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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↗

PubMed2026

Aflatoxins and their biosynthetic precursors in lotus seeds: simultaneous UPLC-MS/MS determination, contamination profiling, and matrix-specific accumulation during Aspergillus flavus infection.

Aflatoxin (AF) contamination poses a severe global threat to food and medicinal material safety, yet existing research focuses on terminal AF metabolites while neglecting residual biosynthetic precursors, leading to potential underestimation of contamination risks. In this study, a UPLC-MS/MS method was established for the simultaneous quantification of six AFs and their five precursors in lotus seeds, with optimization of mass spectrum parameters, chromatographic separation conditions, and sample pretreatment. Method validation confirmed linearity (R2 > 0.99), LODs (0.03-0.36 μg/kg), and recoveries (76.53%-120.0%, RSD < 15%). Analysis of 41 natural lotus seed samples revealed a 63.4% AF contamination rate, dominated by B-group AFs, while O-methylsterigmatocystin (OMST) and versicolorin hemiacetal (VOH) were identified as the primary co-residual precursors with co-occurrence rates ≥ 50%. Notably, AFM1 was predominantly detected in natural samples with AFB1 concentrations exceeding 100 μg/kg. Artificial inoculation experiments further demonstrated that sterilization and sealing conditions modulated AF biosynthesis in lotus seeds, with non-sterilized and non-sealed groups showing delayed fungal metabolism and lower toxin accumulation. A significant linear correlation was observed between AFM1 and AFB1 levels (r = 0.94) in infected samples, demonstrating their accumulation levels are coupled with fungal overall metabolic flux. Given the high co-occurrence rate of OMST/VOH with AFB1 in natural samples, their individual and combined toxicities require in-depth investigation. This work deciphers matrix-specific AF dynamics in lotus seeds, supporting regulatory standard refinement (e.g., precursor inclusion) and targeted control (e.g., time-sensitive drying after harvest). Further studies will focus on exploring the molecular mechanisms of substrate-dependent AF synthesis.

Aflatoxins↗

PubMed2026

Determination of 13 per- and polyfluoroalkyl substances in human plasma samples using LC-MS/MS: application to capillary microsamples.

Per- and polyfluoroalkyl substances (PFAS) are chemicals widely applied in industrial processes and highly persistent in the environment, whose extensive use has been linked to adverse health effects. Venous plasma is the conventional matrix for PFAS assessment in blood, and LC-MS/MS is the most used quantification technique. Despite the relevance of this topic, biomonitoring data on human exposure to PFAS in Brazil remain limited. This study validated an LC-MS/MS method for determination of 13 PFAS in human plasma. Blood samples were collected from volunteers by phlebotomy, followed by protein precipitation with acetonitrile containing 1% formic acid (v/v) and solid-phase extraction. Chromatographic separation was achieved on an Acquity UPLC HSS T3 column. The assay was linear over a calibration range of 0.2-20 ng/mL. Intra- and inter-assay precision (CV%) were within the ranges of 2.06-12.0% and 0.25-10.7%, respectively. As for accuracy, results were 89.0-112.9%. Matrix effect ranged from -1.31 to 0.05%. Stability after four freeze/thaw cycles and under autosampler conditions were also confirmed for all analytes. The method was applied to 40 paired venous and capillary plasma samples. Both measures exhibited high correlation (r = 0.926). PFOS was the only compound detected at concentrations ≥0.2 ng/mL (LLOQ) in all samples, with capillary plasma concentrations of 0.85-13.50 ng/mL. In summary, the method showed good validation performance and demonstrated the suitability of capillary plasma samples as an alternative matrix for PFAS quantification.

Humans↗

PubMed2026

Unravelling bioanalytical innovations, degradation processes, and impurity landscapes of VEGFR inhibitors.

From pre-formulation studies to clinical trials, VEGFR-targeted small-molecule tyrosine kinase inhibitors (TKIs) require rigorous analytical standards. Bioanalysis, stability-indicating studies, and impurity profiling are used to examine chromatographic advances for VEGFR-targeted TKIs like sunitinib, pazopanib, axitinib, sorafenib, cabozantinib, vandetanib, apatinib, lenvatinib, nintedanib, and regorafenib. An LC-MS/MS and UPLC-MS/MS routinely show sub ng/mL performance, as shown by LLOQs (0.2 ng/mL) for sunitinib and axitinib, 1 ng/mL for pazopanib, 5-7 ng/mL for sorafenib, 0.5-1.5 ng/mL for regorafenib metabolic products, and 0.1-0.5 ng/mL for lenvatinib. These approaches are used for pharmacokinetics and therapeutic drug monitoring due to their good correlation coefficient of 0.1-10,000 ng/mL, accuracy of 95%-108%, and precision of 15% RSD. UPLC-QTOF-MS/MS distinguishes degradants and metabolites during forced degradation studies, enabling structural elucidation following ICH M7 risk evaluation protocol. HPTLC/MLC offers fast, sensitive screenings, while RP-HPLC/DAD or HPLC-UV offer reliable, cost-effective routine quality-control solutions with LOD/LOQ in the μg/mL range and linearity of 10-240 μg/mL. This review lists the structures and CAS numbers of ten VEGFR-2 TKI degradants and metabolites, as well as pharmacopeial impurities in SMILES forms. It will be useful for future method development and regulatory applications. To ensure VEGFR-targeted TKI quality, safety, and therapeutic efficacy, LC-MS/MS for trace quantification and HRMS for structure elucidation provide a robust, future-oriented framework. To improve VEGFR-targeted TKI quality, safety, and regulatory compliance, analytical development should focus on HRMS-based impurity characterization, AI-assisted degradation prediction, green chromatography, and harmonized bioanalytical validation.

Humans↗

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

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

First insights into the role of evolutionary history in shaping venom composition of Vipera ammodytes.

Understanding intraspecific venom variation requires distinguishing the contributions of neutral population history from natural selection. This study aims to determine whether venom variation in Vipera ammodytes species complex is structured across eight phylogenetic groups. Despite a complex evolutionary history, venom composition did not differ among phylogenetic groups within the analytical framework used, suggesting that shared ancestry alone does not explain venom variation. Whether local adaptation to environmental conditions explains the observed variation remains an open question for future studies.

Animals↗

PubMed2026

Influence of nicotine on protein expression around hydrophilic osseointegrated implants: A proteomic study in male rats.

OBJECTIVE: To ensure the success of dental implant treatment, various factors must be considered, including osseointegration and systemic conditions. There is evidence in the literature that smokers may exhibit alterations in tissue healing, which can compromise the success of implant rehabilitation. Therefore, this study aimed to investigate the influence of nicotine on the protein profile of bone tissue around hydrophilic implants during the osseointegration process in rats. DESIGN: Bone tissue samples from the control and nicotine groups (n = 3 per group) were subjected to protein extraction, mass spectrometry, and bioinformatic analyses. Protein identification was performed using Proteome Discoverer 2.1 software and the SEQUEST algorithm, and the protein data were compared with those of a protein database of Rattus norvegicus obtained from UniProt. RESULTS: A total of 740 proteins were detected in both the control group and the nicotine-exposed group. Among them, the proteins biglycan, periostin and histone H4 were highlighted because of their higher abundance in the healthy implant group, while they were reduced in the nicotine-exposed group. CONCLUSIONS: Nicotine has the potential to alter the protein profile of bone tissue around hydrophilic implants during osseointegration, which may impair tissue remodeling and healing.

Animals↗

PubMed2026

Occupationally relevant vibrations and the brain: frequency-dependent proteomics signatures in a rat model.

INTRODUCTION: Occupational exposure to whole-body vibration (WBV), particularly in agricultural environments, has been associated with adverse cognitive and physiological effects. This study examined the neurophysiological impact of WBV in a rat model at 4 Hz and 30 Hz, frequencies representative of off-road and on-road vehicle operation. METHODOLOGY: Forty-four Sprague-Dawley rats were assigned to control (0 Hz), low-frequency (4 Hz), or high-frequency (30 Hz) vibration conditions. After three days of exposure, brain tissues were collected and analyzed using mass spectrometry-based proteomics to identify differentially expressed proteins. RESULTS: Proteomic profiling revealed distinct, frequency-dependent alterations in brain protein expression. Compared with controls, 32 cognition-related proteins were differentially regulated at 4 Hz and 29 at 30 Hz, with 13 differing between the two vibration conditions. Principal component analysis showed clear separation among groups, indicating unique proteomic signatures for each exposure frequency. Functional enrichment and protein-protein interaction analyses demonstrated involvement of synaptic plasticity, cytoskeletal organization, calcium regulation, and neurotransmitter release. Exposure to 4 Hz was associated with the upregulation of proteins involved in calcium homeostasis and synaptic integrity, suggesting potential disruption of cognitive processes. In contrast, 30 Hz increased the expression of proteins related to axonal guidance and neuroprotection, indicating a less clearly adverse response that may reflect adaptive or potentially beneficial effects. DISCUSSION: These findings provide new insight into biological mechanisms underlying WBV-induced cognitive changes and underscore the importance of vibration frequency in shaping neurophysiological outcomes. They also establish a foundation for future studies integrating proteomics with behavioural assessments in animals and humans.

Animals↗

PubMed2026

Proteomic characterization of the acquired enamel pellicle under acidic challenges at early and mature formation stages.

OBJECTIVES: This study aimed to characterize acquired enamel pellicle (AEP) proteomic changes after exposure to citric acid (CA) and hydrochloric acid (HCl) under different pellicle formation times (3 and 120 min) in the same volunteers. DESIGN: Nine healthy volunteers participated in this randomized crossover in vivo study. The AEP was allowed to form for 3 or 120 min and subsequently exposed for 10 s to deionized water (control), 1% CA (pH 2.5), or 0.01 M HCl (pH 2.0). Pellicle samples were collected, followed by protein extraction, tryptic digestion, and analysis by nanoliquid chromatography (nanoLC) coupled to mass spectrometry (MS) with MSE (data-independent acquisition; nanoLC-MSᴱ). Label-free quantitative proteomics were performed for relative quantification using t-test (p < 0.05). RESULTS: At 120 min, CA exposure markedly reduced several typical AEP proteins, especially acidic proline-rich proteins (PRPs). Conversely, basic PRPs were upregulated, suggesting acid-resistance protein signature. At 3 min, basal-layer proteins (PRPs, cystatins, histatins and mucins) were more abundant. Hemoglobins increased 6-8-fold (up to 150-fold in 3 min control), suggesting association with early pellicle formation and an acid-resistant protein signature. CA exposures for 120 min also upregulated typical AEP proteins (PRPs, mucins, cystatins, immunoglobulins), while HCl exposure depleted albumins and lactotransferrin. CONCLUSION: Intrinsic and extrinsic acids induce distinct proteomic signatures in the AEP. Hemoglobin and PRPs appear consistently enriched in the early pellicle layer, reflecting an initial acid-resistant protein signature. These findings provide new insights into the molecular remodeling of the AEP following intrinsic and extrinsic acid exposure, highlighting proteins potentially involved in early-stage pellicle formation.

Humans↗

PubMed2026

Comparative profiling of microbial community structure, enzyme potential, metabolic features, and volatile composition in craft and Jiafan Huangjiu processes.

Craft Huangjiu and Jiafan Huangjiu represent two distinct industrial Huangjiu product outcomes with contrasting volatile profiles. This study compared craft Huangjiu (L70) and Jiafan Huangjiu (L79) to characterize their physicochemical, microbial, gene-level functional, metabolic, and volatile features. Because L70 involved mid-fermentation addition of finished Huangjiu, this comparison was not intended to isolate the sole effect of fermentation interruption versus continued fermentation. L79 showed more extensive carbon and nitrogen utilization, with lower residual substrates and higher ethanol and acetic acid contents than L70, whereas L70 retained a less complete fermentation state. At the volatile level, GC-MS and volatile metabolomics consistently showed an ester-enriched profile in L79 and a more alcohol-dominant profile in L70. FlavorDB-based putative annotation and threshold-based OAV analysis further indicated distinct database-assigned descriptor distributions and potential odor-active compounds, with more OAV > 1 ester-related compounds in L79. Metagenomic analysis showed that L70 was dominated by Lactobacillus acetotolerans, whereas L79 contained higher relative abundances of Saccharomyces cerevisiae, Aspergillus oryzae, Aspergillus flavus, and Fructilactobacillus fructivorans. Metagenomic functional annotation showed higher representation of hydrolysis-related CAZy genes and ester-related enzyme annotations in L79. KEGG-based pathway mapping further indicated greater gene-level potential for ethanol-, acetate-, and acetyl-CoA-related metabolism in L79. Accordingly, the L70 profile should be interpreted as the integrated final-product outcome of process intervention, exogenous input, and subsequent fermentation. The findings provide a comparative basis for future flavor regulation and process optimization in Huangjiu and other fermented alcoholic beverages.

Volatile Organic Compounds↗

PubMed2026

Transpulmonary proteomic gradient analysis in women with pulmonary arterial hypertension associated with systemic sclerosis.

This study investigated proteomic alterations in the pulmonary circulation of patients with pulmonary arterial hypertension associated with systemic sclerosis (PAH-SSc) by analyzing the transpulmonary protein gradient and comparing the proteomic profiles with systemic sclerosis (SSc) without PAH. Twenty women were included (10 PAH-SSc, 64.6 ± 10.8 years; 10 SSc, 62.8 ± 11.5 years). The transpulmonary gradient was defined as the difference in biomarker concentrations between wedge-position and pulmonary artery blood samples. Peptides were analysed using liquid chromatography-mass spectrometry, and differentially abundant proteins were identified with Proteome Discoverer. Protein-protein interaction networks were generated with STRING and visualized in Cytoscape. A total of 270 proteins were detected, with no significant transpulmonary gradient alterations. However, patients with PAH-SSc showed distinct proteomic profiles compared to SSc. Multivariate analysis identified 48 differentially abundant proteins in pulmonary artery plasma, with 15 overrepresented and 33 downregulated in PAH-SSc. Among these, the downregulation of transforming growth factor-beta-induced protein ig-h3 (TGFβI/ig-h3) points to a potential involvement of the TGF-β-related extracellular matrix remodelling pathway in PAH-SSc. However, further validation in larger and independent cohorts is required before its relevance as a biomarker or therapeutic target can be established. In conclusion, while no transpulmonary proteomic gradient was observed, the proteomic profiles of PAH-SSc and SSc were different. The profile in PAH-SSc was characterized by differences in immune response, lipid metabolism, and hemostatic proteins. SIGNIFICANCE: This study offers the first proteomic characterization of the transpulmonary gradient in PAH-SSc and SSc. Although no differences in the gradient were found, the pulmonary artery plasma proteome of PAH-SSc patients showed a distinct pattern compared to SSc. Several proteins associated with immune function, haemostasis, and cellular processes were altered, which may indicate specific pathophysiological features of PAH-SSc or suggest how lung dysfunction develops in SSc. Targeting dysregulated proteins like TGFβI/ig-h3 or addressing immune-coagulation imbalances may support future research studies. Overall, these findings refine the molecular profile of PAH-SSc and provide a basis for future large-scale studies aimed at clarifying disease mechanisms and identifying clinically relevant molecular signatures.

Humans↗

PubMed2026

Integrated electronic nose, GC-MS, and metagenomic analyses reveal volatile flavor and microbial community differences in heap-fermented grains of Jiangxiangxing Baijiu across different fermentation degrees.

The fermentation degree of heap-fermented grains in Jiangxiangxing Baijiu production is a critical factor influencing base Baijiu quality. However, conventional assessment methods largely rely on empirical experience and therefore suffer from limited objectivity and accuracy. In this study, integrated volatile profiling and metagenomic approaches were employed to investigate volatile characteristics and microbial functional potential differentiation in fermented grains with different fermentation degrees (under-fermented, normally fermented, and over-fermented). Significant differences in physicochemical properties were observed among fermentation degrees, particularly in acidity and reducing sugar content. Electronic nose analysis revealed distinct sensor response patterns among different fermentation degrees, indicating differences in overall volatile odor fingerprint patterns. A total of 81 volatile compounds were identified by HS-SPME-GC-MS, with aldehydes, ketones, and pyrazines showing pronounced variations among fermentation degrees, and acetaldehyde exhibiting strong discriminatory potential. LEfSe analysis identified 18 microbial taxa as potential biomarkers associated with different fermentation degrees, including Pichia kudriavzevii, Lentibacillus daiqui, and Acetobacter pasteurianus. Correlation analysis revealed significant positive associations between acetaldehyde levels and Acetobacter abundance. Furthermore, KEGG, CAZy, and eggNOG analyses revealed differentiated functional potentials among fermentation degrees, providing insights into the potential metabolic basis associated with flavor differentiation. Overall, these findings highlight that fermentation degree differentiation is closely associated with coordinated changes in physicochemical conditions, microbial communities, and functional potentials, providing ecological insights into flavor differentiation and theoretical support for objective fermentation degree evaluation and quality control of Jiangxiangxing Baijiu production.

Fermentation↗

PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Metabolomics and genomics reveal high diversity and concentrations of cyanopeptides during a Microcystis bloom.

Cyanobacterial blooms are an immense global problem that release complex mixtures of poorly characterized biologically active cyanopeptides into freshwater. In this study, metabolomics and genomics were used to assess the diversity and concentrations of cyanopeptides during a dense Microcystis bloom during the late summer of 2023 in Lake Champlain, a large transboundary lake situated between Canada and the United States. Despite the relatively low genetic diversity of the bloom determined by 16S rRNA metabarcoding, 151 cyanopeptides were detected by non-targeted metabolomics. This represents the most recorded cyanopeptides from a single lake plankton bloom event to date. Fifty-two cyanopeptides were previously reported and 99 represent putative new structures. Standards from the microcystin, cyanopeptolin, microginin, and anabaenopeptin groups were used to either quantify or approximate respective cyanopeptide concentrations over the sampling period. Cyanopeptolins were the most diverse (n = 68) cyanopeptides and the second most abundant, reaching 12,892 μg/L. Microginins were the second most diverse (n = 24) and reached the highest concentrations (18,262 μg/L). Anabaenopeptins were the third most diverse (n = 17) cyanopeptides, reaching 4,818 μg/L. Only 8 microcystins were detected, reaching 4,935 μg/L, where MC-LR was the dominant congener. Target cyanopeptide biosynthesis genes for microcystins (mcyE), cyanopeptolins (mcnC), anabaenopeptins (apnD), microviridins (mdnC), and aeruginosins (aerA) were also quantified using digital droplet PCR (ddPCR). The gene copy numbers for mcyE, mcnC, and apnD were highly correlated with their corresponding cyanopeptide concentrations. Overall, the studied Microcystis bloom produced a very diverse cyanopeptide mixture with high cyanopeptide concentrations including non-microcystin groups.

Microcystis↗

PubMed2026

Bioepidemiology of cardiac amyloidosis.

BACKGROUND: Cardiac amyloidosis, primarily due to immunoglobulin light chain (AL) or transthyretin (ATTR) amyloid, is an increasingly recognized cause of heart failure. Modern diagnostic advances suggest that ATTR, particularly in older adults, may be more prevalent than historically reported. METHODS: All Olmsted County decedents aged ≥40 years from 1970 to 1976 were identified. Available ventricular myocardium from retained paraffin blocks was screened histologically for amyloid using sulfated Alcian blue staining; positive cases underwent grading and proteomic typing by laser microdissection coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Beyond prevalence estimation, this analysis characterizes amyloid type, deposition grade and distribution, associated comorbidities, and cause-of-death patterns, comparing amyloid-positive decedents with age- and sex-matched controls. RESULTS: Of 2,566 eligible deaths, 1,028 autopsy cases with evaluable myocardium formed the study cohort (mean age 70.5 years; 61.1% male; 97% White). Cardiac amyloid was present in 52 cases giving an overall prevalence of 5.1% (95% CI: 3.8-6.6, which rose from 0% under age 60 to 37.5% (95% CI: 21.1-56.3) in those ≥90 years (p < 0.001). While prevalence estimates were higher in men above age 80 compared to women, there was no evidence of an interaction of age and sex (p = 0.90). The quantity of amyloid was sufficient for typing in 38 cases: ATTR (84.2%), AL (7.9%), serum amyloid A (5.3%), and apolipoprotein A-IV (2.6%). Adjusted estimates assuming untyped mild cases were ATTR-type increased ATTR prevalence to 4.5% (95% CI: 3.3-5.9) overall. Comorbidity profiles were similar between amyloid-positive and negative groups, though syncope and leg weakness were more common in amyloid-positive decedents. CONCLUSIONS: In an unselected autopsy cohort, cardiac amyloid was common, particularly ATTR in older adults. Prevalence increased steeply after age 80. These findings suggest that ATTR amyloidosis is not rare and is likely underdiagnosed and has similar prevalence in women and men, despite the male predominance reported in the literature.

Humans↗

PubMed2026

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets↗