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PubMed2026

Metabolomic differences in the Ophiura sarsii complex from the Yellow Sea Cold Water Mass and Bering Sea Cold Pool.

Metabolomics provides a functional readout of cellular physiology and can reveal metabolite-level differences associated with environmental and evolutionary contexts. Here, we used GC-MS- and LC-MS-based metabolomics to characterize metabolic profiles of the Ophiura sarsii complex from the Yellow Sea Cold Water Mass (YSCWM) and the Bering Sea Cold Pool (BSCP). This metabolomics analysis identified 398 LC-MS/MS and 87 GC-MS/MS differential metabolites (DEMs). Marked metabolic differences were observed between the two taxa, involving antioxidant-related metabolites, central carbon-related intermediates, osmolyte-associated compounds, and membrane lipid components. O. sarsii vadicola from the YSCWM showed higher levels of glutathione, glucose, citric acid, D-ribulose 5-phosphate, and unsaturated lipid-related metabolites, indicating differences in antioxidant-related and energy-associated metabolic profiles. By contrast, O. sarsii from the BSCP was characterized by higher levels of sugar alcohols, particularly myo-inositol, together with differences in membrane lipid-associated metabolites. These results provide metabolomics-based evidence for metabolite-level physiological differences between two members of the O. sarsii complex sampled from the Yellow Sea Cold Water Mass and the Bering Sea Cold Pool, while the relative contributions of lineage divergence and site-specific environmental variation remain to be tested experimentally.

Metabolomics↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

PubMed2025

Effects of aerosol aging on composition and light-absorbance of nitrogen-containing organic compounds: Evidences from ultra-high-resolution mass spectrometry analysis.

Nitrogen-containing organic compounds (NOCs) are key components of particulate matter (PM), but their compositional evolution and light-absorbing properties during atmospheric aging remain poorly understood. In this study, ultra-high-performance liquid chromatography coupled with Orbitrap mass spectrometry was used to semi-quantitatively analyze 59 PM1 samples collected in Shanghai. NOCs accounted for 31 % and 64 % of the detected species in negative (ESI-) and positive (ESI+) ionization modes, respectively. Atmospheric aging significantly reduced the molecular diversity of polar organics, with both the number and mass concentration percentages of CHON- compounds showing significant negative correlations with aging degree. Van Krevelen analysis demonstrated a decrease in the number of carboxylic-rich alicyclic molecules and their CHON- contributions during the aging process (from 37.7 % in fresh samples to 21.2 % in aged samples). CHN+ compounds, a major NOCs group in ESI+ mode, also decreased with aging. Correlation analyses involving the Bep/(Bep+Bap) ratio, relative humidity, and mass absorption efficiency at 365 nm revealed a decline in light absorption capacity with aging, suggesting aqueous-phase oxidation as a dominant aging mechanism. CHON- and CHN+ compounds were identified as the principal light-absorbing constituents in PM1. This work provides new insights into the aging-induced transformations of NOCs in urban PM1, and their changing role in light absorption, highlighting the need for further investigation of the aging mechanisms of NOCs.

Aerosols↗

PubMed2026

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans↗

PubMed2026

Efficacy and Safety of the Dual Glucagon-Like Peptide-1 and Glucagon Receptor Agonist Mazdutide in Predominantly Chinese Adults With Obesity and/or Type 2 Diabetes: A Systematic Review and Meta-Analysis.

AIM: To assess the effects of mazdutide on body weight, HbA1c, metabolic outcomes, and adverse events in adults with overweight/obesity and/or type 2 diabetes (T2D). METHODS: This systematic review and meta-analysis included randomized controlled trials (RCTs) comparing mazdutide with placebo or active comparators in adults with overweight/obesity and/or T2D, identified through PubMed, Scopus, Web of Science, and ClinicalTrials.gov to 20 February 2026. Co-primary outcomes were percent change in body weight and change in HbA1c. Secondary outcomes included other weight-related and metabolic outcomes, as well as safety. Random-effects models were used to generate pooled mean differences (MDs) or risk ratios with 95% confidence intervals, and the certainty of the evidence (COE) was assessed using GRADE. RESULTS: Nine RCTs (N = 2292; most with low risk of bias) were included. In overweight/obesity without diabetes, mazdutide 3, 4, and 6 mg reduced body weight more than placebo (MDs -6.56%, -9.92%, and -11.1%, respectively; very low COE due to substantial heterogeneity and few trials). In T2D, mazdutide 4 and 6 mg reduced body weight and HbA1c versus placebo (moderate COE) and also outperformed dulaglutide for both outcomes. Mazdutide also improved waist circumference, lipids, liver enzymes, and uric acid levels. Gastrointestinal adverse events were more frequent, but serious adverse events and treatment discontinuation rates were comparable with those of the comparators. CONCLUSIONS: Mazdutide was associated with dose-dependent reductions in body weight and HbA1c, with broader metabolic benefits in predominantly Chinese adults with obesity and/or T2D. Longer-term, multi-ethnic studies are needed to confirm durability, generalizability, and cardiovascular safety.

Humans↗

PubMed2026

An overview of the use of proteomics and peptidomics to characterize alternative protein foods.

The global protein transition is accelerating the development of alternative protein foods, mainly derived from plants, insects, algae, fungi, and cellular agriculture. Ensuring the authenticity, safety, and nutritional adequacy of these emerging protein matrices requires molecular-level characterization beyond traditional compositional analyses. Proteomics and peptidomics have emerged as transformative analytical platforms capable of decoding the molecular signatures that define protein origin, structural integrity, digestibility, functionality, and health potential. The review comprehensively examines the application of proteomics, and peptidomics for profiling alternative protein foods. Further, the source authentication strategies based on species-specific protein and peptide biomarkers, detection of adulteration in complex matrices, and allergenicity assessment is discussed. Special attention is also given to nutritional proteomics with protein digestibility, gastrointestinal peptide release, and identification of bioactive sequences. SIGNIFICANCE: The importance of this review is that proteomics and peptidomics are becoming central in the management of the fast-growing environment of alternative protein foods, such as plant-based, insect, algal, fungal, and cultured meat products. It provides an explanation of the application of mass spectrometry-based processes to decode molecular signatures defining the origin of proteins, their structural integrity, digestibility, allergenicity, and bioactive properties, and thus directly contribute to safety, nutritional analysis, and authenticity of the product. Presentation of the article includes the integration of the knowledge of traditional muscle foods with alternative systems of proteins, where validated protein and peptide biomarkers are used in authentication, fraud detection, and allergy risk assessment in a wide variety of matrices. It also indicates the role of nutritional proteomics and peptidomics in informing the formulation strategy to promote digestibility and release of health-promoting peptides. In general, this review will guide scientists, the food industry, and regulatory bodies to use modern proteomic technologies in quality assurance, and decision-making, for the advancementof sustainable protein-based foods.

Proteomics↗

PubMed2026

Exploring the role of successful exercise-induced body weight loss on cardiometabolic health in individuals with metabolic syndrome.

BACKGROUND AND AIM: High-intensity interval training (HIIT) is known to improve cardiorespiratory fitness (i.e., VO2MAX), a key marker of cardiometabolic health in individuals with metabolic syndrome (MetS). Nonetheless, body weight loss is widely recognized as a crucial factor in reducing insulin resistance and improving metabolic risk factors. Thus, we aimed to determine the importance of body weight loss following exercise training on improving MetS. METHODS AND RESULTS: Two hundred and twenty-eight adults (55.3 ± 7.9 yr) with overweight/obesity (32.5 ± 4.6 kg·m-2) and MetS were randomized to: a) standard health care non-exercise group (CONTROL group, N=58) or b) standard health care plus 16 weeks of HIIT (EXER group, N=170). MetS (MetS z-score), insulin resistance (HOMA-IR), cardiorespiratory fitness (VO2PEAK), maximal cycling power (WPEAK), and body weight/composition were assessed. After intervention, EXER group participants were divided according to their weight loss response to training: i) those achieving the weight loss predicted from estimated exercise energy expenditure (-BW group, n=78; -3.3 ± 2.2 kg); ii) those not reaching the expected weight loss (=BW group, n=38; -0.7 ± 0.5 kg); iii) and those who gained weight (+BW group, n=54; 1.1 ± 1.0 kg). VO2PEAK significantly improved regardless of body weight loss response (-BW, 0.3 ± 0.3; =BW, 0.2 ± 0.3; +BW, 0.3 ± 0.2 L·min-1; all p < 0.001) compared to CONTROL group (0.0 ± 0.3 L·min-1). However, significant improvements in MetS z-score (-0.31 ± 0.41) and HOMA-IR (-0.7 ± 1.6) were observed only in the -BW group (both p < 0.001). CONCLUSIONS: Exercise recommendations should consider that greater improvements in MetS are observed when interventions are accompanied by successful body weight loss. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05120778.

Humans↗

PubMed2026

Direct background subtraction LC-MS/MS assay for human plasma progesterone: Full validation and comparative application.

OBJECTIVE: To develop and validate a liquid chromatography-tandem mass spectrometry method based on direct background subtraction for the quantification of endogenous progesterone in human plasma. METHODS: Protein precipitation was used for sample preparation with deuterated progesterone as the internal standard. Chromatographic separation was performed on an ACQUITY C18 column using gradient elution with 0.1% formic acid in water and acetonitrile at a flow rate of 0.3 mL/min. Mass spectrometry was operated in positive electrospray ionization mode with multiple reaction monitoring. Instead of using analyte-stripped matrix or surrogate matrix, authentic plasma was directly used for all validation experiments. Quantitation was achieved by subtracting the background signal, and results were compared with those from the classical method using stripped matrix. RESULTS: Excellent linearity was achieved over 0.1-100 ng/mL (R2 ≥ 0.99). Precision, accuracy, recovery, matrix effect, and stability all met FDA and ICH M10 acceptance criteria. Compared with the classical method, the bias in Cmax and AUC0-t was within ±15%, indicating no significant difference between the two methods. CONCLUSION: The direct background subtraction method avoids laborious preparation of blank matrix, eliminates matrix effect discrepancies, and is simple, efficient, and low-cost. It can serve as a general strategy for endogenous substance determination.

Humans↗

PubMed2026

Furanic compounds in different coffee extraction systems: Analysis of the main influencing factors and correlation with acrylamide.

This study investigates how different coffee types representative of distinct roast profiles and brewing methods jointly affect the occurrence of furanic compounds and acrylamide in brewed coffee. Coffees were prepared using eight extraction methods (AeroPress, Clever, Chemex, French Press, Moka, Pure Brew, Turkish and V60). Five furanic compounds (furfural, furfuryl acetate, 5-methylfurfural, furfuryl alcohol and 5-hydroxymethylfurfural) were quantified in coffee powders and brews by HS-SPME-GC-MS, while acrylamide was determined by UHPLC-MS/MS. Moka and Turkish brews consistently exhibited the highest concentrations of furanic compounds, whereas paper-filtered pour-over methods (V60 and Chemex) showed the lowest levels. Pearson correlation analysis revealed coffee-dependent relationships between furanic compounds, acrylamide and extraction parameters with the strongest associations observed in dark-roasted coffee, reflecting advanced Maillard reaction chemistry. Overall, these results demonstrate that contaminant levels arise from the combined effects of intrinsic coffee chemistry and brewing mechanics and support targeted mitigation strategies: such as roast selection and brewing method optimization.

Acrylamide↗

PubMed2026

Comparative transcriptome analysis provides insights into dorso-ventral color pattern formation of Holothuria edulis.

Animal body color patterns are highly diverse and play critical roles in camouflage, intraspecific communication, and environmental adaptation. Holothuria edulis, an important echinoderm inhabiting tropical waters, exhibits a typical dorsoventral dichromatism. This unique body color difference represents a key phenotypic trait for its habitat adaptation; however, the core differential genes regulating this trait remain to be elucidated. In this study, comparative transcriptome sequencing was performed on the dorsal and ventral body wall tissues of H. edulis, leading to the identification of a number of differentially expressed genes (DEGs), followed by GO functional annotation and KEGG pathway enrichment analysis. GO enrichment analysis indicated that the DEGs were significantly enriched in functional categories such as extracellular region, peptidase inhibitor activity, and tetrapyrrole binding. KEGG pathway analysis further revealed significant enrichment of protein digestion and absorption, the TNF signaling pathway, and cholesterol metabolism. Notably, the pigmentation-related gene FMO2 was highly expressed in the dorsal body wall tissue, whereas cyp1a1, ZIC1, Slc7a11, WNT-1, and ADAMTS20 were highly expressed in the ventral body wall tissue. This study identified DEGs and enriched pathways associated with dorsoventral body color differences in H. edulis, providing new insights into the molecular regulatory mechanisms underlying body color pattern formation. From the perspective of aquaculture applications, body color is one of the important traits affecting the quality and market value of sea cucumber products. Elucidating the molecular mechanisms of body color variation can provide a scientific basis for molecular marker-assisted breeding of superior sea cucumber variety.

Animals↗

PubMed2026

Integrated widely targeted metabolomics and GC-IMS reveal dynamic flavor, nutritional, functional, and metabolic profiles in macadamia kernels during processing.

Different processing stages influence the color, flavor, and antioxidant activities of macadamia kernels. However, the biochemical mechanisms that occur during processing are not well known. This study integrated widely targeted metabolomics (UPLC-MS/MS) with GC-IMS to systematically characterize non-volatile and volatile compounds in macadamia kernels across key three sample groups: fresh kernels (FMN), low-temperature-dried kernels (DMN), and roasted kernels (BMN). A total of 622 non-volatile metabolites and 52 volatile compounds were identified. Low-temperature drying promoted the accumulation of phenolic acids and flavonoids, enhancing antioxidant capacity. Roasting degraded heat-sensitive nutrients but generated flavor compounds via Maillard reaction and lipid oxidation, shifting aroma from green to nutty notes. Nutritional assessment confirmed that roasting significantly reduced antioxidant activities and bile acid binding capacity. Pearson correlation analysis verified the key metabolite-antioxidant relationships. These findings provide critical insights into metabolic dynamics during nut processing and establish a scientific basis for optimizing thermal processing strategies.

Metabolomics↗

PubMed2026

Development and validation of a novel LC-MS/MS method for simultaneous quantification of fidaxomicin and metabolite (OP-1118) from feces for gut pharmacobiome studies.

Fidaxomicin is a first-line antibiotic for treating Clostridioides difficile infection. While it has low systemic absorption and reaches high colonic concentrations, it is hydrolyzed to a less active metabolite, OP-1118. Few studies have completely described critical experimental details of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for quantifying fecal fidaxomicin and OP-1118. This study developed and validated a simple, fast, and sensitive LC-MS/MS method to quantify fidaxomicin and OP-1118 in human and mouse feces. This method simplified fecal sample preparation without the use of solid phase extraction and optimized LC-MS/MS parameters. A broad working range (0.3-1000 ng/ml) in both diluted human and murine fecal matrices was achieved with good intra- and inter-day accuracy (93-107%), precision (1-7%), and recovery (70-105%) as well as little IS-normalized matrix effects. This method was utilized to quantify fidaxomicin and OP-1118 in human and murine fecal samples. This novel method was simple, fast, sensitive, and accurate in analyzing fecal fidaxomicin and OP-1118 and could be deployed to facilitate gut pharmacobiome research.

Feces↗

PubMed2026

Comprehensive identification of carboxylic acids by using bromine isotope-based chemical isotope labelling and structure-guided molecular network.

Carboxylic acids (CAs) are important contributors to the flavor quality of sauce-flavor Chinese Baijiu, yet their comprehensive analysis remains challenging due to poor ionization efficiency, weak chromatographic retention, and limited annotation capability. Herein, we developed a workflow for the high-coverage discovery and annotation of CAs in Baijiu by coupling chemical isotope labeling-liquid chromatography-mass spectrometry with a structure-guided molecular network strategy (SGMNS). A bromine-containing derivatization reagent, 1-(3-aminopropyl)-3-bromoquinolin-1-ium bromide (APBQ), was designed and synthesized to exploit the natural isotope distribution of bromine and characteristic MS/MS fragmentation behavior. Following APBQ derivatization, the target CAs showed superior chromatographic retention and favorable analytical performance. Based on isotopic peak pairing in MS1 and diagnostic fragment validation in MS2, 372 potential CA derivatives were discovered from pooled Baijiu samples and 355 of them were validated by diagnostic fragments in MS2 spectra. To address the scarcity of derivatized spectral libraries, SGMNS was employed for annotation using a background network constructed from APBQ-labeled candidates derived from the Expanded Chinese Baijiu Compound Database. The developed method was further applied to profile Baijiu samples, revealing pronounced differences in CA composition across the seven fermentation rounds. Notably, rounds 3 to 5 exhibited the largest numbers of differential CAs. This study provided an effective analytical strategy for large-scale CA profiling, offering new insight into the chemical basis of flavor formation during multi-round fermentation of sauce-flavor Baijiu.

Isotope Labeling↗

PubMed2026

Validated UPLC-MS/MS quantification and intracellular PK-PD Modeling of periplocin-related cardiac glycosides in H/R-injured H9c2 cells.

Reliable intracellular quantification is essential for characterizing the target-site disposition and exposure-response relationships of bioactive natural products. In this study, an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed and validated for the simultaneous determination of periplocin and four related cardiac glycoside metabolites in H9c2 cell lysates. Acceptable linearity, precision, recovery, and stability were achieved for intracellular quantification. Cells were treated with each compound at 50 μM, and intracellular concentrations and cell viability were monitored over 48 h. In hypoxia/reoxygenation (H/R) -injured cells, the time to maximum intracellular concentration was shortened for all five compounds, indicating altered cellular disposition under injury conditions. Cell viability was improved by all compounds during the observation period. Pharmacokinetic-pharmacodynamic (PK-PD) integration was performed using a sigmoid Emax model, and acceptable model fits were obtained, with Akaike information criterion (AIC) values ranging from 79.22 to 130.46. Low apparent EC50 values were estimated under this single-dose design, whereas the estimated Ke0 values suggested delayed equilibration with the effect compartment. These findings indicate that sustained cytoprotective responses can be produced by periplocin and related metabolic markers in injured cardiomyocytes. This intracellular bioanalytical strategy provides a quantitative approach for linking cellular exposure to pharmacodynamic response and may support further evaluation of periplocin-related cardiac glycosides.

Tandem Mass Spectrometry↗

PubMed2026

Quantifying the aromatic amino acid metabolome: UPLC-MS/MS analysis of aromatic amino acids and their host and co-metabolites in plasma.

Aromatic amino acids (AAAs), tryptophan, phenylalanine, and tyrosine along with their pathway metabolites have been implicated in the pathogenesis of diseases ranging from cardiovascular, neurological, inflammatory, and cancer diseases, among others. As such, the measurement of the primary AAAs, their host pathway metabolites, and microbiome derived co-metabolites in blood can provide a sensitive reflection of systemic health. The aim of the study was to develop a method for the quantification of 17 metabolites, the three AAAs and various of their metabolites in plasma using a high-throughput ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method. The method demonstrated a dynamic range (1 to 16,700 ng/mL), with detection limits (LOD) as low as 0.05 ng/mL. Quantification limits ranged from 3 to 5019 ng/mL (LLOQ) and up to 16,700 ng/mL (ULOQ). Recovery at LQC, MQC, and HQC was satisfactory and consistent across most metabolites, with significant matrix effects observed only for 4-ethylphenol sulfate. Furthermore, intra and inter-day accuracy and precision met all acceptance criteria at all quality control concentrations for most of the metabolites. Measurement of NIST SRM 1950 showcased the method's accuracy for most of the metabolites. Finally, the method was applied on the analysis of plasma samples from 55 individuals (13 males and 42 females) providing information on AAAs and their pathway metabolites relevant concentrations in human plasma.

Amino Acids, Aromatic↗

PubMed2026

Improved comprehensive profiling of fecal bile acids through chemical derivatization combined with HPLC-MS/MS analysis.

Bile acids (BAs) facilitate the digestion and absorption of fats and influence lipid and glucose homeostasis, making them potential therapeutic targets for obesity and related metabolic disorders. The liver and intestinal microbiota modify BAs structurally, generating diverse chemical forms and isomers. Comprehensive profiling of the BA pool is critical for understanding their key biological functions and as a therapeutic approach for related diseases. High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) is usually chosen as the preferred method for BA detection due to the complex chemical structures, the wide range of actual concentrations and the complexity of fecal sample matrices. However, free BAs are difficult to ionize, resulting in low detection signals and a lack of characteristic structural fragments to assist in structural identification. In this method, the labeling reagent (2-aminoethyl) trimethylammonium (AETMA) is employed to label the carboxyl group of BAs. Compared with underivatized BAs, the detection sensitivity of unconjugated BAs was enhanced by 25-180 fold, while that of conjugated BAs increased by 6-160 fold. It also generates unique fragment ions and enhances MS response, facilitating the discovery of potential BAs. Methodological parameters were validated using 38 BAs as representatives. Through methodological validation, it was verified that the precision, recovery, matrix effect and stability parameters of the method met acceptable criteria. We also identified 61 confirmed BAs and 55 additional candidate BAs in human pooled fecal samples. It has been successfully applied to fecal BA analysis in obese populations, providing valuable insights into potential therapeutic strategies for obesity.

Tandem Mass Spectrometry↗

PubMed2026

Development and validation of an LC-MS/MS method for the quantification of the KRASG12C inhibitor divarasib.

Divarasib is a newly developed covalent KRASG12C inhibitor, currently under clinical investigation in a phase 3 trial in patients with non-small cell lung cancer (NSCLC). At the moment, very limited pharmacokinetic data are publicly known. However, obtaining more insight into the pharmacokinetic properties of divarasib is important, since this may provide a better understanding of its efficacy and safety risks. Pre-clinical studies have been performed in mouse models to evaluate the effect of drug transporters and drug-metabolizing enzymes on the plasma exposure and tissue distribution of divarasib. Therefore, a reliable quantification method is required. To our knowledge, no bioanalytical assay of divarasib has been published yet. Therefore, in this study we developed and validated an assay to quantify divarasib in human plasma and in eight different mouse-related matrices, and partially in mouse plasma, using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method was initially evaluated over a concentration range of 1-10,000 nM. However, due to carry-over observed at 10,000 nM, the validated calibration range was established at 1-2000 nM, with matrix-dependent LLOQs of 1-10 nM. Erlotinib was used as an internal standard and acetonitrile was utilized to perform protein precipitation as sample pretreatment. Divarasib demonstrated stability in human plasma and in mouse plasma and tissue homogenates under various experimental conditions. A pilot in vivo study showed the applicability of our validated LC-MS/MS method. Ongoing clinical trials may collect plasma samples, and this developed method enables quantification of divarasib in both mouse and human plasma samples.

Animals↗

PubMed2026

A streamlined workflow for high throughput metaproteomic analysis of the rumen microbiome.

Metaproteomics can provide direct functional insights into complex microbial communities, yet its application in rumen research remains limited due to labor-intensive and low-throughput sample preparation workflows before the MS analysis. This work aimed to develop and characterize a streamlined, high throughput metaproteomic workflow optimized for rumen samples. Key steps, including microbial cell extraction, cell lysis, protein digestion, and LC-MS/MS acquisition, were systematically assessed and optimized to reduce hands-on time while maintaining deep proteome coverage. The optimized workflow integrates a minimized cell extraction protocol using 0.5 g starting material and in-solution tryptic digestion. Application of the final workflow to 72 samples from in vitro fermentation revealed that biological variability between inocula dominated technical variability, which remained moderate (median CV of 21-24% across batches). Overall, the optimized workflow supports robust taxonomic and functional characterization of the rumen microbiome with improved scalability. These advances provide a foundation for applying metaproteomics to larger experimental designs, including nutritional trials and cohort studies, thereby enabling broader functional interrogation of rumen microbial ecosystems. SIGNIFICANCE: This study addresses current limitations in the application of metaproteomics to rumen microbiome research by developing a streamlined and scalable sample preparation workflow. By optimizing key steps and reducing sample input while maintaining reproducibility and proteome coverage, this work enables more efficient processing of larger sample sets. These advances support the broader use of metaproteomics in rumen studies and facilitate functional investigations relevant to animal nutrition and sustainable livestock production.

Animals↗