Keeping Analytical Chemistry Training Up-to-Date.

The undergraduate analytical chemistry curriculum serves to equip students with the knowledge and skills for work outside of classroom training. As such, instructors face a challenging task in deciding the breadth and depth of topics for their courses to ensure their syllabi can remain up-to-date with today's needs. We propose that instructors consider covering capillary electrophoresis (CE) and lab-on-a-chip (LOC) technologies in their analytical chemistry courses. Past surveys of the curriculum show a noticeable lack of emphasis on these topics, which we feel is a missed opportunity and one that holds potential for the collective benefit of instructors and students. CE and LOCs are utilized in a diverse array of fields like biochemistry, pharmaceutical production, materials science, and environmental analysis, and their applications are becoming increasingly important amidst the growing movement toward environmentally sustainable practices and green chemistry. They are also more accessible in the analytical chemistry classroom compared with typical benchtop instruments due to the flexibility of their size and cost. This makes them easier to obtain, maintain, and transport for use and demonstration purposes. Additionally, interwoven in these topics are core concepts that are fundamental to analytical chemistry; thus, covering them will inherently reinforce students' understanding of fundamental knowledge. Therefore, we believe increased coverage of CE and LOCs can better prepare undergraduates for modern analytical chemistry work in various industries and fields of research.

Ion-Imprinted Polymer-Based Sensor for the Detection of Mercury Ions.

In this work, the development of a novel method for the detection of mercury (II) ions in wastewater using a mercury ion-imprinted polymer (IIP) combined with a quartz crystal microbalance (QCM) is described. The IIP was successfully synthesized via the polymerization of a of a novel fluorescein- and 2-aminophenol-functionalized methacrylic acid monomer, which was noted to have high binding affinity to mercury (II) ions. This polymer was subsequently coated on a QCM chip to create an IIP-QCM sensor. This sensor was established to have high selectivity and good sensitivity to mercury (II) ions, and had a limit of detection (LOD) of 14.17 ppb, a limit of quantification (LOQ) of 42.94 ppb, a signal-to-noise ratio (S/N) of 4.29, good repeatability, and a working range of 42.94 ppb to 2 ppm. The sensor was also able to analyze tap water and wastewater samples. The IIP-QCM is, therefore, promising as a highly selective, cost-effective, and rapid mercury ion sensor for applications involving the detection of mercury in wastewater.

Targeted Plasma Metabolomics Reveals Association of Acute Myocardial Infarction Risk with the Dynamic Balance between Trimethylamine-N-oxide, Betaine, and Choline.

The relationship between trimethylamine-N-oxide (TMAO), betaine, and choline with acute myocardial infarction (AMI) end point remains unclear. We analyzed plasma TMAO, betaine, and choline concentrations in AMI cases and non-AMI community-dwelling controls by LC-MS/MS to understand how the balance between these metabolites helps to reduce AMI risk. Results showed that the odds ratio (OR) for the highest versus lowest quartiles of betaine was 0.30 (95% CI, 0.10-0.82) after adjustment for AMI risk factors, and the unadjusted OR for quartile 3 versus quartile 1 of TMAO was 2.47 (95% CI, 1.02-6.17) (p < 0.05). The study populations with "high betaine + low TMAO" had a significant protective effect concerning AMI with a multivariable-adjusted OR of 0.20 (95% CI, 0.07-0.55) (p < 0.01). Multivariate linear regression showed that the chronological age was correlated with TMAO concentrations among AMI patients (95% CI, 0.05-3.24, p < 0.01) but not among the controls. This implies a further potential interplay between age and metabolite combination─AMI risk association.

Interpretable machine learning-accelerated seed treatment using nanomaterials for environmental stress alleviation.

Crops are constantly challenged by different environmental conditions. Seed treatment using nanomaterials is a cost-effective and environmentally friendly solution for environmental stress mitigation in crop plants. Here, 56 seed nanopriming treatments are used to alleviate environmental stresses in maize. Seven selected nanopriming treatments significantly increase the stress resistance index (SRI) by 13.9% and 12.6% under salinity stress and combined heat-drought stress, respectively. Metabolomics data reveal that ZnO nanopriming treatment, with the highest SRI value, mainly regulates the pathways of amino acid metabolism, secondary metabolite synthesis, carbohydrate metabolism, and translation. Understanding the mechanism of seed nanopriming is still difficult due to the variety of nanomaterials and the complexity of interactions between nanomaterials and plants. Using the nanopriming data, we present an interpretable structure-activity relationship (ISAR) approach based on interpretable machine learning for predicting and understanding its stress mitigation effects. The post hoc and model-based interpretation approaches of machine learning are integrated to provide complementary advantages and may yield more illuminating or trustworthy results for researchers or policymakers. The concentration, size, and zeta potential of nanoparticles are identified as dominant factors for correlating root dry weight under salinity stress, and their effects and interactions are explained. Additionally, a web-based interactive tool is developed for offering prediction-level interpretation and gathering more details about a specific nanopriming treatment. This work offers a promising framework for accelerating the agricultural applications of nanomaterials and may contribute to nanosafety assessment.

Averaging Strategy for Interpretable Machine Learning on Small Datasets to Understand Element Uptake after Seed Nanotreatment.

Understanding plant uptake and translocation of nanomaterials is crucial for ensuring the successful and sustainable applications of seed nanotreatment. Here, we collect a dataset with 280 instances from experiments for predicting the relative metal/metalloid concentration (RMC) in maize seedlings after seed priming by various metal and metalloid oxide nanoparticles. To obtain unbiased predictions and explanations on small datasets, we present an averaging strategy and add a dimension for interpretable machine learning. The findings in post-hoc interpretations of sophisticated LightGBM models demonstrate that solubility is highly correlated with model performance. Surface area, concentration, zeta potential, and hydrodynamic diameter of nanoparticles and seedling part and relative weight of plants are dominant factors affecting RMC, and their effects and interactions are explained. Furthermore, self-interpretable models using the RuleFit algorithm are established to successfully predict RMC only based on six important features identified by post-hoc explanations. We then develop a visualization tool called RuleGrid to depict feature effects and interactions in numerous generated rules. Consistent parameter-RMC relationships are obtained by different methods. This study offers a promising interpretable data-driven approach to expand the knowledge of nanoparticle fate in plants and may profoundly contribute to the safety-by-design of nanomaterials in agricultural and environmental applications.

The effects of pollutant mixture released from grafted adipose tissues on fatty acid and lipid metabolism in the skeletal muscles, kidney, heart, and lungs of male mice.

Persistent organic pollutants (POPs) accumulated in the adipose tissue can affect the fatty acid and lipid metabolism in the body. Gas chromatography-mass spectrometry (GC-MS) metabolomics analysis was carried out to study the metabolic changes induced by internal exposure to the POPs in mouse skeletal muscle (soleus, plantaris, and gastrocnemius), kidney, heart, and lungs. Male donor mice were injected with a mixture of 10 POPs at concentrations of 0 × and 5 × lowest-observed-adverse-effect level (LOAEL). Their adipose tissue (AT) containing the POP was then grafted onto the host mice and the metabolic change of the host mice was monitored for 3 or 21 days. The metabolites related to fatty acid and lipid metabolism were studied. For the host mice engrafted with POP-containing fat pad, there was dysregulation of the fatty acids and glycerides observed in all the organs studied 3 days after the graft. However, there was no longer a significant change in the metabolites 21 days after the graft. The difference in significant values and metabolite regulation in each of the skeletal muscles showed that the POP mixture affects different types of skeletal muscle in a heterogeneous manner. Fold change analysis showed that certain metabolites in the kidney of host mice exposed to POPs for 3 days were greatly affected. Using multivariate analysis, apart from the plantaris, most treated groups exposed to POPs for 3 days are well distinguished from the control groups. However, for host mice exposed to POPs for 21 days, apart from the kidney and heart, groups are not well-distinguished from the control group. This study helps bring new insight into the effects of the pollutants mixture released from AT on fatty acid and lipid metabolism at different periods and how the dysregulation of metabolites might result in diseases associated with the organs.

Synergistic interactions between sewage sludge, polypropylene, and high-density polyethylene during co-pyrolysis: An investigation based on iso-conversional model-free methods and master plot analysis.

Sewage sludge (SS) is a hazardous by-product of wastewater treatment processes that requires careful management for minimal environmental impacts and effective resource recovery. Through thermochemical processes such as pyrolysis, clean energy is recovered from SS in the form of bio-oil, biogas, and biochar. To improve the yield and quality of products, the co-pyrolysis of more than two materials is increasingly gaining interest. Here, the thermal behaviour, kinetics, and synergistic interactions during the co-pyrolysis of SS with polypropylene (PP) and high-density polyethylene (HDPE) were comparatively evaluated with thermogravimetric analysis at different mixing ratios and heat rates. Activation energies and reaction mechanisms were determined through iso-conversional model-free methods and master plot analysis. Evolved gases were monitored with thermogravimetric-mass spectrometry. Increased volatile conversion and degradation rates, and reduced activation energies during co-pyrolysis were mediated by synergistic interactions between H-radicals of PP/HDPE and oxygenated intermediates of SS. Contrary to the pyrolysis of SS, PP and HDPE, the co-pyrolysis processes are predominantly diffusion-controlled. Insights into the co-pyrolysis processes of SS/PP and SS/HDPE gained from this work provide the theoretical support for subsequent investigation, facilitate design of waste-to-energy reactor, and aid the adoption of the technology to harness the bioenergy potential of the feedstocks.

Plasma metallomics reveals potential biomarkers and insights into the ambivalent associations of elements with acute myocardial infarction.

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Using a validated and efficient ICP-MS/MS-based workflow, a total of 30 metallomic features were profiled in a study comprising 101 AMI patients and 66 age-matched healthy controls. The metallomic features include 12 essential elements (Ca, Co, Cu, Fe, K, Mg, Mn, Na, P, S, Se, Zn), 8 non-essential/toxic elements (Al, As, Ba, Cd, Cr, Ni, Rb, Sr, U, V), and 10 clinically relevant element-pair product/ratios (Ca/Mg, Ca×P, Cu/Se, Cu/Zn, Fe/Cu, P/Mg, Na/K, Zn/Se). Preliminary linear regression with feature selection confirmed smoking status as a predominant determinant for the non-essential/toxic elements, and revealed potential routes of action. Univariate assessments with adjustments for covariates revealed insights into the ambivalent relationships of Cu, Fe, and P with AMI, while also confirming cardioprotective associations of Se. Also, beyond their roles as risk factors, Cu and Se may be involved in the response mechanism in AMI onset/intervention, as demonstrated via longitudinal data analysis with 2 additional time-points (1-/6-month follow-up). Finally, based on both univariate tests and multivariate classification modelling, potentially more sensitive markers measured as element-pair ratios were identified (e.g., Cu/Se, Fe/Cu). Overall, metallomics-based biomarkers may have utility for AMI prediction.

Electrochemical sensing mechanism of ammonium ions over an Ag/TiO2 composite electrode modified by hematite.

Here, we demonstrate a new electrochemical sensing mechanism of ammonium ions (NH4+) involving a two-electron oxygen reduction reaction (ORR) and a hydrazine reaction. The NH4+ are electrooxidized to hydrazine by H2O2 derived from the ORR over a self-supporting Ag/TiO2 nanotube array composite electrode modified by hematite (Ag/Fe2O3/TNTs). The Ag/Fe2O3/TNT sensor exhibits a high sensitivity of 1876 µA mM-1 cm-2 with a detection limit of 0.18 µM under non-alkaline conditions, a short response time of 3 s, good reproducibility, and fine selectivity among various interferents, and is also successfully used in real water bodies to display high accuracy. Furthermore, this new mechanism has a certain universality in a range of Ag (main catalyst)/transition metal oxide (cocatalyst)/TNT sensing systems. This work offers a new design basis for the urgently needed electrochemical ammonia nitrogen sensors.

Auranofin inhibits virulence pathways in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is widely attributed as the leading cause of hospital-acquired infections. Due to intrinsic antibiotic resistance mechanisms and the ability to form biofilms, P. aeruginosa infections are challenging to treat. P. aeruginosa employs multiple virulence mechanisms to establish infections, many of which are controlled by the global virulence regulator Vfr. An attractive strategy to combat P. aeruginosa infections is thus the use of anti-virulence compounds. Here, we report the discovery that FDA-approved drug auranofin attenuates virulence pathways in P. aeruginosa, including quorum sensing (QS) and Type IV pili (TFP). We show that auranofin acts via multiple targets, one of which being Vfr. Consistent with inhibition of QS and TFP expression, we show that auranofin attenuates biofilm maturation, and when used in combination with colistin, displays strong synergy in eradicating P. aeruginosa biofilms. Auranofin may have immediate applications as an anti-virulence drug against P. aeruginosa infections.

A Review on Electrospinning as Versatile Supports for Diverse Nanofibers and Their Applications in Environmental Sensing.

Rapid industrialization is accompanied by the deterioration of the natural environment. The deepening crisis associated with the ecological environment has garnered widespread attention toward strengthening environmental monitoring and protection. Environmental sensors are one of the key technologies for environmental monitoring, ultimately enabling environmental protection. In recent decades, micro/nanomaterials have been widely studied and applied in environmental sensing owing to their unique dimensional properties. Electrospinning has been developed and adopted as a facile, quick, and effective technology to produce continuous micro- and nanofiber materials. The technology has advanced rapidly and become one of the hotspots in the field of nanomaterials research. Environmental sensors made from electrospun nanofibers possess many advantages, such as having a porous structure and high specific surface area, which effectively improve their performance in environmental sensing. Furthermore, by introducing functional nanomaterials (carbon nanotubes, metal oxides, conjugated polymers, etc.) into electrospun fibers, synergistic effects between different materials can be utilized to improve the catalytic activity and sensitivity of the sensors. In this review, we aimed to outline the progress of research over the past decade on electrospinning nanofibers with different morphologies and functional characteristics in environmental sensors.

Multi-Omics Investigation into Acute Myocardial Infarction: An Integrative Method Revealing Interconnections amongst the Metabolome, Lipidome, Glycome, and Metallome.

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. This work aims to investigate the translational potential of a multi-omics study (comprising metabolomics, lipidomics, glycomics, and metallomics) in revealing biomechanistic insights into AMI. Following the N-glycomics and metallomics studies performed by our group previously, untargeted metabolomic and lipidomic profiles were generated and analysed in this work via the use of a simultaneous metabolite/lipid extraction and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis workflow. The workflow was applied to blood plasma samples from AMI cases (n = 101) and age-matched healthy controls (n = 66). The annotated metabolomic (number of features, n = 27) and lipidomic (n = 48) profiles, along with the glycomic (n = 37) and metallomic (n = 30) profiles of the same set of AMI and healthy samples were integrated and analysed. The integration method used here works by identifying a linear combination of maximally correlated features across the four omics datasets, via utilising both block-partial least squares-discriminant analysis (block-PLS-DA) based on sparse generalised canonical correlation analysis. Based on the multi-omics mapping of biomolecular interconnections, several postulations were derived. These include the potential roles of glycerophospholipids in N-glycan-modulated immunoregulatory effects, as well as the augmentation of the importance of Ca-ATPases in cardiovascular conditions, while also suggesting contributions of phosphatidylethanolamine in their functions. Moreover, it was shown that combining the four omics datasets synergistically enhanced the classifier performance in discriminating between AMI and healthy subjects. Fresh and intriguing insights into AMI, otherwise undetected via single-omics analysis, were revealed in this multi-omics study. Taken together, we provide evidence that a multi-omics strategy may synergistically reinforce and enhance our understanding of diseases.

Single-cell and bulk ICP-MS investigation of accumulation patterns of Pt-based metallodrugs in cisplatin-sensitive and -resistant cell models.

In research enabling preclinical development and attaining a deeper understanding of the behavior of metallodrugs in cancer cells with acquired resistance, intracellular Pt accumulation could be considered an important biomarker and analytical focus. In this work, Pt accumulation patterns in terms of the number of cells and Pt mass in single cells were precisely defined by using inductively coupled plasma-mass spectrometry (ICP-MS) operating in a fast time-resolved analysis mode. This technique is otherwise known as single-cell (SC)-ICP-MS. By applying the nascent and validated SC-ICP-MS technique, comparisons across three Pt drugs (cisplatin, carboplatin, and oxaliplatin) in the A2780 and A2780cis ovarian cancer cell models could be made. Additional roles of transporters on top of passive diffusion and the drugs' bioactivity could be postulated. The SC-ICP-MS-based observations also served as a cross-validation point to augment preexisting research findings on Pt-resistance mechanisms. Conjectures regarding S and Fe metabolism were also derived based on an additional and direct ICP-MS analysis of endogenous elements. Overall, our work not only confirms the utility of SC-ICP-MS in chemotherapeutic research, but also provided insights into further ICP-MS-based analytical capacities to be developed.

Simultaneous Polar Metabolite and N-Glycan Extraction Workflow for Joint-Omics Analysis: A Synergistic Approach for Novel Insights into Diseases.

Bioinformatics and machine learning tools have made it possible to integrate data across different -omics platforms for novel multiomic insights into diseases. To synergistically process -omics data in an integrative manner, analyte extractions for each -omics type need to be done on the same set of clinical samples. Therefore, we introduce a simultaneous dual extraction method for generating both metabolomic (polar metabolites only) and glycomic (protein-derived N-glycans only) profiles from one sample with good extraction efficiency and reproducibility. As proof of the usefulness of the extraction and joint-omics workflow, we applied it on platelet samples obtained from a cohort study comprising 66 coronary heart disease (CHD) patients and 34 matched healthy community-dwelling controls. The metabolomics and N-glycomics data sets were subjected to block partial least-squares-discriminant analysis (block-PLS-DA) based on sparse generalized canonical correlation analysis (CCA) for identifying relevant mechanistic interactions between metabolites and glycans. This joint-omics investigation revealed intermodulative roles that protein-bound carbohydrates or glycoproteins and amino acids have in metabolic pathways and through intermediate protein dysregulations. It also suggested a protective role of the glyco-redox network in CHD, demonstrating proof-of-principle for a joint-omics analysis in providing new insights into disease mechanisms, as enabled by a simultaneous polar metabolite and protein-derived N-glycan extraction workflow.

Cross-identification of N-Glycans by CE-LIF using two capillary coatings and three labeling dyes.

Recombinant protein biopharmaceuticals comprise a significant portion of the current drug development landscape. The glycosylation profile of these proteins is a key quality parameter as it can affect their safety, efficacy, and stability. However, glycan analysis is challenging because of the complexity of their structures. To overcome this challenge in achieving accurate glycan identification, cross-identification of N-Glycans by CE-LIF method using two capillary coatings and three labeling dyes was developed in this work. This work explored whether complementary separation capabilities can be achieved using homemade polyvinyl alcohol (PVA) coating and commercial Guarant™ (Guarant) coating in the analysis of N-glycans. Similar separation profiles were observed using the two capillary coatings, and hence the N-glycan GU databases generated by these coatings were comparable and complementary. The performance of cross-validation by labeling with three fluorescent dyes indicated that low covariance of APTS and Turquoise™ labeling can be obtained, and hence these two labeling mechanisms provided better accuracy for the identification of glycans. Superior reproducibility with RSDs less than 1% for all target glycan standards was achieved by the internal standards (IS) method using maltodextrin ladders as additives in the separation buffer. The developed CE-LIF analysis method was applied to the identification of N-glycans in IgG samples.

N-glycan profiles of acute myocardial infarction patients reveal potential biomarkers for diagnosis, severity assessment and treatment monitoring.

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Diagnostic challenges remain in this highly time-sensitive condition. Using capillary electrophoresis-laser-induced fluorescence, we analyzed the blood plasma N-glycan profile in a cohort study comprising 103 patients with AMI and 69 controls. Subsequently, the data generated was subjected to classification modeling to identify potential AMI biomarkers. An area under the Receiving Operating Characteristic curve (AUCROC) of 0.81 was obtained when discriminating AMI vs. non-MI patients. We postulate that the glycan profile involves a switch from a pro- to an anti-inflammatory state in the AMI pathophysiology. This was supported by significantly decreased levels in galactosylation, alongside increased levels in sialylation, afucosylation and GlcNAc bisection levels in the blood plasma of AMI patients. By substantiating the glycomics analysis with immunoglobulin G (IgG) protein measurements, robustness of the glycan-based classifiers was demonstrated. Changes in AMI-related IgG activities were also confirmed to be associated with alterations at the glycosylation level. Additionally, a glycan-biomarker panel derived from glycan features and current clinical biomarkers performed remarkably (AUCROC = 0.90, sensitivity = 0.579 at 5% false positive rate) when discriminating between patients with ST-segment elevation MI (n = 84) and non-ST-segment elevation MI (n = 19). Moreover, by applying the model trained using glycomics information, AMI and controls can still be discriminated at 1 and 6 months after baseline. Thus, glycomics biomarkers could potentially serve as a valuable complementary test to current diagnostic biomarkers. Additional research on their utility and associated biomechanisms via a large-scale study is recommended.

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.

Application of omics beyond the central dogma in coronary heart disease research: A bibliometric study and literature review.

Despite remarkable progress in disease diagnosis and treatment, coronary heart disease (CHD) remains the number one leading cause of death worldwide. Many practical challenges still faced in clinical settings necessitates the pursuit of omics studies to identify alternative/orthogonal biomarkers, as well as to discover novel insights into disease mechanisms. Albeit relatively nascent as compared to the omics frontrunners (genomics, transcriptomics, and proteomics), omics beyond the central dogma (OBCD; e.g., metabolomics, lipidomics, glycomics, and metallomics) have undeniable contributions and prospects in CHD research. In this bibliometric study, we characterised the global trends in publication/citation outputs, collaborations, and research hotspots concerning OBCD-CHD, with a focus on the more prolific fields of metabolomics and lipidomics. As for glycomics and metallomics, there were insufficient publication records on their applications in CHD research for quantitative bibliometrics analysis. Thus, we reviewed their applications in health/disease research in general, discussed and justified their potential in CHD research, and suggested important/promising research avenues. By summarising evidence obtained both quantitatively and qualitatively, this study offers a first and comprehensive picture of OBCD applications in CHD, facilitating the establishment of future research directions.

Optimisation of an Aglycone-Enhanced Celery Extract with Germinated Soy Supplementation Using Response Surface Methodology.

In this study, the extraction conditions of bioactive aglycones from a celery extract supplemented with germinated soy were optimised by a response surface methodology. For subsequent enzymatic hydrolysis to enhance the apigenin content, increased production of its precursor apigetrin was firstly achieved through acidic extraction at optimal conditions, involving water at pH 1, at 75 °C for 2 h. Subsequently, a central composite design was conducted to analyse the pH (3-11) and temperature (25-35 °C) effects on the aglycone levels (apigenin, daidzein and genistein). The optimal extraction conditions were pH 7.02 and 29.99 °C, which resulted in a 40-fold increase in apigenin. The novel and cost-effective application of germinated soy ß-glucosidase for the conversion of aglycones in non-soy foods is demonstrated. The enhanced bioactivities of aglycones may suggest potential applications for similar formulations as functional food ingredients.

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.