1 H NMR-based metabolomics for discrimination of rice from different geographical origins of China

Geographical discrimination of Paw San rice cultivated in different regions of Myanmar using near-infrared spectroscopy, headspace-gas chromatography-ion mobility spectrometry and chemometrics

Paw San rice, also known as "Myanmar pearl rice", is considered the highest quality rice in Myanmar. There are considerable differences in terms of the premium commercial value of Paw San rice, which is an incentive for fraud, e.g. adulteration with cheaper rice varieties or mislabelling its geographical origin. Shwe Bo District is one of the most popular rice growing areas in the Sagaing region of Myanmar which produces the most valued and highly priced Paw San rice (Shwe Bo Paw San). The verification of the geographical origin of Paw San rice is not readily undertaken in the rice supply chain because the existing analytical approaches are time-consuming and expensive. Therefore, there is a need for rapid, robust and cost-effective analytical techniques for monitoring the authenticity and geographical origin of Paw San rice. In this 4-year study, two rapid screening techniques, Fourier-transform near-infrared (FT-NIR) spectroscopy and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), coupled with chemometric modelling, were applied and compared for the regional differentiation of Paw San rice. In addition, low-level fusion of the FT-NIR and HS-GC-IMS data was performed and its effect on the discriminative power of the chemometric models was assessed. Extensive model validation, including the validation using independent samples from a different production year, was performed. Furthermore, the effect of the sample preparation technique (grinding versus no sample preparation) on the performance of the discriminative model, obtained with FT-NIR spectral data, was assessed. The study discusses the suitability of FT-NIR spectroscopy, HS-GC-IMS and the combination of both approaches for rapid determination of the geographical origin of Paw San rice. The results demonstrated the excellent potential of the FT-NIR spectroscopy as well as HS-GC-IMS for the differentiation of Paw San rice cultivated in two distinct geographical regions. The OPLS-DA model, built using FT-NIR data of rice from 3 production years, achieved 96.67% total correct classification rate of an independent dataset from the 4th production year. The DD-SIMCA model, built using FT-NIR data of ground rice, also demonstrated the highest performance: 94% sensitivity and 97% specificity. This study has demonstrated that FT-NIR spectroscopy can be used as an accessible, rapid and cost-effective screening tool to discriminate between Paw San rice cultivated in the Shwe Bo and Ayeyarwady regions of Myanmar.

Intelligent System/Equipment for Quality Deterioration Detection of Fresh Food: Recent Advances and Application

The quality of fresh foods tends to deteriorate rapidly during harvesting, storage, and transportation. Intelligent detection equipment is designed to monitor and ensure product quality in the supply chain, measure appropriate food quality parameters in real time, and thus minimize quality degradation and potential financial losses. Through various available tracking devices, consumers can obtain actionable information about fresh food products. This paper reviews the recent progress in intelligent detection equipment for sensing the quality deterioration of fresh foods, including computer vision equipment, electronic nose, smart colorimetric films, hyperspectral imaging (HSI), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), ultrasonic non-destructive testing, and intelligent tracing equipment. These devices offer the advantages of high speed, non-destructive operation, precision, and high sensitivity.

Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review

Food authentication and contamination are significant concerns, especially for consumers with unique nutritional, cultural, lifestyle, and religious needs. Food authenticity involves identifying food contamination for many purposes, such as adherence to religious beliefs, safeguarding health, and consuming sanitary and organic food products. This review article examines the issues related to food authentication and food fraud in recent periods. Furthermore, the development and innovations in analytical techniques employed to authenticate various food products are comprehensively focused. Food products derived from animals are susceptible to deceptive practices, which can undermine customer confidence and pose potential health hazards due to the transmission of diseases from animals to humans. Therefore, it is necessary to employ suitable and robust analytical techniques for complex and high-risk animal-derived goods, in which molecular biomarker-based (genomics, proteomics, and metabolomics) techniques are covered. Various analytical methods have been employed to ascertain the geographical provenance of food items that exhibit rapid response times, low cost, nondestructiveness, and condensability.

The differences in metabolites, starch structure, and physicochemical properties of rice were related to the decrease in taste quality under high nitrogen fertilizer application

Nitrogen fertilizer application is one of the key cultivation practices to improve rice yields. However, the application of high nitrogen fertilizers often leads to a reduction in the stickiness of the rice after cooking, thus reducing the taste quality of rice. Moreover, there are differences in taste quality among rice varieties, and the mechanism has not been studied in depth. In this study, two rice varieties (Meixiangzhan2hao and Exiang2hao) were planted under two nitrogen fertilizer levels. The physicochemical properties and taste quality of the rice were determined after maturity. Our results showed that high nitrogen fertilizer level alters tryptophan metabolism in rice, increasing most amino acid content and protein content in rice. The high content of protein and the higher short-range ordered structure of starch inhibited the gelatinization characteristics of starch and reduced the taste quality of rice. Under high nitrogen fertilizer application, Exiang2hao showed smaller increases in protein content, lower level of amylose and relative crystallinity, and higher content of lipid metabolites. These differences in chemical substances resulted in a less pronounced reduction in the taste quality of Exiang2hao. In this study, the taste quality of different rice varieties under different levels of nitrogen fertilizer application was analyzed, providing new ideas for future improvement of rice taste quality.

A review of conventional and rapid analytical techniques coupled with multivariate analysis for origin traceability of soybean

Soybean has developed a reputation as a superfood due to its nutrient profile, health benefits, and versatility. Since 1960, its demand has increased dramatically, going from a mere 17 MMT to almost 358 MMT in the production year 2021/22. These extremely high production rates have led to lower-than-expected product quality, adulteration, illegal trade, deforestation, and other concerns. This necessitates the development of an effective technology to confirm soybean's provenance. This is the first review that investigates current analytical techniques coupled with multivariate analysis for origin traceability of soybeans. The fundamentals of several analytical techniques are presented, assessed, compared, and discussed in terms of their operating specifics, advantages, and shortcomings. Additionally, significance of multivariate analysis in analyzing complex data has also been discussed.

Real-time traceability of sorghum origin by soldering iron-based rapid evaporative ionization mass spectrometry and chemometrics

Sorghum is an important grain with a high economic value for liquor production. Tracing the geographical origin of sorghum is vital to guarantee the liquor flavor. Soldering iron-based rapid evaporative ionization mass spectrometry (REIMS) combined with chemometrics was developed for the real-time discrimination of the sorghum's geographical origin. The working conditions of soldering iron-based ionization were optimized, and then the obtained MS profiling data were processed using chemometrics analysis methods, including principal component analysis-linear discriminant analysis and orthogonal projection to latent structures discriminant analysis (OPLS-DA). A recognition model was established, and discriminations of sorghum samples from 10 provinces in China were achieved with a correct rate higher than 90%. On the basis of OPLS-DA, the specific ions of m/z 279.2327, 281.2479, and 283.2639 had relatively strong discrimination power for the geographical origins of sorghum. The developed method was successfully applied in the discrimination of sorghum origins. The results indicated that the soldering iron-based REIMS technique combined with chemometrics is a useful tool for direct, fast, and real-time ionization of poor conductivity samples and acquisition of metabolic profiling data.

Classification of sugarcane genotypes susceptible and resistant to the initial attack of sugarcane borer Diatraea saccharalis using epicuticular wax composition

Identifying compounds present in the sugarcane epicuticular wax and using these compounds to classify the genotypes susceptible and resistant to the initial attack of sugarcane borer (Diatraea saccharalis) was the aim of this study. A greenhouse experiment was performed in a factorial scheme with and without borer infestation using genotypes previously characterized as resistant or susceptible in field-based experiments. Sugarcane whorls of six-month-old plants were collected before (BI) and after (AI) 72 h of sugarcane borer infestation. The sugarcane epicuticular wax was extracted in both times, i.e., BI and AI and its chemical composition was assessed by gas chromatography coupled to mass spectrometry (GC-MS). Twenty-five compounds were identified for both BI and AI. Classification models were built using partial least squares for discriminant analysis (PLS-DA) and linear discriminant analysis (LDA). Variable selection methods were used to improve the classification models. Ordered predictors selection for discriminant analysis (OPSDA) selected compounds that correctly classified all the test samples before borer infestation (Error = 0.000), and exhibited the most suitable classification parameters for the test set after borer infestation (Error = 0.111). The C30 pentacyclic triterpene friedelin and a high alcohol/aldehyde ratio were associated with the classification of resistant genotypes. Our findings have applicability in developing a screening methodology for breeding programs interested in identifying genotypes resistant to the initial feeding of sugarcane borer.

NMR Metabolome-Based Classification of Cymbopogon Species: a Prospect for Phyto-equivalency of its Different Accessions Using Chemometric Tools

Cymbopogon species are widely distributed worldwide and known for their high essential oil content with potential commercial and medicinal benefits justifying for their inclusion in food and cosmetics. Most species received scant characterization regarding their full complement of bioactive constituents necessary to explain their medicinal activities. In this study, the metabolite profiles of 5 Cymbopogon species, C. citratus, C. flexuosus, C. procerus, C. martini, and C. nardus, were characterized via NMR-based metabolomics. The results of 13 shoot accessions revealed the identification and quantification of 23 primary and secondary metabolites belonging to various compound classes. Multivariate analyses were used for species classification, though found not successful in discrimination based on geographical origin. Nevertheless, C. citratus was found particularly enriched in neral, geranial, (E)-aconitic acid, isoorientin, and caffeic acid as the major characterizing metabolites compared to other species, while an unknown apigenin derivative appeared to discriminate C. martini. The high essential oil and phenolic content in C. citratus emphasizes its strong antioxidant activity, whereas (E)-aconitic acid accounts for its traditional use as insecticide. This study affords the first insight into metabolite compositional differences among Cymbopogon species. Moreover, antimicrobial, insecticidal, antidiabetic, and antioxidant compounds were identified that can be utilized as biomarkers for species authentication.

NMR Tracing of Food Geographical Origin: The Impact of Seasonality, Cultivar and Production Year on Data Analysis

The traceability of typical foodstuffs is necessary to protect high quality of traditional products. It is well-known that several factors could influence metabolites content in certified foods, but soil composition, altitude, latitude and coded production protocols constitute the territorial conditions responsible for the peculiar organoleptic and nutritional properties of labelled foods. Instead, regardless of origin, seasonality, cultivar, collection year can affect all agricultural products, so it is appropriate to include them in data analysis in order to obtain a correct interpretation of the differences linked to growing areas alone. Therefore, it is useful to use a flexible all-round technique, and NMR spectroscopy coupled with multivariate statistical analysis is considered a powerful means of assessing food authenticity. The purpose of this review is to investigate the relevance of year, cultivar, and seasonal period in the determination of food geographical origin using NMR spectroscopy. The strategy for testing these three factors may differ from author to author, but a preliminary study of cultivar or collection year effects on NMR spectra is the most popular method before starting the geographical characterization of samples. In summary, based on the available literature, the most significant influence is due to cultivar, followed by harvesting year, however seasonality is not considered a source of variability in data analysis.

Nontargeted 1 H NMR fingerprinting and multivariate statistical analysis for traceability of Greek PDO Vostizza currants

In this study, non-targeted ¹ H NMR fingerprinting was used in combination with multivariate statistical analyses for the classification of Greek currants based on their geographical origins (Aeghion, Nemea, Kalamata, Zante, and Amaliada). As classification techniques, Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were carried out. To elucidate different components according to PDO (Protected Designation of Origin), products from Aeghion (Vostizza) were statistically compared with each one of the four other regions. PLS-DA plots ensure that currants from Kalamata, Nemea, Zante, and Amaliada are well classified with respect to the PDO currants, according to differences observed in metabolites. Results suggest that composition differences in carbohydrates, amino, and organic acids of currants are sufficient to discriminate them in correlation to their geographical origin. In conclusion, currants metabolites which mostly contribute to classification performance of such discriminant analysis model present a suitable alternative technique for currants traceability. The study results contribute information to the currants' metabolite fingerprinting by NMR spectroscopy and their geographical origin. PRACTICAL APPLICATION: This study presents an analytical approach for a high nutritional value Greek PDO product, Vostizza currant. A further research and implementation of this method in food industry, can be the key to food fraud incidents. Thus, application of this work opens up posibilities to "farm to table" mission.

Molecular Approaches to Agri-Food Traceability and Authentication: An Updated Review

In the last decades, the demand for molecular tools for authenticating and tracing agri-food products has significantly increased. Food safety and quality have gained an increased interest for consumers, producers, and retailers, therefore, the availability of analytical methods for the determination of food authenticity and the detection of major adulterations takes on a fundamental role. Among the different molecular approaches, some techniques such as the molecular markers-based methods are well established, while some innovative approaches such as isothermal amplification-based methods and DNA metabarcoding have only recently found application in the agri-food sector. In this review, we provide an overview of the most widely used molecular techniques for fresh and processed agri-food authentication and traceability, showing their recent advances and applications and discussing their main advantages and limitations. The application of these techniques to agri-food traceability and authentication can contribute a great deal to the reassurance of consumers in terms of transparency and food safety and may allow producers and retailers to adequately promote their products.

Unique Metabolic Profiles of Korean Rice According to Polishing Degree, Variety, and Geo-Environmental Factors

The precise determination of the chemical composition in crops is important to identify their nutritional and functional value. The current study performed a systematic delineation of the rice metabolome, an important staple in Asia, to investigate the following: (1) comparative features between brown and white rice; (2) variety-specific composition (Ilpum vs. Odae); and (3) cultivation of region-dependent metabolic content. Global metabolic profiling and data-driven statistics identified the exclusive enrichment of compounds in brown rice compared to white rice. Next, the authors investigated a variety-governed metabolic phenotype among various geo-environmental factors. Odae, the early-ripening cultivar, showed higher contents of most chemicals compared to the late-ripening cultivar, Ilpum. The authors identified regional specificity for cultivation among five areas in Korea which were characterized by polishing degree and cultivar type. Finally, the current study proposes a possible linkage of the region-specific metabolic signatures to soil texture and total rainfall. In addition, we found tryptophan metabolites that implied the potential for microbe-host interactions that may influence crop metabolites.

Authentication of Rice (Oryza sativa L.) Using Near Infrared Spectroscopy Combined with Different Chemometric Classification Strategies

Rice is a staple food in Vietnam, and the concern about rice is much greater than that for other foods. Preventing fraud against this product has become increasingly important in order to protect producers and consumers from possible economic losses. The possible adulteration of this product is done by mixing, or even replacing, high-quality rice with cheaper rice. This highlights the need for analytical methodologies suitable for its authentication. Given this scenario, the present work aims at testing a rapid and non-destructive approach to detect adulterated rice samples. To fulfill this purpose, 200 rice samples (72 authentic and 128 adulterated samples) were analyzed by near infrared (NIR) spectroscopy coupled, with partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA). The two approaches provided different results; while PLS-DA analysis was a suitable approach for the purpose of the work, SIMCA was unable to solve the investigated problem. The PLS-DA approach provided satisfactory results in discriminating authentic and adulterated samples (both 5% and 10% counterfeits). Focusing on authentic and 10%-adulterated samples, the accuracy of the approach was even better (with a total classification rate of 82.6% and 82.4%, for authentic and adulterated samples, respectively).

Recent advances in the application of metabolomics for food safety control and food quality analyses

As one of the omics fields, metabolomics has unique advantages in facilitating the understanding of physiological and pathological activities in biology, physiology, pathology, and food science. In this review, based on developments in analytical chemistry tools, cheminformatics, and bioinformatics methods, we highlight the current applications of metabolomics in food safety, food authenticity and quality, and food traceability. Additionally, the combined use of metabolomics with other omics techniques for "foodomics" is comprehensively described. Finally, the latest developments and advances, practical challenges and limitations, and requirements related to the application of metabolomics are critically discussed, providing new insight into the application of metabolomics in food analysis.

Chemical Composition, Total Phenols and Flavonoids Contents and Antioxidant Activity as Nutritive Potential of Roasted Hazelnut Skins (Corylus avellana L.)

The present study evaluates natural composition of Serbian roasted hazelnut skins (HS) with potential role in application as functional nutrient of various food products. Total phenols (TPC) and flavonoids contents (TFC) in HS extracts obtained with different ethanol concentrations (10%—I, 50%—II and 96%—III) and their antioxidant activities were investigated. The highest total phenols content (706.0 ± 9.7 mgGAE/g_extract) was observed in 96% ethanol HS extract. Ethanol HS extracts showed very high antioxidant activity with effective concentrations (EC₅₀) ranged between 0.052 and 0.066 mg/mL. The phenol and flavonoid content of roasted HS extracts I–III was determined by HPLC-ESI-MS/MS analyses. Contents of lipids, proteins, carbohydrates, metals, and C, H, N, S elements in roasted HS were also determined. Relatively high C/N, C/P and C/N/P ratios, rich metal contents and fatty acids composition indicated that hazelnut skin might be a good candidate for use as either human or fungal functional nutrient. In addition, possible application of phenolic HS extracts as UV booster was studied by recording UV spectra (220–440 nm) of 10 mg/L of HS extracts I–III combined with 10 mg/L of chemical sunscreen agent benzophenone-3 and in vitro sun protection factor (SPF) was calculated.

NMR Based Metabolomic Analysis of Health Promoting Phytochemicals in Lentils

Lentils are a high-protein plant food and a valuable source of human nutrition, particularly in the Indian subcontinent. However, beyond sustenance, there is evidence that the consumption of lentils (and legumes in general) is associated with decreased risk of diseases, such as diabetes and cardiovascular disease. Lentils contain health-promoting phytochemicals, such as trigonelline and various polyphenolics. Fourteen lentil genotypes were grown at three locations to explore the variation in phytochemical composition in hulls and cotyledons. Significant differences were measured between genotypes and environments, with some genotypes more affected by environment than others. However, there was a strong genetic effect which indicated that future breeding programs could breed for lentils that product more of these health-promoting phytochemicals.

1H NMR-based metabolomic analysis coupled with reversed-phase solid-phase extraction for sample preparation of Saposhnikovia roots and related crude drugs

¹H NMR-based metabolomics has been applied in research on food, herbal medicine, and natural products. Although excellent results were reported, samples were directly extracted with a deuterated solvent (e.g., methanol-d₄ or D₂O) in most reports. As primary metabolites account for most of the results, data for secondary metabolites are partially reflected. Consequently, secondary metabolites tend to be excluded from factor loading analysis, serving as a significant unfavorable feature of ¹H NMR-based metabolomics when investigating biologically active or functional components in natural products and health foods. Reversed-phase solid-phase extraction column (RP-SPEC) was applied for sample preparation in ¹H NMR-based metabolomics to overcome this feature. The methanol extract from Saposhnikoviae radix (SR), an important crude drug, was fractionated with RP-SPEC into 5% methanol-eluting fractions, and the remaining fraction was collected. Each fraction was subjected to ¹H NMR-based metabolomics and compared to results from conventional ¹H NMR-based metabolomics. Based on principal component analysis (PCA) and partial least squares projections to latent structures discriminant analysis (PLS-DA), the 5% methanol fraction and conventional method reflected the amount of saccharides such as sucrose on the PC1/PLS1 axes, and wild and cultivated samples were discriminated along those axes. The remaining fraction clearly distinguished SR from Peucedanum ledebourielloides root. The compounds responsible for this discrimination were deemed falcarindiol derivatives and other unidentified secondary metabolites from the s-plot on PLS-DA. The secondary metabolites from original plants were, therefore, presumed to be concentrated in the remaining fraction by RP-SPEC treatment and strongly reflected the species differences. The developed series is considered effective to perform quality evaluation of crude drugs and natural products.

Determination of Geographical Origin of Wuchang Rice with the Geographical Indicator by Multielement Analysis

The study aims to investigate whether the multielement analysis result can be used as a fingerprint to identify the geographical origin of Wuchang rice. The element contents of rice and soil samples from three regions in China (Wuchang, Qiqihar, and Jiamusi) were analyzed. The concentrations of 16 elements (Na, Mg, Al, K, Ca, V, Mn, Fe, Co, Cu, Zn, As, Rb, Sr, Cd, and Pb) in 194 rice samples and 112 soil samples from the harvest season in 2013 and 2014 were determined. The analysis of variance and linear discriminant analysis were performed to analyze the variation among regions and rice genotypes and classify the geographical origins of rice. Only the element of Cu showed significant differences among different genotypes. In the discriminant analysis, the overall correct identification rates of the rice samples obtained in 2013 and 2014 were, respectively, 96.6% and 89.6% and the overall correct identification rate for Wuchang rice reached 100%.

Grape and Wine Metabolomics to Develop New Insights Using Untargeted and Targeted Approaches

Chemical analysis of grape juice and wine has been performed for over 50 years in a targeted manner to determine a limited number of compounds using Gas Chromatography, Mass-Spectrometry (GC-MS) and High Pressure Liquid Chromatography (HPLC). Therefore, it only allowed the determination of metabolites that are present in high concentration, including major sugars, amino acids and some important carboxylic acids. Thus, the roles of many significant but less concentrated metabolites during wine making process are still not known. This is where metabolomics shows its enormous potential, mainly because of its capability in analyzing over 1000 metabolites in a single run due to the recent advancements of high resolution and sensitive analytical instruments. Metabolomics has predominantly been adopted by many wine scientists as a hypothesis-generating tool in an unbiased and non-targeted way to address various issues, including characterization of geographical origin (terroir) and wine yeast metabolic traits, determination of biomarkers for aroma compounds, and the monitoring of growth developments of grape vines and grapes. The aim of this review is to explore the published literature that made use of both targeted and untargeted metabolomics to study grapes and wines and also the fermentation process. In addition, insights are also provided into many other possible avenues where metabolomics shows tremendous potential as a question-driven approach in grape and wine research.

NMR-based global metabolomics approach to decipher the metabolic effects of three plant growth regulators on strawberry maturation

Plant growth regulators (PGRs) are commonly used to regulate maturation in strawberry. Despite this, comprehensive assessments of the metabolomic effects of PGRs on strawberry maturation are lacking. In this study, a nuclear magnetic resonance-based approach, combined with multivariate and pathway analysis, was used to evaluate the regulatory effects of gibberellin, forchlorfenuron, and brassinolide, applied at two different maturation stages, on the expression of metabolites in strawberry. The results demonstrated that the PGRs differentially influenced metabolism, whether applied at the same or different maturation stages. Additionally, we also discovered that these different PGRs exhibited some similar metabolic trends when applied at the same growth period. Our findings validate the use of NMR-based metabolomics for identifying subtle changes in the expression of metabolites associated with PGR application.

1H-NMR metabolomics analysis of nutritional components from two kinds of freshwater fish brain extracts

There are a number of bioactive compounds in freshwater fish brains, and their functional roles have not been clearly elucidated. NMR-based metabolic profiling could enable rapid characterization of the nutritional composition a fish's brain. Here, two kinds of freshwater fish brains were investigated, crucian carp and yellow catfish. A ¹H-NMR based metabolomic approach was used to illustrate the nutritional components of these two kinds of brain. At first, the microwave method was utilized to cease the activity of the enzymes in the brain, and the chemicals were extracted for NMR analysis. These two kinds of brain had significant differences in metabolic patterns, and the chemical compositions of the yellow catfish brain were similar to those of rodent and human brains. Furthermore, most of the different metabolites were significantly higher in the yellow catfish, except for acetamide. This study could provide comprehensive information regarding the utilization of fish heads during processing of fish and dietary nutrition guidance.

There are a number of bioactive compounds in freshwater fish brains, and their functional roles have not been clearly elucidated. NMR-based metabolic profiling could provide a rapid characterization of a fish brain's nutritional composition.

NMR-based metabolic study of fruits of Physalis peruviana L. grown in eight different Peruvian ecosystems

The berry of Physalis peruviana L. (Solanaceae) represents an important socio-economical commodity for Latin America. The absence of a clear phenotype renders it difficult to trace its place of origin. In this study, Cape gooseberries from eight different regions within the Peruvian Andes were profiled for their metabolism implementing a NMR platform. Twenty-four compounds could be unequivocally identified and sixteen quantified. One-way ANOVA and post-hoc Tukey test revealed that all of the quantified metabolites changed significantly among regions: Bambamarca I showed the most accumulated significant differences. The coefficient of variation demonstrated high phenotypic plasticity for amino acids, while sugars displayed low phenotypic plasticity. Correlation analysis highlighted the closely coordinated behavior of the amino acid profile. Finally, PLS-DA revealed a clear separation among the regions based on their metabolic profiles, accentuating the discriminatory capacity of NMR in establishing significant phytochemical differences between producing regions of the fruit of P. peruviana L.

Proteomics and metabolomics analysis of hepatic mitochondrial metabolism in alcohol-preferring and non-preferring rats

Alcohol preference induced tolerance in humans and animals when their bodily functions adapt to compensate for the disruption caused by alcohol consumption. This was thought to be an important component of the genetic predisposition to alcoholism. To investigate the underlying mechanisms of hepatic metabolic tolerance during alcohol preference, the alcohol preferring and alcohol non-preferring rats were used in this study. The liver mitochondria were purified for comparative quantitative proteomics analysis, and the liver metabolite extracts were collected for metabolomics analysis. Our study identified 96 differentially expressed hepatic mitochondrial proteins that associated with alcohol preference, the further gene ontology and protein interaction network analysis suggest a down-regulation of amino acid metabolism and up-regulation of lipid metabolism. We found alcohol preference induced a series of enzymes decreased (e.g. SSADH and GABA-T) and several amino acids increased (e.g. glutamate and aspartate) in rat liver, indicating down-regulations of glutamate degradation occurred during alcohol preference. Most of these changes were due to the genetic differences between alcohol preferring and non-preferring animals. Furthermore, this study would provided new insights to further clarify the mechanisms of hepatic metabolic tolerance during alcohol preference.