Evaluation of the physiochemical and metabolite of different region coffee beans by using UHPLC-QE-MS untargeted-metabonomics approaches

Utilizing metabolomics and network analysis to explore the effects of artificial production methods on the chemical composition and activity of agarwood

Introduction: Agarwood is a traditional aromatic southern medicine. It has a long history of being used in traditional Chinese aromatherapy to treat insomnia, anxiety and depression. Due to the scarcity of wild resources, people have planted trees successfully and begun to explore various agarwood-inducing techniques. This study comparative analysis of volatile metabolites in agarwood produced by various inducing techniques and its potential sleep-promoting, anti-anxiety and anti-depressant network pharmacological activities. Methods: A total of 23 batches of two types of agarwood were collected, one of which was produced by artificial techniques, including 6 batches of TongTi (TT) agarwood produced by "Agar-Wit" and 6 batches of HuoLao (HL) agarwood produced by "burning, chisel and drilling", while the other was collected from the wild, including 6 batches of BanTou (BT) agarwood with trunks broken due to natural or man-made factors and 5 batches of ChongLou (CL) agarwood with trunks damaged by moth worms. The study employed metabolomics combined with network analysis to compare the differences in volatile metabolites of agarwood produced by four commonly used inducing techniques, and explored their potential roles and possible action targets in promoting sleep, reducing anxiety, and alleviating depression. Results: A total of 147 volatile metabolites were detected in agarwood samples, mainly including small aromatic hydrocarbons, sesquiterpenes and 2-(2-phenylethyl) chromone and their pyrolysis products. The results showed composition of metabolites was minimally influenced by the agarwood induction method. However, their concentrations exhibited significant variations, with 17 metabolites showing major differences. The two most distinct metabolites were 6-methoxy-2-(2-phenylethyl) chromone and 6,7-dimethoxy-2-(2-phenylethyl) chromone. Among the volatile metabolites, 142 showed promising potential in treating insomnia, anxiety, and depression, implicating various biological and signaling pathways, predominantly ALB and TNF targets. The top three active metabolites identified were 2-(2-phenylethyl) chromone, 1,5-diphenylpent-1-en-3-one, and 6-methoxy-2-[2-(4'-methoxyphenyl) ethyl] chromone, with their relative content in the four types of agarwood being TT>HL>CL>BT. Conclusion: The differences in the content of 2-(2-phenylethyl) chromones suggest that they may be responsible for the varying therapeutic activities observed in different types of agarwood aromatherapy. This study offers theoretical support for the selection of agarwood in aromatherapy practices.

Multi-omics in food safety and authenticity in terms of food components

One of the main goals of food science is to ensure the high quality and safety of food. The inspection technology for known hazards has matured, and the identification of unknown and potential food safety hazards, as well as the identification of their composition and origin, is a challenge faced by food safety. Food safety and authenticity require multi-omics methods to support the implementation of qualitative discrimination to precise quantitative analysis, from targeted screening to non-target detection, and from multi component to full component analysis to address these challenges. The present review aims to provide characterizations, advantages, the latest progress, and prospects of using omics (including genomics, proteomics, and metabonomics) in food safety and authenticity. Multi omics strategies used to detect and verify different standard biomarkers of food will contribute to understanding the basic relationship between raw materials, processing, foods, nutrition, food safety, and human health.

Assessing the impact of Chlorantraniliprole (CAP) pesticide stress on oilseed rape (Brassia campestris L.): Residue dynamics, enzyme activities, and metabolite profiling

This study investigates the effects of chlorantraniliprole (CAP) pesticide stress on oilseed rape through comprehensive pot experiments. Assessing CAP residue variations in soil and oilseed rape (Brassia campestris L.), enzyme activities (POD, CPR, GST), and differential metabolites, we unveil significant findings. The average CAP residue levels were 18.38-13.70 mg/kg in unplanted soil, 9.94-6.30 mg/kg in planted soil, and 0-4.18 mg/kg in oilseed rape samples, respectively. Soil microbial influences and systemic pesticide translocation into oilseed rape contribute to CAP residue variations. Under the influence of CAP stress, oilseed rape displays escalated enzyme activities (POD, CPR, GST) and manifests 57 differential metabolites. Among these, 32 demonstrate considerable downregulation, mainly impacting amino acids and phenolic compounds, while 25 exhibit noteworthy overexpression, primarily affecting flavonoid compounds. This impact extends to 24 metabolic pathways, notably influencing amide biosynthesis, as well as arginine and proline metabolism. These findings underscore the discernible effects of CAP pesticide stress on oilseed rape.

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.

Identification of potential quality markers in Indonesia's Arabica specialty coffee using GC/MS-based metabolomics approach

INTRODUCTION

The cupping test is a widely used method for quality assessment of Arabica coffee. However, the cupping test is limited by the low number of certified panelists and the low throughput. Therefore, an analytical-based quality assessment may be a promising tool to complement the cupping test. A present, there is no report investigating quality marker candidates, focusing only on "specialty" grade Arabica coffee from Indonesia.

OBJECTIVE

This study identified the potential quality marker(s) in Arabica Specialty coffee at different stages (green beans, roasted beans, and brewed coffee.

METHODS

The metabolite profiles of ten different Arabica specialty-grade coffees were analyzed with different cup scores using gas chromatography-mass spectrometry (GC/MS). From the ten samples, green coffee beans, roasted coffee beans, and brewed coffee were selected. In addition, an orthogonal projection to latent structure (OPLS) regression analysis was conducted to obtain a potential quality marker based on the variable importance in projection (VIP). The potential quality marker(s) were validated by GC/MS metabolome profiling and OPLS analysis of different sets of samples consisting of 35 Arabica specialty-grade coffee samples.

RESULTS

In Arabica coffee samples, the OPLS model of the three stages showed galactinol to have a high VIP score. Galactinol showed a consistent positive correlation with cup scores at all stages of coffee production (green beans, roasted beans, and brewed coffee). The correlation suggests galactinol is a potential quality marker after further validation using different samples.

CONCLUSION

GC/MS combined with OPLS regression analysis suggested galactinol as a quality marker and provide an early screening method for Arabica coffee quality that complements the cupping test performed by certified panelists.

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.

Paper Spray Mass Spectrometry as an Effective Tool for Differentiating Coffees Based on Their Geographical Origins

With the rising trend of valuing flavor complexity of coffees, means to distinguish the properties of individual coffee sources is vital to the sustainable growth of the coffee industry. Herein, paper spray mass spectrometry (PS-MS), a simple technique with little sample preparation, was used to collect mass data from aqueous extracts of coffees from various sources. Thereafter, principal component analysis and linear discriminant analysis were used to successfully classify coffee samples (with 80-100 % accuracy) from various studies including the differentiations of Arabica and Robusta coffees, Arabica coffees from different countries, Robusta coffees from different geographical locations, and Arabica coffees from different locations within the same province in Thailand. With further insight from significant test via Fisher weight determination, this method was proved to be practical for differentiating coffees based on types and geographical origins, thus paving the way for broader applications.

Interactive deciphering electron-shuttling characteristics of Coffea arabica leaves and potential bioenergy-steered anti-SARS-CoV-2 RdRp inhibitor via microbial fuel cells

Due to the pandemics of COVID-19, herbal medicine has recently been explored for possible antiviral treatment and prevention via novel platform of microbial fuel cells. It was revealed that Coffea arabica leaves was very appropriate for anti-COVID-19 drug development. Antioxidant and anti-inflammatory tests exhibited the most promising activities for C. arabica ethanol extracts and drying approaches were implemented on the leaf samples prior to ethanol extraction. Ethanol extracts of C. arabica leaves were applied to bioenergy evaluation via DC-MFCs, clearly revealing that air-dried leaves (CA-A-EtOH) exhibited the highest bioenergy-stimulating capabilities (ca. 2.72 fold of power amplification to the blank). Furthermore, molecular docking analysis was implemented to decipher the potential of C. arabica leaves metabolites. Chlorogenic acid (-6.5 kcal/mol) owned the highest binding affinity with RdRp of SARS-CoV-2, showing a much lower average RMSF value than an apoprotein. This study suggested C. arabica leaves as an encouraging medicinal herb against SARS-CoV-2.