Evaluation of Anti-Inflammatory Effects of Celery Leaf and Stem Extracts in LPS-Induced RAW 264.7 Cells Using Nitric Oxide Assay and LC-MS Based Metabolomics.

The present work demonstrated and compared the anti-inflammatory effects of celery leaf (CLE) and stem (CSE) extracts. LC-MS-based metabolomics were an effective approach to achieve the biomarker identification and pathway elucidation associated with the reduction in inflammatory responses. The celery extracts suppressed LPS-induced NO production in RAW 264.7 cells, and CLE was five times more effective than CSE. Distinct differences were revealed between the control and celery-treated samples among the 24 characteristic metabolites that were identified. In celery-treated LPS cells, reversals of intracellular (citrulline, proline, creatine) and extracellular (citrulline, lysine) metabolites revealed that the therapeutic outcomes were closely linked to arginine metabolism. Reversals of metabolites when treated with CLE (aspartate, proline) indicated targeted effects on the TCA and urea cycles, while, in the case of CSE (histidine, glucose), the glycolysis and the pentose phosphate pathways were implicated. Subsequently, apigenin and bergapten in CLE were identified as potential biomarkers mediating the anti-inflammatory response.

Untargeted LC-QTOF-MS/MS based metabolomics approach for revealing bioactive components in probiotic fermented coffee brews.

Amidst trends in non-dairy probiotic foods and functional coffees, we recently developed a fermented coffee brew containing high live counts of the probiotics Lacticaseibacillus rhamnosus GG and Saccharomyces boulardii CNCM-I745. However, probiotic fermentation did not alter levels of principal coffee bioactive components based on targeted analyses. Here, to provide therapeutic justification compared to other non-fermented coffee brews, we aimed to discover postbiotics in coffee brews fermented with L. rhamnosus GG and/or S. boulardii CNCM-I745. By using an untargeted LC-QTOF-MS/MS based metabolomics approach coupled with validated multivariate analyses, 37 differential metabolites between fermentation treatments were putatively annotated. These include the production of postbiotics such as 2-isopropylmalate by S. boulardii CNCM-I745, and aromatic amino acid catabolites (indole-3-lactate, p-hydroxyphenyllactate, 3-phenyllactate), and hydroxydodecanoic acid by L. rhamnosus GG. Overall, LC-QTOF based untargeted metabolomics can be an effective approach to uncover postbiotics, which may substantiate additional potential functionalities of probiotic fermented foods compared to their non-fermented counterparts.

Improved detection of key odourants in Arabica coffee using gas chromatography-olfactometry in combination with low energy electron ionisation gas chromatography-quadrupole time-of-flight mass spectrometry.

Four Arabica coffees (Brazil, Colombia, Ethiopia, and Guatemala) yield highly variant odours, attesting to the complexities of coffee aroma that command advanced analytical tools. In this study, their volatiles were extracted using solvent-assisted flavour evaporation (SAFE) and headspace solid-phase microextraction (HS-SPME). Due to matrix complexity, some trace odourants were detected in SAFE extracts by aroma extract dilution analysis (AEDA) but remained difficult to quantify by gas chromatography-mass spectrometry (GC-MS). This prompted the application of low energy electron ionisation (EI) coupled with GC-quadrupole time-of-flight (GC-QTOF). Optimal low EI GC-QTOF parameters (EI energy: 15 eV, acquisition rate: 3 Hz) were applied to achieve improved molecular ion signal intensity and reproducibility (relative standard deviation < 10%) across five compounds, which resulted in good linearity (R2 ≥ 0.999) and lowered detection levels (e.g. 0.025 ±â€¯0.005 ng/mL for 4-hydroxy-5-methyl-3(2H)-furanone). Therefore, this method potentially improves the measurement of trace odourants in complex matrices by increasing specificity and sensitivity.