A Native Nepenthesin Reactor for Improved Proteolytic Digestion of Intrinsically Disordered Proteins in Proteomics Workflows A workflow is presented for the extraction and purification of native nepenthesin (NEP-NAT) from Nepenthes species, followed by the enzyme's immobilization on POROS-AL chromatographic material. The N...

Latest publication from SNP2Prot colleagues C. Wall and A. Sinz reveals that the Nepenthesin protease, isolated from 𝘕𝘦𝘱𝘦𝘯𝘵𝘩𝘦𝘴 sp., carries superior proteolytic activity towards IDPs.

Kudos to the team 🎉

doi.org/10.1002/cbic...

#MassSpec #Protease #IDPs
#Proteomics

@sinzandrea.bsky.social

Is your lab short on electrical outlets. Spectrometrics has a range of add-ons that typically let you pull the plug on at least two outlets per #MassSpec system.

Mascot search engine | Protein identification software for mass spec data Mascot software from Matrix Science - identification, characterisation and quantitation of proteins using mass spectrometry data

matrixscience.com is being overwhelmed by millions of HTTP requests from distributed botnets, essentially a distributed denial of service (DDoS) attack. We are forced to mitigate it by restrict access to certain pages of dynamic content.

www.matrixscience.com/whats_new/mi...

#proteomics #massspec

Shimadzu at London Biological Mass Spectrometry Discussion Group

Today we're pleased to be supporting @bio-mass-spec-ldn.bsky.social at Burlington House.
If you're here too, come and say hi to our LCMS specialists, Ollie Sligsby-Wolfe & Emma Poole!

#analysis #biosciences #massspec #massspectrometry #lcms #lbmsdg
#SciSky #AcademicSky #ChemSky #EduSky #Edchat 🧪

Bar chart comparison of standard acqusition method compared to Thunder-DDA-PASEF.

Thunder-DDA-PASEF is an acquisition strategy for capturing more human leukocyte antigen (HLA) class I peptide ligands on Bruker timsTOF instruments. This month's blog shows how you can process Thunder-DDA-PASEF data with Mascot Distiller.

www.matrixscience.com/blog/process...

#proteomics #massspec

I 100% agree with this take.

Plug: If you are working with #proteomics and/or #massspec data, check out our shortcourse at #ASMS2026 to get a jump start on many of these methods! (Course 04 here: www.asms.org/conferences/...)

MSInet: A Self-Supervised CNN Framework Integrating Global and Local Context for Robust Mass Spectrometry Imaging Segmentation Mass spectrometry imaging (MSI) enables label-free molecular mapping in tissues but presents challenges for spatial segmentation due to high dimensionality, nonlinear spectral variation, and tissue he...

What's your biggest segmentation challenge?

🧠 Complex brain anatomy (many subregions)
🔬 Tumor heterogeneity (cancer vs. necrosis vs. healthy)
📊 Choosing cluster numbers (k=?)
🌀 Fragmented results

pubs.acs.org/doi/10.1021/...

#MassSpec #SpatialOmics #DeepLearning #Metabolomics

(4/4)

Multiomics Analysis across the Life Cycle Identifies Zn2Cys6_61 as a Target for Enhancing Triterpenoid Production in Ganoderma lucidum Ganoderic acids (GAs) are high-value lanostane-type triterpenoids derived from Ganoderma lucidum (G. lucidum) with broad applications in functional foods and nutraceuticals, yet their low natural abundance limits industrial production. In this study, an integrated life-cycle multiomics analysis combining metabolomics, transcriptomics, and proteomics was conducted across six developmental stages in four G. lucidum strains to elucidate regulatory mechanisms governing GA biosynthesis. Weighted gene coexpression network analysis identified candidate cytochrome P450 enzymes and transcription factors associated with GA accumulation. A Zn2Cys6-type transcription factor, Zn2Cys6_61, was identified as a central regulator and functionally validated through overexpression and RNA interference. Genetic manipulation of Zn2Cys6_61 expression significantly altered GA levels, with overexpression markedly enhancing GA accumulation. Further analysis demonstrated that Zn2Cys6_61 directly binds to and activates the promoter of squalene synthase, a key enzyme in triterpenoid backbone biosynthesis. Together, these findings identify Zn2Cys6_61 as an effective engineering target and provide a transcription factor-based strategy for improving GA production in medicinal mushrooms.

Multiomics Analysis across the Life Cycle Identifies Zn2Cys6_61 as a Target for Enhancing Triterpenoid Production in Ganoderma lucidum #JAFC #MassSpec pubs.acs.org/doi/10.1021/...

Metabolomics-Guided Integration of a “Push–Pull-Restrain” Strategy for Enhanced LNnT Production in Saccharomyces cerevisiae Lacto-N-neotetraose (LNnT) is a prominent neutral human milk oligosaccharide (HMO) with limited availability. Here, Saccharomyces cerevisiae (GRAS strain, Generally Recognized as Safe) was metabolically engineered to enhance LNnT production. Metabolomics analysis revealed that competition from chitin synthesis and insufficient metabolic driving force for heterologous glycosyltransferases in yeast constituted major metabolic bottlenecks. To overcome these limitations, a “push–pull-restraint” strategy was applied, integrating glycosyltransferase screening, protein tag fusion evaluation, targeted chitin disruption of chitin biosynthetic genes, and balanced modulation of UDP-Gal/UDP-GlcNAc supply. These interventions increased extracellular LNnT titer in shake-flask cultures from 14.65 mg/L to 1.66 g/L, with total LNnT reaching 2.01 g/L. Further scale-up in a 5 L bioreactor under fed-batch conditions resulted in a total LNnT titer of 4.70 g/L. These results demonstrate the potential for the production of LNnT by S. cerevisiae and open up an innovative framework for the effective synthesis of LNnT.

Metabolomics-Guided Integration of a “Push–Pull-Restrain” Strategy for Enhanced LNnT Production in Saccharomyces cerevisiae #JAFC #MassSpec pubs.acs.org/doi/10.1021/...

Systematic Evaluation of the Impact of Storage Time on Label-Free Proteomics of Colorectal Adenocarcinoma Formalin-Fixed Paraffin-Embedded Tissues Mass spectrometry (MS)-based proteomics has empowered comprehensive protein profiling of biological specimens. However, formalin-fixed paraffin-embedded (FFPE) tissues─critical resources for clinical biomarker discovery-remain underexplored in the setting of long-term storage (>15 years). Herein, we systematically evaluated the impact of storage time on proteomic analyses of 80 colorectal adenocarcinoma (CRC) FFPE samples, which were stratified by two key variables: storage time (>15 years vs <1 year) and tissue type (tumor vs adjacent normal tissue). We adopted a standardized protein extraction strategy, and subsequent proteomic profiling was performed via data-dependent acquisition and data-independent acquisition MS workflows. Our results demonstrated that FFPE tissue storage time impacts protein extraction efficiency, peptide yields, PTM identification, and protein quantification. The impacts were more pronounced on the peptide level. However, the biological enrichments (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis) from the global proteome profile and from differentially expressed proteins in CRC tissues were independent of archival time. Five clinically relevant biomarkers of CRC were further validated via immunohistochemistry. Collectively, our findings confirm that FFPE tissues retain stability for proteomic analyses even following >15 years of storage, thereby providing critical insights for leveraging archival FFPE biobanks to advance clinical proteomics and archival pathology research.

Systematic Evaluation of the Impact of Storage Time on Label-Free Proteomics of Colorectal Adenocarcinoma Formalin-Fixed Paraffin-Embedded Tissues #JProteomeRes #MassSpec pubs.acs.org/doi/10.1021/...

Graph Machine Learning Can Estimate Drug Concentrations in Whole Blood from Forensic Screening Results LC-HRMS is widely used in forensic toxicology for broad-scope screening. When a newly emerging or rarely encountered compound is tentatively identified, toxicologists must decide whether it may be relevant to a case and, if so, quantify it. However, acquiring reference material for quantification is costly and time-consuming. A rapid semiquantitative estimation method would help prioritize only compounds above the toxic threshold. This study presents a machine-learning (ML) framework that estimates drug concentrations in whole blood using molecular structure information and LC-HRMS signals. Using a data set of 191 drugs spiked into whole blood at multiple concentration levels, we trained and evaluated several ML models. Standard models, including Random Forests, achieved moderate performance. In contrast, a recently reported Graph Neural Network (GNN) leveraging atomic features and global molecular properties consistently produced the highest accuracy. Under cross-validation, the GNN predicted signal-to-concentration ratios for 79% of all molecules, corresponding to concentration estimates between 50% and 200% of the true value. Toxicological thresholds often span multiple orders of magnitude, making this precision acceptable. The GNN model was additionally evaluated on an external benchmark data set of ionization efficiencies (logIE), where it outperformed the current state of the art. Overall, the results demonstrate the feasibility of using graph-based ML to estimate drug concentrations in whole blood without reference material. This is a practical ML tool that can support decision-making in toxicological evaluation, particularly for newly emerging or rarely encountered drugs. The GNN model is open source, and the data set used for training and testing the models are publicly available.

Graph Machine Learning Can Estimate Drug Concentrations in Whole Blood from Forensic Screening Results #AC #MassSpec pubs.acs.org/doi/10.1021/...

Development of Low-Flow High-Resolution Desorption Electrospray Ionization Mass Spectrometry Imaging Desorption electrospray ionization mass spectrometry (DESI-MS) imaging is a well-established technique for molecular analysis of biological samples, although its spatial resolution has been limited when compared to other MS imaging techniques. Here, we...

Catch up on trending research! Read more: Development of Low-Flow High-Resolution Desorption Electrospray Ionization Mass Spectrometry Imaging https://bit.ly/3N2pVsm

#ASMS #JASMS #TeamMassSpec #MassSpec

Development of Low-Flow High-Resolution Desorption Electrospray Ionization Mass Spectrometry Imaging Desorption electrospray ionization mass spectrometry (DESI-MS) imaging is a well-established technique for molecular analysis of biological samples, although its spatial resolution has been limited when compared to other MS imaging techniques. Here, we...

Catch up on trending research! Read more: Development of Low-Flow High-Resolution Desorption Electrospray Ionization Mass Spectrometry Imaging https://bit.ly/3N2pVsm

#ASMS #JASMS #TeamMassSpec #MassSpec

Gradually changing peaks in a chromatogram

An underestimated issue in LC-MS: gradual changes in peak shape.
A bit more tailing here, more fronting there... and suddenly your quantitation is drifting.
When you see peak shape change, what's the first thing you check?

#MassSpec #troubleshooting #SciSky #AcademicSky #ChemSky #EduSky #Edchat

Cross ionization mode chemical similarity prediction between tandem mass spectra in metabolomics - Nature Communications Mass spectrometry is a cornerstone of untargeted metabolomics, but comparisons across ionization modes have remained a substantial challenge due to the distinct fragmentation patterns produced by each...

MS2DeepScore 2.0 is finally published 🚀 --> www.nature.com/articles/s41...

This was a great journey with Niek de Jonge and a great team of collaborators! See more on LinkedIn: www.linkedin.com/posts/f-hube...

#massspec #cheminformatics #ML #opensource #openscience #python

This article is now available in Proteomes: Scout-Triggered Multiple Reaction Monitoring Enables Robust Quantification of Host Cell Proteins Across Bioprocess Matrices 🧬🖥️🧪🧫🥼

www.mdpi.com/2227-7382/14...

#proteomes #proteomics #proteoform #HCP #MassSpec

Metabolic disparities of potentially toxic components derived from Psoraleae Fructus and Euodiae Fructus within the Sishen wan influenced by varying compatibilities and physiological conditions in an ... Sishen wan (SSW) is utilized in the treatment of irritable bowel syndrome (IBS). This study aimed to compare gut microbiota-mediated metabolic profile…

Metabolic disparities of potentially toxic components derived from Psoraleae Fructus and Euodiae Fructus within the Sishen wan influenced by varying compatibilities and physiological conditions in an in vitro gut microbiota model #JPBA #MassSpec www.sciencedirect.com/science/arti...

Glycoinformatic profiling of label-free intact heparan sulfate oligosaccharides Heparan sulfates (HS) are a group of heterogenous linear, sulfated polysaccharides that play a role in in health and many diseases including cancer, cardiovascular, and kidney diseases. The structural...

Glycoinformatic profiling of label-free intact heparan sulfate oligosaccharides #MCP #MassSpec www.mcponline.org/article/S153...

Supramolecular Solvent Extraction for Doping Control Analysis of Prohibited Substances in Horse Urine This paper describes the first application of supramolecular solvent extraction for doping control analysis of prohibited substances in horse urine.

Supramolecular Solvent Extraction for Doping Control Analysis of Prohibited Substances in Horse Urine #DTA #MassSpec analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/...

Spatial localization and pharmacodynamic assessment of intracrine androgen metabolism in CRPC xenograft tumor tissues upon active vitamin D treatment - Analytical and Bioanalytical Chemistry Castrate-resistant prostate cancer (CRPC) progression is driven by intracrine androgen synthesis despite low circulating androgens. This study investigates the effects of active vitamin D (1,25-(OH)₂-...

Spatial localization and pharmacodynamic assessment of intracrine androgen metabolism in CRPC xenograft tumor tissues upon active vitamin D treatment #ABC #MassSpec link.springer.com/article/10.1...

A new multi-residue method for PFAS analysis in wastewater for environmental and public health risk assessment - Analytical and Bioanalytical Chemistry This work focuses on the detection and quantification of per-/polyfluorinated alkyl substances (PFAS) in influent wastewater, using wastewater-based epidemiology via a new multi-residue ultra performa...

A new multi-residue method for PFAS analysis in wastewater for environmental and public health risk assessment #ABC #MassSpec link.springer.com/article/10.1...

Proteomics and Lipidomics Analysis Reveal That Membrane Remodeling and Extracellular Matrix Alterations Are Crucial for Cisplatin Resistance in Triple-Negative Breast Cancer Cisplatin is a widely used chemotherapeutic agent for triple-negative breast cancer (TNBC), but resistance remains a major challenge. Understanding the molecular alterations driving this resistance is essential for identifying therapeutic targets. In this study, we employed an integrated proteomics and lipidomics approach to elucidate key pathways associated with cisplatin resistance. Employing high-resolution mass spectrometry, we conducted a comparative analysis between cisplatin-resistant (cisR) and cisplatin-sensitive (cisS) TNBC cell lines to discover resistance-associated alterations in protein and lipid expression. Proteomic analysis revealed overexpression of extracellular matrix (ECM) remodeling proteins, COL6A1, COL6A2, COL6A3, and VTN, that support epithelial-mesenchymal transition (EMT) and chemoresistance. Membrane-associated proteins such as TIMP2, MMP14, and APP were also elevated, indicating enhanced invasive and pro-survival signaling. Lipidomic alterations, including upregulation of FABP3, FABP4, LPL, and downregulation of PLA2G4A, indicated increased lipid uptake, metabolic rewiring, and membrane restructuring. Notably, elevated long-chain phosphatidylcholines and decreased sphingomyelins suggested increased membrane rigidity and reduced cisplatin permeability. Additionally, dysregulation of CDK activity through CCND2, CCND3, and CCNB2 overexpression indicated accelerated cell cycle progression and evasion of DNA damage checkpoints. Together, this integrative analysis highlights ECM remodeling, cytoskeletal dynamics, and lipid metabolism as major contributors to cisplatin resistance and identifies potential therapeutic markers for TNBC.

Proteomics and Lipidomics Analysis Reveal That Membrane Remodeling and Extracellular Matrix Alterations Are Crucial for Cisplatin Resistance in Triple-Negative Breast Cancer #JProteomeRes #MassSpec pubs.acs.org/doi/10.1021/...

Combined Quantitative and Qualitative Statistical Analyses Improve Benzodiazepine Target Discovery in Label-free Affinity-Based Protein Profiling Data Affinity-based protein profiling (AfBPP) allows us to identify target proteins that bind drugs or other small molecules of interest in complex samples. As an enrichment technique, label-free AfBPP often generates data with high missingness, particularly in negative control samples. We developed an R package, chemoprotR, which enables both quantitative and qualitative statistical analyses of chemoproteomic data, and applied it to the identification of specific benzodiazepine drug targets in the brain. Benzodiazepines comprise a class of drugs that affect GABAA receptors through positive allosteric modulation, but benzodiazepine interactions with other proteins are not fully understood. To this end, we synthesized benzodiazepine affinity-based probes (AfBPs) and applied them to rat brain synaptosomes. Our benzodiazepine AfBPs identified GABAA receptor subunits and other proteins with ion channel functions. Across the three probes, there was minimal overlap in protein targets identified by competitive labeling with flurazepam, and FR-DA, the probe based on flurazepam, yielded more significant protein targets than the probes based on flunitrazepam. These results demonstrate the ability of benzodiazepine AfBPs to identify protein targets when used with an authentic benzodiazepine to compete for binding sites and highlight the utility of combined statistical analyses for the interpretation of presence–absence data in AfBPP data sets.

Combined Quantitative and Qualitative Statistical Analyses Improve Benzodiazepine Target Discovery in Label-free Affinity-Based Protein Profiling Data #JProteomeRes #MassSpec pubs.acs.org/doi/10.1021/...

This article is now available in Proteomes: Proteome-Wide Analysis of Functional Phosphosites in the FGFR Family of Proteins: Insights from Large-Scale Phosphoproteomic Analysis 🧬🖥️🧪🧫🥼

www.mdpi.com/2227-7382/14...

#proteomes #proteomics #proteoform #phosphoproteomics #MassSpec

Site-Specific and Quantitative O-GlcNAc Proteomics for Hepatocellular Carcinoma O-linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation) underlies the pathogenesis of multiple cancers, including hepatocellular carcinoma (HCC). However, comprehensive and quantitative characterization of site-specific O-GlcNAcylation at the proteome scale remains technically challenging. Here, we employed an integrated workflow for the quantitative O-GlcNAc proteomics of HCC and controls. Proteins from liver samples were subjected to chemoenzymatic labeling, photocleavable alkyne-biotin-based enrichment, proteolytic digestion, and isotopic labeling with tandem mass tags. The O-GlcNAc peptides were analyzed by a nanoUPLC-MS/MS system in HCD product-dependent EThcD (HCD-pd-EThcD) mode for site mapping and quantification. A total of 440 O-GlcNAc peptides, representing 305 sites on 196 proteins, were confidently identified. Differential analysis revealed 190 O-GlcNAc peptides from 121 proteins significantly upregulated in HCC after normalization to their corresponding protein abundance. Functional enrichment and protein–protein interaction analyses indicate that proteins with increased levels of O-GlcNAcylation are involved in nuclear transport, transcriptional regulation, and ATP-dependent chromatin remodeling. Our work provides quantitative proteomic insights into O-GlcNAcylation in HCC, revealing global upregulation and functional clustering of O-GlcNAc-modified proteins. These findings will help elucidate the functional roles of O-GlcNAcylation in liver cancer, facilitating the development of novel therapeutics and sensitive biomarkers.

Site-Specific and Quantitative O-GlcNAc Proteomics for Hepatocellular Carcinoma #JProteomeRes #MassSpec pubs.acs.org/doi/10.1021/...

EIQuan: A Stacked Ensemble Learning-Based Predictor for Quantification of Nontargeted Chemicals in Gas Chromatography Coupled with Electron Ionization High-Resolution Mass Spectrometry Analysis Nontargeted analysis using gas chromatography coupled with electron ionization high-resolution mass spectrometry (GC-EI-HRMS) is a vital tool for identifying a large quantity of compounds in complex environmental samples. Herein, we employed GC-EI-HRMS to profile chemicals in wastewaters from an iron and steel corporation. To address the challenge of quantifying compounds without authentic standards, we developed a stacked ensemble learning model using bootstrap aggregation to integrate the predictions from three distinct base learners. A total of 910 compounds were tentatively identified across all wastewater samples, which were primarily categorized into 19 subgroups. Based on these major categories, 278 reference standards were used to develop a stacked ensemble learner. This model outperformed semiquantitative methods based on surrogates, with 95% of quantification errors falling within a 3.79-fold range. Total quantified concentrations ranged from 8.86 × 105 (influent) to 7.01 × 103 μg/L (effluent) in coking wastewater and from 331 μg/L (influent) to 47.1 μg/L (effluent) in mixed wastewater. Notably, 97.1% of tentatively identified chemicals fell within the model’s applicability domain. To facilitate the model application, a user-friendly predictor, EIQuan, was developed, providing an efficient tool for predicting response factors of GC-amenable environmental pollutants. This study establishes a robust framework for accurate semiquantification of unknown pollutants in complex industrial wastewater.

EIQuan: A Stacked Ensemble Learning-Based Predictor for Quantification of Nontargeted Chemicals in Gas Chromatography Coupled with Electron Ionization High-Resolution Mass Spectrometry Analysis #EST #MassSpec pubs.acs.org/doi/10.1021/...

Polychlorinated Alkane Profiles and Concentrations in Bolivian Andes Soils Point to a Long-Range Transport Influence High-altitude terrain may intersect the upper atmospheric boundary layer and exhibit distinct environmental dynamics. We investigated the anthropogenic pollutants polychlorinated alkanes (PCAs, also known as chlorinated paraffins) in surface soils along a transect from the La Paz-El Alto metropolitan area in Bolivia (3200–4100 masl) to the upper slopes of Mount Chacaltaya (>5200 masl), around 16 km away. Concentrations of PCAs in urban soils (750–5,230 ng/g organic carbon [OC]) decreased exponentially with increasing distance from the urban boundary, declining to ∼150 ng/g OC at elevations below 4,700 masl. Beyond 4,700 masl concentrations increased again, reaching levels comparable to those in the urban area, 1,670–4,300 ng/g OC, above 5,000 masl. Given that pollutant concentrations typically decline with distance from their source, this altitudinal trend, together with a pronounced shift in PCA forensic fingerprints near 4,700 masl, strongly suggests contributions from sources beyond the local metropolitan area. Carbon and nitrogen isotope signatures in organic carbon further support long-range transport as a source, consistent with previous modeling and observations that the upper slopes of Mount Chacaltaya predominantly receive air masses and organic carbon from distant regions via transport in the free troposphere. Our observation that pollutant levels in high-altitude areas are comparable to those in the metropolis of 1.8-million inhabitants underscores the efficiency of long-range atmospheric transport.

Polychlorinated Alkane Profiles and Concentrations in Bolivian Andes Soils Point to a Long-Range Transport Influence #EST #MassSpec pubs.acs.org/doi/10.1021/...

RT Parastoo Azadi @CCRCUGA Advance your expertise in carbohydrates, glycoproteins, and glycomics through our hands-on, laboratory-focused training at the

RT Parastoo Azadi @CCRCUGA Advance your expertise in carbohydrates, glycoproteins, and glycomics through our hands-on, laboratory-focused training at the #CCRC.

ast.uga.edu/training-in-...

#glycotime #glycoscience #glycomics #MassSpec #NMR #glycobiology #ResearchTraining #UGA

Chemistry Cat welcomed some special guests today! We love when customers visit our lab equipment showroom. www.ietltd.com

#masssspectrometry #teammassspec #massspec #hplc #lab #phd #nmrchat

Welcome! You are invited to join a meeting: Proteoform Thursday: Jeffrey Huang presents - A Catenin Phospho-Code for Adherens Junction Organization. After registering, you will receive a confirmation... Proteoforms, defined by the precise primary structure of proteins, are becoming a central currency in modern proteomics because they more directly link to cellular functions and disease phenotypes. Re...

Join us March 26 for Proteoform Thursday: Jeffrey Huang presents - "A Catenin Phospho-Code for Adherens Junction Organization"
us06web.zoom.us/meeting/regi... #proteomics #massspec