origins. The use of biomarkers of vegetable oils and associated contaminants or trace substances offers a comprehensive approach to authentication. However, the identification of novel biomarkers holds immense potential for enhancing food safety, preventing fraud, and safeguarding consumer health in the vegetable oil industry. The ongoing research and advancements in biomarker identification represent a promising avenue for addressing authenticity concerns in vegetable oils.

Alterations of plasma metabolomes and their correlations with immunogenicity in maintenance hemodialysis patients receiving different COVID-19 vaccine regimens

Maintenance hemodialysis (MHD) patients exhibit compromised immune responses, leading to lower immunogenicity to the COVID-19 vaccine than the general population. The metabolomic factors influencing COVID-19 vaccine response in MHD patients remain elusive. A cross-sectional study was conducted with 30 MHD patients, divided into three vaccine regimen groups (N= 10 per group): homologous CoronaVac® (SV-SV), homologous ChAdOx1 nCoV-19 (AZ-AZ), and heterologous prime-boost (SV-AZ). Plasma samples were collected at baseline and at 28 days after the final dose to analyze 92 metabolomic levels using targeted metabolomics. The study included 30 MHD patients (mean age 56.67 ± 10.79 years) with similar neutralizing antibody (nAb) levels across vaccine regimens. The most significant differences in metabolomics were found between AZ-AZ and SV-SV, followed by SV-AZ versus SV-SV, and AZ-AZ versus SV-AZ. Overall, the metabolomic changes involved amino acids like glutamate and phenylalanine, and phospholipids. Prevaccination metabolomic profiles, including PG (38:1), lysoPE (20:2), lysoPC (18:2), lysoPI (18:1), and PC (34:2), exhibited negative correlations with postvaccination nAb levels. Different COVID-19 vaccine regimens had unique interactions with the immune response in MHD patients. Amino acid and phospholipid metabolisms play crucial roles in nAb formation, with the phospholipid metabolism being a potentially predictive marker of vaccine immunogenicity among MHD patients.

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.

Untargeted metabolomics using liquid chromatography-high resolution mass spectrometry and chemometrics for analysis of non-halal meats adulteration in beef meat

OBJECTIVE

The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach.

METHODS

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr.

RESULTS

The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R2>0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w).

CONCLUSION

A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

A View on the Chemical and Biological Attributes of Five Edible Fruits after Finishing Their Shelf Life: Studies on Caco-2 Cells

We studied five common perishable fruits in terms of their polyphenols dynamic, minerals distribution, scavenger activity and the effects of 50% ethanolic extracts on the viability of Caco-2 cells in vitro, over a period of time between T = 0 and T = 5/7 days, typically the end of their shelf life. Altogether, there were few changes found, consisting of either an increase or a decrease in their chemical and biological attributes. A slow decrease was found in the antioxidant activity in apricot (-11%), plum (-6%) and strawberry (-4%) extracts, while cherry and green seedless table grape extracts gained 7% and 2% antioxidant potency, respectively; IC50 values ranged from 1.67 to 5.93 μg GAE/μL test extract. The cytotoxicity MTS assay at 24 h revealed the ability of all 50% ethanol fruit extracts to inhibit the Caco-2 cell viability; the inhibitory effects ranged from 49% to 83% and were measured at 28 µg GAE for strawberry extracts/EES, from 22 µg to 45 µg GAE for cherry extracts/EEC, from 7.58 to 15.16 µg GAE for apricot extracts/EEA, from 12.50 to 25.70 µg GAE for plum extracts/EEP and from 21.51 to 28.68 µg GAE for green table grape extracts/EEG. The MTS anti-proliferative assay (72 h) also revealed a stimulatory potency upon the Caco-2 viability, from 34% (EEA, EEG) and 48% (EEC) to 350% (EES) and 690% (EEP); therefore fruit juices can influence intestinal tumorigenesis in humans.

Analysis of dog meat adulteration in beef meatballs using non-targeted UHPLC-Orbitrap HRMS metabolomics and chemometrics for halal authentication study

Due to the different price and high quality, halal meat such as beef can be adulterated with non-halal meat with low price to get an economical price. The objective of this research was to develop an analytical method for halal authentication testing of beef meatballs (BM) from dog meat (DM) using a non-targeted metabolomics approach employing liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics. The differentiation of authentic BM from that adulterated with DM was successfully performed using partial least square-discriminant analysis (PLS-DA) with high accuracy (R2X = 0.980, and R2Y = 0.980) and good predictivity (Q2 = 0.517). In addition, partial least square (PLS) and orthogonal PLS (OPLS) were successfully used to predict the DM added (% w/w) in BM with high accuracy (R2 > 0.990). A number of metabolites, potential for biomarker candidates, were identified to differentiate BM and that adulterated with DM. It showed that the combination of a non-targeted LC-HRMS Orbitrap metabolomics and chemometrics could detect up to 0.1% w/w of DM adulteration. The developed method was successfully applied for analysis of commercial meatball samples (n = 28). Moreover, pathway analysis revealed that beta-alanine, histidine, and ether lipid metabolism were significantly affected by dog meat adulteration. In summary, this developed method has great potential to be developed and used as an alternative method for analysis of non-halal meats in halal meat products.

Recent Advances in the Detection of Food Toxins Using Mass Spectrometry

Edibles are the only source of nutrients and energy for humans. However, ingredients of edibles have undergone many physicochemical changes during preparation and storage. Aging, hydrolysis, oxidation, and rancidity are some of the major changes that not only change the native flavor, texture, and taste of food but also destroy the nutritive value and jeopardize public health. The major reasons for the production of harmful metabolites, chemicals, and toxins are poor processing, inappropriate storage, and microbial spoilage, which are lethal to consumers. In addition, the emergence of new pollutants has intensified the need for advanced and rapid food analysis techniques to detect such toxins. The issue with the detection of toxins in food samples is the nonvolatile nature and absence of detectable chromophores; hence, normal conventional techniques need additional derivatization. Mass spectrometry (MS) offers high sensitivity, selectivity, and capability to handle complex mixtures, making it an ideal analytical technique for the identification and quantification of food toxins. Recent technological advancements, such as high-resolution MS and tandem mass spectrometry (MS/MS), have significantly improved sensitivity, enabling the detection of food toxins at ultralow levels. Moreover, the emergence of ambient ionization techniques has facilitated rapid in situ analysis of samples with lower time and resources. Despite numerous advantages, the widespread adoption of MS in routine food safety monitoring faces certain challenges such as instrument cost, complexity, data analysis, and standardization of methods. Nevertheless, the continuous advancements in MS-technology and its integration with complementary techniques hold promising prospects for revolutionizing food safety monitoring. This review discusses the application of MS in detecting various food toxins including mycotoxins, marine biotoxins, and plant-derived toxins. It also explores the implementation of untargeted approaches, such as metabolomics and proteomics, for the discovery of novel and emerging food toxins, enhancing our understanding of potential hazards in the food supply chain.

Identification of a β-Carboline Alkaloid from Chemoselectively Derived Vanilla Bean Extract and Its Prevention of Lipid Droplet Accumulation in Human Hepatocytes (HepG2)

Targeting bioactive compounds to prevent lipid droplet accumulation in the liver, we explored an antioxidative extract from vanilla bean (Vainilla planifolia) after chemo-selective derivatization through heating and acid modification. The chemical analysis of vanilla bean extract through chemoselective derivatization resulted in the identification of sixteen compounds (34-50) using LC-MS/MS analysis. A β-carboline alkaloid with a piperidine C-ring and a vanillin moiety at C-1 (34) was identified by molecular networking and diagnostic fragmentation filtering approaches. β-carboline alkaloid 34 exhibited significant inhibitory activity of lipid droplet accumulation (LDAI) in oleic acid-loaded hepatocellular carcinoma HepG2 cells. The LDAI activity was associated with both activation of lipolysis and suppression of lipogenesis in the cells. The study indicates that crude plant extracts, following chemoselective derivatization, may contain bioactive compounds that could be beneficial in preventing hepatosteatosis and could serve as a source of lead compounds for drug development. This approach may be useful to investigate other mixtures of natural products and food resources.

Microbial Diversity in African Foods and Beverages: A Systematic Assessment

This article provides a comprehensive and in-depth examination of the microbial diversity inherent in African food and beverages, with a particular emphasis on fermented products. It identifies and characterizes the dominant microorganisms, including both prokaryotes and yeasts, prevalent in these foods, and furthermore, critically analyzes the health benefits of these microbial strains, especially their probiotic properties, which could potentially improve digestion and contribute to human health. Notably, it underscores the vital role these microorganisms play in bolstering food security across Africa by enhancing and preserving food quality and safety. It also delves into the potential applications of microbial products, such as metabolites, in the food industry, suggesting their possible use in food processing and preservation. Conclusively, with a summarization of the key findings, emphasizing the importance of gaining a deep understanding of microbial diversity in African beverages and foods. Such knowledge is crucial not only in promoting food security but also in advancing public health.

Natural complex substances: From molecules to the molecular complexes. Analytical and technological advances for their definition and differentiation from the corresponding synthetic substances

Natural complex substances (NCSs) are a heterogeneous family of substances that are notably used as ingredients in several products classified as food supplements, medical devices, cosmetics and traditional medicines, according to the correspondent regulatory framework. The compositions of NCSs vary widely and hundreds to thousands of compounds can be present at the same time. A key concept is that NCSs are much more than the simple sum of the compounds that constitute them, in fact some emerging phenomena are the result of the supramolecular interaction of the constituents of the system. Therefore, close attention should be paid to produce and characterize these systems. Today many natural compounds are produced by chemical synthesis and are intentionally added to NCSs, or to formulated natural products, to enhance their properties, lowering their production costs. Market analysis shows a tendency of people to use products made with NCSs and, currently, products made with ingredients of natural origin only are not conveniently distinguishable from those containing compounds of synthetic origin. Furthermore, the uncertainty of the current European regulatory framework does not allow consumers to correctly differentiate and identify products containing only ingredients of natural origin. The high demand for specific and effective NCSs and their high-cost offer on the market, create the conditions to economically motivated sophistications, characterized by the addition of a cheap material to a more expensive one, just to increase profit. This type of practice can concern both the addition of less valuable natural materials and the addition of pure artificial compounds with the same structure as those naturally present. In this scenario, it becomes essential for producers of natural products to have advanced analytical techniques to evaluate the effective naturalness of NCSs. In fact, synthetically obtained compounds are not identical to their naturally occurring counterparts, due to the isotopic composition or chirality, as well as the presence of different trace metabolites (since pure substances in nature do not exist). For this reason, in this review, the main analytical tests that can be performed to differentiate natural compounds from their synthetic counterparts will be highlighted and the main analytical technologies will be described. At the same time, the main fingerprint techniques useful for characterizing the complexity of the NCSs, also allowing their identification and quali-quantitative evaluation, will be described. Furthermore, NCSs can be produced through different manufacturing processes, not all of which are on the same level of quality. In this review the most suitable technologies for green processes that operate according to physical extraction principles will be presented, as according to the authors they are the ones that come closest to creating more life-cycle compatible NCSs and that are well suited to the European green deal, a strategy with the aim of transforming the EU into a sustainable and resource-efficient society by 2050.

Emerging trends and applications of metabolomics in food science and nutrition

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.

Untargeted metabolomics liquid chromatography-high resolution mass spectrometry approach for the geographical origin assessment of Italian dehydrated apples

Geographical provenience is nowadays a relevant aspect of the authenticity and the quality of many food commodities. Dehydrated apple cubes/slices represent an ingredient commonly used by food companies for bakery products. However, this apple-based matrix is not so known and studied from an analytical point of view. In the present work, seven compounds were identified as key molecules to distinguish between Italian and non-Italian samples, through an untargeted ultrahigh-pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) approach. This methodology was merged with multivariate statistical analysis, and the principal features were studied and identified considering several identification steps. Samples from 2020 and 2021 harvesting campaigns, with partial and total dehydration rates, with or without peel, and from different apple varieties were considered for the study, for a total of 91 samples. Afterward, the same analysis protocol was applied to an external set (n = 12 samples), included in the statistical models, searching for the key compounds identified in the training set. Interesting and significant results underlined the potentiality of the UHPLC-HRMS technology as a confirmatory strategy for the geographical origin assessment of dehydrated apple commodities.

Microneedles for advanced ocular drug delivery

In the field of ocular drug delivery, topical delivery remains the most common treatment option for managing anterior segment diseases, whileintraocular injectionsare the current gold standard treatment option for treating posterior segment diseases. Nonetheless, topical eye drops are associated with low bioavailability (<5%), and theintravitreal administration procedure is highly invasive, yielding poor patient acceptability. In both cases, frequent administration is currently required. As a result, there is a clear unmet need for sustained drug delivery to the eye, particularly in a manner that can be localised. Microneedles, which are patches containing an array of micron-scale needles (<1 mm), have the potential to meet this need. These platforms can enable localised drug delivery to the eye while enhancing penetration of drug molecules through key ocular barriers, thereby improving overall therapeutic outcomes. Moreover, the minimally invasive manner in which microneedles are applied could provide significant advantages over traditional intravitreal injections regarding patient acceptability. Considering the benefitsofthis novel ocular delivery system, this review provides an in-depth overviewofthe microneedle systems for ocular drug delivery, including the types of microneedles used and therapeutics delivered. Notably, we outline and discuss the current challenges associated with the clinical translation of these platforms and offer opinions on factors which should be considered to improve such transition from lab to clinic.

Metabolomics: A suitable foodomics approach to the geographical origin traceability of Ethiopian Arabica specialty coffees

Coffee arabica, originated in Ethiopia, is considered a quality bean for its high sensory qualities, and has a special price in the world coffee market. The country is a pool of genetic diversity for Arabica coffee, and coffee from different regions has a distinct flavor profile. Their exceptional quality is attributed to their genetic diversity, favorable environmental conditions, and agroforestry-based production system. However, the country still needs to benefit from its single-origin product due to a lack of appropriate traceability information to register for its geographical indication. Certification of certain plants or plant-derived products emerged to inform consumers about their exceptional qualities due to their geographical origin and protect the product from fraud. The recently emerging foodomics approaches, namely proteomics, genomics, and metabolomics, are reported as suitable means of regional agri-food product authentication and traceability. Particularly, the metabolomics approach provides truthful information on product traceability. Despite efforts by some researchers to trace the geographical origin of Ethiopian Arabica coffees through stable isotope and phenolic compound profiling and elemental analysis, foodomics approaches are not used to trace the geographical origin of Arabica specialty coffees from various parts of the country. A metabolomics-based traceability system that demonstrates the connection between the exceptional attributes of Ethiopian Arabica specialty coffees and their geographic origin is recommended to maximize the benefit of single-origin coffees.

Metabolomics Reveals Distinctive Metabolic Profiles and Marker Compounds of Camellia (Camellia sinensis L.) Bee Pollen

Camellia bee pollen (CBP) is a major kind of bee product which is collected by honeybees from tea tree (Camellia sinensis L.) flowers and agglutinated into pellets via oral secretion. Due to its special healthcare value, the authenticity of its botanical origin is of great interest. This study aimed at distinguishing CBP from other bee pollen, including rose, apricot, lotus, rape, and wuweizi bee pollen, based on a non-targeted metabolomics approach using ultra-high performance liquid chromatography-mass spectrometry. Among the bee pollen groups, 54 differential compounds were identified, including flavonol glycosides and flavone glycosides, catechins, amino acids, and organic acids. A clear separation between CBP and all other samples was observed in the score plots of the principal component analysis, indicating distinctive metabolic profiles of CBP. Notably, L-theanine (864.83-2204.26 mg/kg) and epicatechin gallate (94.08-401.82 mg/kg) were identified exclusively in all CBP and were proposed as marker compounds of CBP. Our study unravels the distinctive metabolic profiles of CBP and provides specific and quantified metabolite indicators for the assessment of authentic CBP.

Fast screening and identification of illegal adulteration in dietary supplements and herbal medicines using molecular networking with deep-learning-based similarity algorithms

Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is a powerful analytical tool used for adulteration inspection. Nevertheless, it is a challenging task to identify illegal adulterants that are not included in the library or are unexpected from large MS data. Molecular networking is a good tool for exploring, visualizing, and organizing MS/MS spectra, and moreover, it employs shifted peak match to calculate spectral similarity, making it capable of identifying adulteration that is not included in the library. The key of molecular networking is spectral similarity algorithms, and therefore, in this study, we compared the performance of four cutting-edge similarity algorithms, modified cosine similarity (shifted peak match), entropy similarity, and two deep-learning-based algorithms, MS2DeepScore and Spec2Vec, in building molecular networking for identification of adulteration that is not included in the library. We conducted an analysis of excluded-query-compound on all MS/MS spectra in test library and performed a large-scale false discovery rate estimation to investigate whether the spectral similarity calculated by each algorithm could represent the actual structural similarity well. The obtained results demonstrated Spec2Vec exhibited good performance in both detection capability and false discovery rate. Further comprehensive evaluation of the performance of Spec2Vec in the identification of adulteration that is not included in the library or is unexpected in different matrices and in application to real samples proved the approach studied here is a promising and powerful tool for adulterant inspection and improved the capability of analyzing large MS data.

HPLC-MS-based untargeted metabolomic analysis of differential plasma metabolites and their associated metabolic pathways in reproductively anosmic black porgy, Acanthopagrus schlegelii

Olfaction, a universal form of chemical communication, is a powerful channel for animals to obtain social and environmental cues. The mechanisms by which fish olfaction affects reproduction, breeding and disease control are not yet clear. To evaluate metabolites profiles, plasma from anosmic and control black porgy during reproduction was analyzed by non-targeted metabolomics using ultra high-performance liquid chromatography-mass spectrometry and multivariate statistical analysis techniques, including principal component analysis and orthogonal partial least squares discriminant analysis. The metabolite profiles of anosmia and control groups were found to be significantly separated. Ten different differential metabolites, mainly including amino acids, such as isoleucine and methionine, and lipids, such as phosphatidylserine, were screened based on the combined analysis of variable importance in the projection and p values. In addition, six key differential metabolic pathways were analyzed using the Kyoto Encyclopedia of Genes and Genomes and enriched for four metabolic pathways including the citrate acid (TCA) cycle, tyrosine metabolism, arginine and proline metabolism, and arginine synthesis. The TCA cycle enhances fertility through the reduction of pyruvate kinase, and intermediate derivatives (acetyl CoA, malonyl CoA) act as signaling factors that regulate immune cell function. The tyrosine cycle can indirectly participate and promote reproduction in black porgy through melanin-concentrating hormone. Arginine and proline metabolism can promote reproduction by promoting growth hormone and enhance immunity in anosmic black porgy by stimulating T lymphocytes. Our metabolomic study revealed that anosmia in black porgy played an active role in immunity and reproduction and provided theoretical support for breeding and disease control.

Stepwise Approach for Tracing the Geographical Origins of the Manila Clam Ruditapes philippinarum Using Dual-Element Isotopes and Carbon Isotopes of Fatty Acids

While there are many studies that have reported methods for tracing the geographical origin of seafoods, most of them have focused on identifying parameters that can be used effectively and not the direct application of these methods. In this study, we attempted to differentiate the geographical origins of the Manila clam R. philippinarum collected from different sites in Korea, the Democratic People’s Republic of Korea, and China using a combination of analyses based on dual-element isotopes, fatty acids (FAs), and compound-specific isotopic analysis of FAs. We hypothesized that a stepwise application of new parameters to unclassified samples could achieve this objective by integrating new information while reducing time and labor. The FA profiles and compound-specific carbon isotopic values of FAs were found to enhance the discrimination power of determining the geographic origin up to 100%. Our findings demonstrate the advantageousness of using several parameters simultaneously over the conventional method of employing individual analytical methods when identifying geographic origins of the Manila clam, which could have implications for tracing the origins of different shellfish species or other food products as well.