Exploring the potential of omics technologies in medicinal plant research: a review in Colombia / Explorando el potencial de las tecnologías ómicas en la investigación de plantas medicinales: una revisión en Colombia

This review presents advances in the implementation of high - throughput se quencing and its application to the knowledge of medicinal plants. We conducted a bibliographic search of papers published in PubMed, Science Direct, Google Scholar, Scopus, and Web of Science databases and analyzed the obtained data using VOSviewer (versi on 1.6.19). Given that medicinal plants are a source of specialized metabolites with immense therapeutic values and important pharmacological properties, plant researchers around the world have turned their attention toward them and have begun to examine t hem widely. Recent advances in sequencing technologies have reduced cost and time demands and accelerated medicinal plant research. Such research leverages full genome sequencing, as well as RNA (ribonucleic acid) sequencing and the analysis of the transcr iptome, to identify molecular markers of species and functional genes that control key biological traits, as well as to understand the biosynthetic pathways of bioactive metabolites and regulatory mechanisms of environmental responses. As such, the omics ( e.g., transcriptomics, metabolomics, proteomics, and genomics, among others) have been widely applied within the study of medicinal plants, although their usage in Colombia is still few and, in some areas, scarce. (185)

El extracto de cloroformo (CE) y las fracciones obtenidas de las raíces de Aldama arenaria se evaluaron para determinar su actividad antiproliferativa in vitro contra 10 líneas ce lulares tumorales humanas [leucemia (K - 562), mama (MCF - 7), ovario que expresa un fenotipo resistente a múltiples fármacos (NCI/ADR - RES), melanoma (UACC - 62), pulmón (NCI - H460), próstata (PC - 3), colon (HT29), ovario (OVCAR - 3), glioma (U251) y riñón (786 - 0)]. CE presentó actividad antiproliferativa débil a moderada (log GI 50 medio 1.07), mientras que las fracciones 3 y 4, enriquecidas con diterpenos de tipo pimarane [ent - pimara - 8 (14), ácido 15 - dien - 19 - oico y ent - 8(14),15 - pimaradien - 3 ß - ol], presentaron activid ad moderada a potente para la mayoría de las líneas celulares, con un log GI 50 medio de 0.62 y 0.59, respectivamente. Los resultados mostraron una acción antiproliferativa in vitro prometedora de las muestras obtenidas de A. arenaria , con los mejores resul tados para NCI/ADR - RES, HT29 y OVCAR - 3, y valores de TGI que van desde 5.95 a 28.71 µg.mL - 1, demostrando que los compuestos de esta clase pueden ser prototipos potenciales para el descubrimiento de nuevos agentes terapéuticos

Chemical composition and antioxidant activity of Polygonatum kingianum processed by the traditional method of "Nine Cycles of Steaming and Sun-Drying".

Polygonatum kingianum Coll. et (Hemsl) is a famous Chinese traditional food and medicine analogous plant. The rhizome of P. kingianum showed a decrease in levels of alkaloids, amino acids and derivatives, terpenoids, and an increase in organic acid and saccharides when it was processed by the traditional method of "Nine Cycles of Steaming and Sun-Drying". The relative content of 341 metabolites were increased (fold change, FC > 2; variable importance in projection, VIP > 1 and P-value, P < 0.05); while 456 metabolites were decreased (FC < 0.5, VIP > 1, and P < 0.05). The changes in chemical components result in a decrease in numb taste and an increase in sweetness. The increased antioxidant activity was observed in the processed samples. Together, this work has advanced the mechanism of reducing numb taste and enhancing antioxidant activity in the resource plants, such as P. kingianum, processed by the traditional method.

Mulberry and Hippophae-based solid beverage promotes weight loss in rats by antagonizing white adipose tissue PPARγ and FGFR1 signaling.

Obesity, a multifactorial disease with many complications, has become a global epidemic. Weight management, including dietary supplementation, has been confirmed to provide relevant health benefits. However, experimental evidence and mechanistic elucidation of dietary supplements in this regard are limited. Here, the weight loss efficacy of MHP, a commercial solid beverage consisting of mulberry leaf aqueous extract and Hippophae protein peptides, was evaluated in a high-fat high-fructose (HFF) diet-induced rat model of obesity. Body component analysis and histopathologic examination confirmed that MHP was effective to facilitate weight loss and adiposity decrease. Pathway enrichment analysis with differential metabolites generated by serum metabolomic profiling suggests that PPAR signal pathway was significantly altered when the rats were challenged by HFF diet but it was rectified after MHP intervention. RNA-Seq based transcriptome data also indicates that MHP intervention rectified the alterations of white adipose tissue mRNA expressions in HFF-induced obese rats. Integrated omics reveals that the efficacy of MHP against obesogenic adipogenesis was potentially associated with its regulation of PPARγ and FGFR1 signaling pathway. Collectively, our findings suggest that MHP could improve obesity, providing an insight into the use of MHP in body weight management.

Therapeutic potential of Thai herbal formula for cognitive impairment: A metabolomics approach for Comprehensive Insights.

Chronic cerebral ischemia hypoperfusion plays a role in the initiation and progression of vascular dementia, which causes changes in metabolites. Currently, there is no standard treatment to treat, prevent and reduce the severity of this condition. Thai herbal Yahom no.20 (YHF20) is indicated for fatigue and dizziness. The components of YHF20 have been found to have pharmacological effects related to the pathology of chronic cerebral ischemia hypoperfusion. This study aimed to investigate metabolomic changes after YHF20 administration in a rat model of permanent bilateral common carotid artery occlusion (2-VO) induced chronic cerebral ischemia hypoperfusion, and to explore its impact on spatial learning and memory. Albino Wistar rats were randomly allocated to 5 groups; sham, 2-VO, 2-VO+ 100 mg/kg YHF20, 2-VO+300 mg/kg YHF20, and 2-VO+1000 mg/kg YHF20. The rats were administered YHF20 daily by oral gavage for 56 days after 2-VO induction. Plasma was collected weekly for metabolome change analysis using LC-MS/QTof and toxicity study. The rats were evaluated for spatial learning and memory using the Morris water maze. The results showed that 78 known metabolites and 10 tentative pathways altered after chronic cerebral hypoperfusion, although it was not able to determine the effect on memory and learning behaviors of rats. Glutathione and glutathione metabolism might be metabolite-pathway that were the affect after YHF20 administration in cerebral ischemic condition. The 4 known metabolites may be the metabolites from the constituents of YHF20 could be considered and confirmed for quality control purpose. In conclusion, YHF20 administration might contribute to metabolic changes related to cerebral ischemia condition without the effect on spatial learning and memory, including hepatotoxicity and nephrotoxicity after 56 days of treatment. Alterations in the potential metabolites may provide data support for elucidating dementia pathogenesis and selecting pathways for intervention.

Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data.

Objective: Classification tasks are an open challenge in the field of biomedicine. While several machine-learning techniques exist to accomplish this objective, several peculiarities associated with biomedical data, especially when it comes to omics measurements, prevent their use or good performance achievements. Omics approaches aim to understand a complex biological system through systematic analysis of its content at the molecular level. On the other hand, omics data are heterogeneous, sparse and affected by the classical "curse of dimensionality" problem, i.e. having much fewer observation, samples (n) than omics features (p). Furthermore, a major problem with multi-omics data is the imbalance either at the class or feature level. The objective of this work is to study whether feature extraction and/or feature selection techniques can improve the performances of classification machine-learning algorithms on omics measurements. Methods: Among all omics, metabolomics has emerged as a powerful tool in cancer research, facilitating a deeper understanding of the complex metabolic landscape associated with tumorigenesis and tumor progression. Thus, we selected three publicly available metabolomics datasets, and we applied several feature extraction techniques both linear and non-linear, coupled or not with feature selection methods, and evaluated the performances regarding patient classification in the different configurations for the three datasets. Results: We provide general workflow and guidelines on when to use those techniques depending on the characteristics of the data available. To further test the extension of our approach to other omics data, we have included a transcriptomics and a proteomics data. Overall, for all datasets, we showed that applying supervised feature selection improves the performances of feature extraction methods for classification purposes. Scripts used to perform all analyses are available at: https://github.com/Plant-Net/Metabolomic_project/.

Systematic review of metabolomic alterations in ulcerative colitis: unveiling key metabolic signatures and pathways.

Background: Despite numerous metabolomic studies on ulcerative colitis (UC), the results have been highly variable, making it challenging to identify key metabolic abnormalities in UC. Objectives: This study aims to uncover key metabolites and metabolic pathways in UC by analyzing existing metabolomics data. Design: A systematic review. Data sources and methods: We conducted a comprehensive search in databases (PubMed, Cochrane Library, Embase, and Web of Science) and relevant study references for metabolomic research on UC up to 28 December 2022. Significant metabolite differences between UC patients and controls were identified, followed by an analysis of relevant metabolic pathways. Results: This review incorporated 78 studies, identifying 2868 differentially expressed metabolites between UC patients and controls. The metabolites were predominantly from 'lipids and lipid-like molecules' and 'organic acids and derivatives' superclasses. We found 101 metabolites consistently altered in multiple datasets within the same sample type and 78 metabolites common across different sample types. Of these, 62 metabolites exhibited consistent regulatory trends across various datasets or sample types. Pathway analysis revealed 22 significantly altered metabolic pathways, with 6 pathways being recurrently enriched across different sample types. Conclusion: This study elucidates key metabolic characteristics in UC, offering insights into molecular mechanisms and biomarker discovery for the disease. Future research could focus on validating these findings and exploring their clinical applications.

Urinary metabolic characterization of advanced tuberculous meningitis cases in a South African paediatric population.

Tuberculous meningitis (TBM) is a severe form of tuberculosis with high neuro-morbidity and mortality, especially among the paediatric population (aged ≤12 years). Little is known of the associated metabolic changes. This study aimed to identify characteristic metabolic markers that differentiate severe cases of paediatric TBM from controls, through non-invasive urine collection. Urine samples selected for this study were from two paediatric groups. Group 1: controls (n = 44): children without meningitis, no neurological symptoms and from the same geographical region as group 2. Group 2: TBM cases (n = 13): collected from paediatric patients that were admitted to Tygerberg Hospital in South Africa on the suspicion of TBM, mostly severely ill; with a later confirmation of TBM. Untargeted 1H NMR-based metabolomics data of urine were generated, followed by statistical analyses via MetaboAnalyst (v5.0), and the identification of important metabolites. Twenty nine urinary metabolites were identified as characteristic of advanced TBM and categorized in terms of six dysregulated metabolic pathways: 1) upregulated tryptophan catabolism linked to an altered vitamin B metabolism; 2) perturbation of amino acid metabolism; 3) increased energy production-metabolic burst; 4) disrupted gut microbiota metabolism; 5) ketoacidosis; 6) increased nitrogen excretion. We also provide original biological insights into this biosignature of urinary metabolites that can be used to characterize paediatric TBM patients in a South African cohort.

Chinmedomics strategy for elucidating the effects and effective constituents of Danggui Buxue Decoction in treating blood deficiency syndrome.

Introduction: Danggui Buxue Decoction (DBD) is a clinically proven, effective, classical traditional Chinese medicine (TCM) formula for treating blood deficiency syndrome (BDS). However, its effects and effective constituents in the treatment of BDS remain unclear, limiting precise clinical therapy and quality control. This study aimed to accurately evaluate the effects of DBD and identify its effective constituents and quality markers. Methods: BDS was induced in rats by a combined injection of acetylphenylhydrazine and cyclophosphamide, and the efficacy of DBD against BDS was evaluated based on body weight, body temperature, energy metabolism, general status, visceral indices, histopathology, biochemical markers, and metabolomics. The effects of DBD on urinary and serum biomarkers of BDS were investigated, and the associated metabolic pathways were analyzed via metabolomics. Guided by Chinmedomics, the effective constituents and quality markers of DBD were identified by analyzing the dynamic links between metabolic biomarkers and effective constituents in vivo. Results: DBD improved energy metabolism, restored peripheral blood and serum biochemical indices, and meliorated tissue damage in rats with BDS. Correlation analyses between biochemical indices and biomarkers showed that 15(S)-HPETE, LTB4, and taurine were core biomakers and that arachidonic acid, taurine, and hypotaurine metabolism were core metabolic pathways regulated by DBD. Calycosin-7-glucoside, coumarin, ferulic acid sulfate, cycloastragenol, (Z)-ligustilide + O, astragaloside IV, acetylastragaloside I, and linoleic acid were identified as effective constituents improving the hematopoietic function of the rats in the BDS model. Additionally, calycosin-7-glucoside, ferulic acid, ligustilide, and astragaloside IV were identified as quality markers of DBD. Conclusion: The hematopoietic function of DBD was confirmed through analysis of energy metabolism, biochemical markers, histopathology, and metabolomics. Moreover, by elucidating effective constituents of DBD in BDS treatment, quality markers were confirmed using a Chinmedomics strategy. These results strengthen the quality management of DBD and will facilitate drug innovation.

Characterizing arginine, ornithine, and putrescine pathways in enteric pathobionts.

Arginine-ornithine metabolism plays a crucial role in bacterial homeostasis, as evidenced by numerous studies. However, the utilization of arginine and the downstream products of its metabolism remain undefined in various gut bacteria. To bridge this knowledge gap, we employed genomic screening to pinpoint relevant metabolic targets. We also devised a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics method to measure the levels of arginine, its upstream precursors, and downstream products in cell-free conditioned media from enteric pathobionts, including Escherichia coli, Klebsiella aerogenes, K. pneumoniae, Pseudomonas fluorescens, Acinetobacter baumannii, Streptococcus agalactiae, Staphylococcus epidermidis, S. aureus, and Enterococcus faecalis. Our findings revealed that all selected bacterial strains consumed glutamine, glutamate, and arginine, and produced citrulline, ornithine, and GABA in our chemically defined medium. Additionally, E. coli, K. pneumoniae, K. aerogenes, and P. fluorescens were found to convert arginine to agmatine and produce putrescine. Interestingly, arginine supplementation promoted biofilm formation in K. pneumoniae, while ornithine supplementation enhanced biofilm formation in S. epidermidis. These findings offer a comprehensive insight into arginine-ornithine metabolism in enteric pathobionts.

Integration of widely targeted metabolomics and the e-tongue reveals the chemical variation and taste quality of Yunnan Arabica coffee prepared using different primary processing methods.

UPLC-Q-TOF-MS and electronic tongue analysis were applied to analyse the metabolic profile and taste quality of Yunnan Arabica coffee under seven primary processing methods. The total phenolic content ranged from 34.44 to 44.42 mg/g DW, the e-tongue results revealed the strongest umami sensor response value in the sample prepared with traditional dry processing, while the samples prepared via honey processing II had the strongest astringency sensor response value. Metabolomics analysis identified 221 differential metabolites, with higher contents of amino acids and derivatives within dry processing II sample, and increased contents of lipids and phenolic acids in the honey processing III sample. The astringency and aftertaste-astringency of the coffee samples positively correlated with the trigonelline, 3,5-di-caffeoylquinic acid and 4-caffeoylquinic acid content. The results contributed to a better understanding of how the primary processing process affects coffee quality, and supply useful information for the enrichment of coffee biochemistry theory.

UPLC-ESI-MS/MS-based widely targeted metabolomics reveals differences in metabolite composition among four Ganoderma species.

The Chinese name "Lingzhi" refers to Ganoderma genus, which are increasingly used in the food and medical industries. Ganoderma species are often used interchangeably since the differences in their composition are not known. To find compositional metabolite differences among Ganoderma species, we conducted a widely targeted metabolomics analysis of four commonly used edible and medicinal Ganoderma species based on ultra performance liquid chromatography-electrospray ionization-tandem mass spectrometry. Through pairwise comparisons, we identified 575-764 significant differential metabolites among the species, most of which exhibited large fold differences. We screened and analyzed the composition and functionality of the advantageous metabolites in each species. Ganoderma lingzhi advantageous metabolites were mostly related to amino acids and derivatives, as well as terpenes, G. sinense to terpenes, and G. leucocontextum and G. tsugae to nucleotides and derivatives, alkaloids, and lipids. Network pharmacological analysis showed that SRC, GAPDH, TNF, and AKT1 were the key targets of high-degree advantage metabolites among the four Ganoderma species. Analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes demonstrated that the advantage metabolites in the four Ganoderma species may regulate and participate in signaling pathways associated with diverse cancers, Alzheimer's disease, and diabetes. Our findings contribute to more targeted development of Ganoderma products in the food and medical industries.

Analysis of blood biochemistry and non-targeted metabolomics of endometritis in dairy cows.

The incidence of bovine endometritis, which has a negative impact on the reproduction of dairy cows, has been recently increasing. In this study, the differential markers and metabolites of healthy cows and cows with endometritis were analyzed by measuring blood biochemical indicators and immune factors using biochemical and enzyme-linked immunosorbent assay kits combined with nontargeted metabolomics. The LC-QTOF platform was used to evaluate the serum metabolomics of healthy cows and cows with endometritis after 21-27 days of calving. The results showed that glucose, free fatty acid, calcium, sodium, albumin, and alanine aminotransferase levels were significantly lower in the serum of cows with endometritis than in healthy cows (P < 0.05). However, the serum potassium, interleukin-1, interleukin-6, and tumor necrosis factor levels were significantly higher in cows with endometritis (P < 0.05). In addition, the serum metabolome data analysis of the two groups showed that the expression of 468 metabolites was significantly different (P < 0.05), of which 291 were upregulated and 177 were downregulated. These metabolites were involved in 78 metabolic pathways, including amino acid, nucleotide, carbohydrate, lipid, and vitamin metabolism pathways; signal transduction pathways, and other biological pathways. Taken together, negative energy balance and immune activation, which are related to local abnormalities in amino acid, lipid, and carbohydrate metabolism, were the important causes of endometritis in dairy cows. Metabolites such as glucose, carnosine, dehydroascorbic acid, L-malic acid, tetrahydrofolic acid, and UDP-glucose may be used as key indicators in the hematological diagnosis and treatment of endometritis in dairy cows.

Oxidized glutathione reverts carbapenem resistance in blaNDM-1-carrying Escherichia coli.

The emergence of drug-resistant Enterobacteriaceae carrying plasmid-mediated ß-lactamase genes has become a significant threat to public health. Organisms in the Enterobacteriaceae family containing New Delhi metallo-ß-lactamase­1 (NDM-1) and its variants, which are capable of hydrolyzing nearly all ß-lactam antibacterial agents, including carbapenems, are referred to as superbugs and distributed worldwide. Despite efforts over the past decade, the discovery of an NDM-1 inhibitor that can reach the clinic remains a challenge. Here, we identified oxidized glutathione (GSSG) as a metabolic biomarker for blaNDM-1 using a non-targeted metabolomics approach and demonstrated that GSSG supplementation could restore carbapenem susceptibility in Escherichia coli carrying blaNDM-1 in vitro and in vivo. We showed that exogenous GSSG promotes the bactericidal effects of carbapenems by interfering with intracellular redox homeostasis and inhibiting the expression of NDM-1 in drug-resistant E. coli. This study establishes a metabolomics-based strategy to potentiate metabolism-dependent antibiotic efficacy for the treatment of antibiotic-resistant bacteria.

Dietary Supplementation with Nervonic Acid Ameliorates Cerebral Ischemia-Reperfusion Injury by Modulating of Gut Microbiota Composition-Fecal Metabolites Interaction.

SCOPE: Cerebral ischemia-reperfusion (IR) injury stands as a prominent global contributor to disability and mortality. Nervonic acid (NA), a bioactive elongated monounsaturated fatty acid, holds pivotal significance in human physiological well-being. This research aims to explore the prophylactic effects and fundamental mechanisms of NA in a rat model of cerebral IR injury. METHODS AND RESULTS: Through the induction of middle cerebral artery occlusion, this study establishes a rat model of cerebral IR injury and comprehensively assesses the pharmacodynamic impacts of NA pretreatment. This evaluation involves behavioral analyses, histopathological examinations, and quantification of serum markers. Detailed mechanisms of nervonic acid's prophylactic effects are revealed through fecal metabolomics and 16S rRNA sequencing analyses. Our findings robustly support nervonic acid's capacity to ameliorate neurological impairments in rats afflicted with cerebral IR injury. Beyond its neurological benefits, NA demonstrates its potential by rectifying metabolic perturbations across diverse pathways, particularly those pertinent to unsaturated fatty acid metabolism. Additionally, NA emerges as a modulator of gut microbiota composition, notably by selectively enhancing vital genera like Lactobacillus. CONCLUSION: These comprehensive findings highlight the potential of incorporating NA as a functional component in dietary interventions aimed at targeting cerebral IR injury.

Method Development for Omics Analyses using Schirmer Strips.

PURPOSE: The aim of this article was to investigate whether Schirmer strips gathered during clinical dry eye examinations can be prepared for omics analyses in a standardized way, to adjust for variations in tear volume and enable two separate omics analyses from the same sample. In addition, the intention was to investigate whether fluorescein dye instillation in the eyes gave bias effects on metabolomic analysis. METHODS: Twelve samples from six individuals, with normal or reduced tear production, were collected. Half of the samples were harvested after instillation of fluorescein in the eye. Each strip was divided in half along the length and prepared with a new method for extracting tear content from the Schirmer strip. The new method was established to compensate for different dilutions of metabolites in varying Schirmer strip wetting levels when using identical extraction volume for all samples. Metabolomic data were compared in samples with and without fluorescein dye and Schirmer strips ranging from 1 to 35 mm wetting levels using a global LC-MS method. RESULTS: All samples were successfully analyzed with an average of ∼350 relevant features detected per sample after using both positive and negative electrospray ionization mode, despite low tear volumes in some samples and that only one half of the Schirmer strips were used. Principal component analysis plots and heatmaps revealed no bias effects of fluorescein dye presence or different Schirmer strip values when using the proposed method. CONCLUSION: A high number of relevant metabolomic features can be extracted from longitudinally cut halves of Schirmer strips, which may enable analyses with more than one omics modality from the same sample. With the pre-analytical method described, Schirmer strips can be used for metabolomic analyses even in cases of very low or high tear volume with or without fluorescence.

Metabolomic profiling of maternal plasma identifies inverse associations of acetate and urea with anti-SARS-CoV-2 antibody titers following COVID-19 vaccination during pregnancy.

We conducted a comprehensive metabolomic analysis of plasma samples obtained from pregnant women who displayed varying post-vaccination antibody titers after receiving mRNA-1273-SARS-CoV-2 vaccines. The study involved 62 pregnant women, all of whom had been vaccinated after reaching 24 weeks of gestation. To quantify post-vaccination plasma antibody titers, we employed binding antibody units (BAU) in accordance with the World Health Organization International Standard. Subsequently, we classified the study participants into three distinct BAU/mL categories: those with high titers (above 2000), medium titers (ranging from 1000 to 2000), and low titers (below 1000). Plasma metabolomic profiling was conducted using 1H nuclear magnetic resonance spectroscopy, and the obtained data were correlated with the categorized antibody titers. Notably, in pregnant women exhibiting elevated anti-SARS-CoV-2 antibody titers, reduced plasma concentrations of acetate and urea were observed. A significant negative correlation between these compounds and antibody titers was also evident. An analysis of metabolomics pathways revealed significant inverse associations between antibody titers and four distinct amino acid metabolic pathways: (1) biosynthesis of phenylalanine, tyrosine, and tryptophan; (2) biosynthesis of valine, leucine, and isoleucine; (3) phenylalanine metabolism; and (4) degradation of valine, leucine, and isoleucine. Additionally, an association between the synthesis and degradation pathways of ketone bodies was evident. In conclusion, we identified different metabolic pathways that underlie the diverse humoral responses triggered by COVID-19 mRNA vaccines during pregnancy. Our data hold significant implications for refining COVID-19 vaccination approaches in expectant mothers. KEY MESSAGES : Anti-SARS-CoV-2 antibody titers decline as the number of days since COVID-19 vaccination increases. Anti-SARS-CoV-2 antibody titers are inversely associated with acetate, a microbial-derived metabolite, and urea. Amino acid metabolism is significantly associated with SARS-CoV-2 antibody titers.

Deciphering feedback regulation of prostaglandin F2α in blood stasis syndrome using nitrogen-doped porous transition metal carbides.

Blood stasis syndrome (BSS) has persistent health risks; however, its pathogenesis remains elusive. This obscurity may result in missed opportunities for early intervention, increased susceptibility to chronic diseases, and reduced accuracy and efficacy of treatments. Metabolomics, employing the matrix-assisted laser desorption/ionization (MALDI) strategy, presents distinct advantages in biomarker discovery and unraveling molecular mechanisms. Nonetheless, the challenge is to develop efficient matrices for high-sensitivity and high-throughput analysis of diverse potential biomarkers in complex biosamples. This work utilized nitrogen-doped porous transition metal carbides and nitrides (NP-MXene) as a MALDI matrix to delve into the molecular mechanisms underlying BSS pathogenesis. Structural optimization yielded heightened peak sensitivity (by 1.49-fold) and increased peak numbers (by 1.16-fold) in clinical biosamples. Validation with animal models and clinical serum biosamples revealed significant differences in metabolic fingerprints between BSS and control groups, achieving an overall diagnostic efficacy of 0.905 (95% CI, 0.76-0.979). Prostaglandin F2α was identified as a potential biomarker (diagnostics efficiency of 0.711, specificity = 0.7, sensitivity = 0.6), and pathway enrichment analysis disclosed disruptions in arachidonic acid metabolism in BSS. This innovative approach not only advances comprehension of BSS pathogenesis, but also provides valuable insights for personalized treatment and diagnostic precision.

Combined sensory, volatilome and transcriptome analyses identify a limonene terpene synthase as a major contributor to the characteristic aroma of a Coffea arabica L. specialty coffee.

BACKGROUND: The fruity aromatic bouquet of coffee has attracted recent interest to differentiate high value market produce as specialty coffee. Although the volatile compounds present in green and roasted coffee beans have been extensively described, no study has yet linked varietal molecular differences to the greater abundance of specific substances and support the aroma specificity of specialty coffees. RESULTS: This study compared four Arabica genotypes including one, Geisha Especial, suggested to generate specialty coffee. Formal sensory evaluations of coffee beverages stressed the importance of coffee genotype in aroma perception and that Geisha Especial-made coffee stood out by having fine fruity, and floral, aromas and a more balanced acidity. Comparative SPME-GC-MS analyses of green and roasted bean volatile compounds indicated that those of Geisha Especial differed by having greater amounts of limonene and 3-methylbutanoic acid in agreement with the coffee cup aroma perception. A search for gene ontology differences of ripening beans transcriptomes of the four varieties revealed that they differed by metabolic processes linked to terpene biosynthesis due to the greater gene expression of prenyl-pyrophosphate biosynthetic genes and terpene synthases. Only one terpene synthase (CaTPS10-like) had an expression pattern that paralleled limonene loss during the final stage of berry ripening and limonene content in the studied four varieties beans. Its functional expression in tobacco leaves confirmed its functioning as a limonene synthase. CONCLUSIONS: Taken together, these data indicate that coffee variety genotypic specificities may influence ripe berry chemotype and final coffee aroma unicity. For the specialty coffee variety Geisha Especial, greater expression of terpene biosynthetic genes including CaTPS10-like, a limonene synthase, resulted in the greater abundance of limonene in green beans, roasted beans and a unique citrus note of the coffee drink.