Clinical Proteomics

ObjectiveA catheter-free, non-radiolabeled method that permits in vivo measurement of tissue-specific glucose uptake does not exist. To address this gap, we sought to develop and validate a new, higher throughput mass spectrometry (MS)-based method that combines an injection of insulin with a non-radiolabeled glucose tracer, 2-fluoro-2-deoxyglucose (2FDG), to determine insulin-stimulated tissue-specific glucose clearance in conscious, unrestrained mice. MethodsInjections of saline or insulin with 2FDG were coupled with LC-Q Exactive Hybrid Quadrupole-Orbitrap (LC) MS-based measures of plasma 2FDG and tissue (2-fluoro-2-deoxyglucose-6-phosphate) 2FDGP to determine glucose clearance in mice under several different conditions. ResultsThe newly developed method was first applied to a dose response experiment in mice. Next, the ability of this method to quantify changes in glucose clearance in response to an insulin stimulus was assessed, and glucose clearance was compared between chow and high fat fed mice. Results from these studies showed that insulin-stimulated skeletal muscle and heart glucose clearance can be estimated following a bolus injection of tracer, and these fluxes are blunted in diet-induced obese mice. The broad applicability of this approach was then demonstrated by assessing glucose clearance in a mouse model with anticipated changes in insulin-stimulated skeletal muscle glucose metabolism. ConclusionsThe results validated a new LC-MS method to quantify insulin-stimulated tissue-specific glucose clearance in vivo without the use of catheters or radiolabeled tracers. The method offers great potential because it is designed for application to pre-clinical studies seeking high throughput tests and/or assays that can be coupled with discovery technologies such as genomics, proteomics and metabolomics. HIGHLIGHTSO_LIIn vivo glucose clearance can be estimated by a new non-radiolabeled method. C_LIO_LIThe plasma tracer to tracee ratio is required to determine tissue tracer phosphorylation. C_LIO_LIMeasures of plasma glucose and tracer kinetics are critical for data interpretation. C_LIO_LIThe new method can be combined with omics technologies such as metabolomics. C_LI

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft tissue sarcomas and the most common cause of disease-associated death for Neurofibromatosis Type 1 (NF1) patients. In the context of NF1, MPSNTs develop from benign premalignant precursors. The transition to malignancy is usually accompanied by loss of the polycomb repressive complex 2 (PRC2), leading to aberrant upregulation of many genes. The specific mechanisms disrupted by PRC2 loss remain incompletely understood. There is a significant gap in our knowledge of which cell-surface targets become derepressed and therapeutically actionable following PRC2 loss, contributing to the current lack of effective targeted therapies for MPNSTs. This study aims to address this gap by using cell-surface capture technology with mass spectrometry to profile MPNST models. In doing so, we define PRC2-dependent effects on the cell surface proteome, including specific biological pathways that are enhanced or suppressed at the cell surface protein level. We also create an MPNST cell-surface protein compendium comprised of proteins that are highly expressed across a variety of well-defined MPNST models. We prioritized proteins that are preferentially expressed in MPNST or other cancers and for which FDA-approved therapies already exist. Specific proteins from this compendium were molecularly targeted with antibody-drug conjugates in these models to surmise their therapeutic efficacy. Results reveal PTK7 as a novel and promising target for MPNST. In total, these efforts represent a step toward addressing the knowledge gap in MPNST genesis and identifying new therapeutic targets for further testing. Additionally, this data serves as a resource for other researchers wishing to characterize specific molecular targets. KEY POINTSPRC2 modulates key MPNST signaling pathways through the cell surface proteome Cell surface proteomics identifies a plethora of therapeutic targets for MPNST targeted therapy Antibody-drug conjugates targeting PTK7 show enhanced efficacy in reducing MPNST viability IMPORTANCE OF THE STUDYThis study utilizes advances in biochemistry to profile the surface proteome of malignant peripheral nerve sheath tumors. In doing so, it identifies many proteins whose presence is abundant on the cell surface of MPNST cells. Pre-clinical drug testing shows that use of antibody-drug conjugates may be effective in killing MPNST cells when targeted to epitopes identified in our MPNST cell surface proteome compendium. This study is a departure from more commonly used transcriptomic methods to identify cell surface proteins by using direct surface capture and mass spectrometry, providing a more direct measurement of cell surface protein abundance. Additionally, it identifies a handful of proteins which can be directly targeted pharmaceutically and one in particular, PTK7, whose targeting is highly effective in killing MPNST cells.

BackgroundTriple-negative breast cancer (TNBC) remains the most clinically challenging breast cancer subtype, in part due to the absence of validated molecular targets and the limited availability of non-invasive early detection strategies. Tumor-derived exosomes have emerged as promising liquid biopsy analytes, yet the functional organization of their protein cargo and the identification of biologically meaningful candidates remain incompletely characterized. MethodsWe present a Composite Driver Score (CDS) framework that integrates differential expression magnitude with protein-protein interaction network topology and Analytic Hierarchy Process (AHP)-based multi-criteria weighting to prioritize exosomal protein candidates in a systems-informed manner. The framework was applied to publicly available label-free quantitative proteomic datasets comparing MDA-MB-231 (TNBC) and MCF-10A (non-tumorigenic) exosomal fractions, with cross-dataset validation performed on an independent proteomic dataset. ResultsCDS prioritization demonstrated robustness to variations in proteome depth and parameter weighting, consistently recovering a functionally coherent set of extracellular matrix (ECM) and adhesion-associated proteins. Network and pathway analyses revealed coordinated co-enrichment of integrin receptors, cognate ECM ligands, and associated co-receptors -- consistent with selective packaging of a functionally integrated invasion module. Agrin (AGRN), a heparan sulfate proteoglycan with virtually limited prior characterization in TNBC exosome biology, emerged as a high-priority candidate through its network integration within this ECM program. ConclusionsThese findings support a model in which TNBC-derived exosomes carry coordinated molecular programs capable of modulating extracellular matrix architecture. The CDS framework offers a transferable strategy for integrative exosomal biomarker prioritization and a systems-level foundation for targeted liquid biopsy panel development.

Peptide-level analyses are becoming increasingly popular in mass spectrometry-based proteomics and are being applied, for example, in immunopeptidomics, structural proteomics, and analyses of post-translational modifications. In such analyses, peptides that are not biologically meaningful but instead arise as artifacts prior to mass spectrometry analysis pose the risk of data misinterpretation. Here, we describe an approach based on retention time analysis and precise chromatographic peak matching to identify peptides generated by in-source fragmentation (ISF), which occurs between chromatographic separation of peptide mixtures and the first mass filter of a tandem mass spectrometer (MS). To understand the prevalence and properties of ISF, we generated 13 proteomics datasets and analyzed them along with additional 25 previously published datasets spanning a broad range of sample types, MS, and proteomics approaches including classical bottom-up proteomics, immunopeptidomics, structural proteomics, and phosphoproteomics. We found that, in typical trypsin-digested samples on average 1 % of fully-tryptic peptides and 22 % of semi-tryptic peptides originated from ISF. However, we observed large variations between datasets, and in-source fragments exceeded, in some cases, a third of the total peptide identifications. The extent of ISF was dependent on the peptide sequence, the instrument, method parameters, and sample complexity. Although ISF did not impair relative quantification across samples, it generated peptides that could be misinterpreted qualitatively, inflated peptide identifications, and comprised up to 37 percent of peptides shorter than 9 amino acids in immunopeptidomics datasets. We propose that, for peptide-centric applications, our open-source ISF detection approach be used to re-annotate peptides generated by ISF and remove them to avoid misinterpretation of data. ISF is an increasing concern with improving mass spectrometers, as they enable detection of an ever-increasing number of m/z features, including low abundance features like ISF products. Our work thus addresses a growing issue in proteomics and presents solutions to mitigate the impact of in-source fragment peptides. In the future, improved feature detection algorithms may enable elucidation of new ISF patterns affecting side chains that have been missed so far, which could contribute to explaining the vast space of as-yet unannotated proteomics data.

Cultivated meat production requires robust and validated analytical methods for comprehensive characterization. While transcriptomics-based approaches establish the foundational profile of molecular analysis, proteomics provides additional resolution that further enhances scientific certainty in both product development and safety characterization. However, the industry adoption of proteomics is currently hindered by technical complexity and a critical lack of analytical standardization, which leads to significant workflow-dependent variations in proteome coverage. To address this gap, we investigated the influence of key workflow steps (digestion, cleanup, LC-MS conditions) on the proteome profile of cultivated duck biomass. We compared five bottom-up sample preparation protocols - two traditional in-solution options (urea and SDC-based protocols), two device-based approaches (PreOmics iST and EasyPep kits), and an innovative protocol (SPEED), and demonstrated that device-based protocols offered the highest peptide yield and proteome coverage. However, optimization allowed cost-effective in-solution methods to achieve comparable performance. Specifically, an optimal digestion time of 3 hours at 37{degrees}C and the use of polymer-based desalting columns significantly enhanced protein identification ([~]4500 - 5000 IDs). Moreover, data independent acquisition (DIA) provided deeper proteome coverage than data dependent acquisition (DDA) with higher precision ([~]6500 vs 5000 IDs). The validated Standard Operating Procedures presented here establish a standardized framework for bulk bottom-up proteomics in cultivated meat, facilitating the generation of reliable and comparable data required for robust multi-omics characterization. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/713501v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@5b61b8org.highwire.dtl.DTLVardef@16c7e65org.highwire.dtl.DTLVardef@1de21d2org.highwire.dtl.DTLVardef@7e984a_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIComplexity and non-standardization limit MS-proteomics use in cultivated meat (CM). C_LIO_LICM protein profile varies with sample prep, LC-MS, and data processing pipeline. C_LIO_LIDevice-based and optimized cost-effective protocols offer a high proteome coverage. C_LIO_LIProteomics can complement transcriptomics for a comprehensive CM characterization. C_LIO_LIProposed standardized methods ensure reliable data for future regulatory submissions. C_LI

Mantle cell lymphoma (MCL) is one of the deadliest forms of Non-Hodgkins B-cell lymphoma. Typically, patients present with both overexpression of CyclinD1 and secondary mutations identified by genomic sequencing. Although MCL patients may initially respond to treatment, they eventually relapse and succumb to disease, highlighting the essential need to identify new targets for treatment. Here we performed proteomic profiling of healthy B cells and three different forms of B-cell malignancies, including MCL, to define the proteomic signature of MCL. We compared the proteome of each to MCL and identified 10 proteins that are specifically upregulated in MCL. Of these 10 proteins, seven of them show no transcriptional changes and have been overlooked by conventional RNA expression analysis. Further analysis of the proteomic signature reveals potential avenues for dual targeting in CAR T-cell therapy and provides guidance for personalized therapeutics based on protein expression. STATEMENT OF SIGNIFICANCEWe present a resource defining the protein landscape of MCL, CLL, and FL as compared to healthy b cells identified utilizing quantitative proteomics from primary patient samples. Applied to MCL, our results identify 10 proteins specifically upregulated in MCL that may prove to be therapeutic targets to treat the disease.

Metabolic syndrome (MetS), characterized by abdominal obesity, insulin resistance, dyslipidemia, and hypertension, affects a substantial proportion of the global population and increases the risk for cardiovascular disease, diabetes, and metabolic dysfunction-associated steatotic liver disease (MASLD). Despite its prevalence, there are currently no effective pharmacological therapies targeting MetS, highlighting the need to identify novel etiological mechanisms, particularly within the gastrointestinal (GI) tract. Using a mouse model of MetS and healthy lean controls, we assessed the colonic microenvironment through metabolomic, transcriptomic, and microbiome analyses. Colonic organoids were cultured to further explore epithelial alterations. Additionally, human MetS fecal metabolomics data were cross-compared with the mouse model to validate translational relevance. MetS mice exhibited upregulation of colonic anabolic pathways, including glycolysis, the pentose phosphate pathway, and the tryptophan/kynurenine pathway, without evidence of intestinal inflammation. Microbiome analysis revealed an increased abundance of the genus Lactobacillus in MS NASH mice. Colonic organoids from MetS mice showed altered goblet cell differentiation. Comparative analysis with human MetS fecal metabolomics demonstrated similar dysregulated pathways, underscoring the translational relevance of these findings. Our study reveals significant metabolic and microbial alterations in the colon of MS NASH mice, implicating a dysfunctional GI tract as a potential etiological factor in MetS. These findings highlight specific metabolic pathways and microbial signatures that could serve as future therapeutic targets for MetS. NEW & NOTEWORTHYThis study identifies the colon as a metabolically active tissue affected in metabolic syndrome. Despite the absence of intestinal inflammation, MS NASH mice displayed altered colonic metabolism and microbiota composition, with conserved metabolite changes matching those seen in humans with metabolic syndrome. These findings highlight colonic metabolic dysfunction as a potential driver of gut dysbiosis and disease progression in metabolic syndrome and MASLD. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/716131v1_ufig1.gif" ALT="Figure 1"> View larger version (77K): org.highwire.dtl.DTLVardef@1b7c685org.highwire.dtl.DTLVardef@4a832aorg.highwire.dtl.DTLVardef@1e95c66org.highwire.dtl.DTLVardef@1b14209_HPS_FORMAT_FIGEXP M_FIG C_FIG

Many proteomics protocols rely on enzymatic digestion of complex protein mixtures to generate peptides with predictable cleavage patterns for the mass spectrometry analysis. One of the most utilized enzymes, trypsin, is classically defined as a serine endopeptidase with high specificity for cleaving peptide bonds on the C-terminal side of internal lysine and arginine residues. Accordingly, trypsin is not expected to remove the N-terminal arginine, which may arise through posttranslational modification such as arginylation or by proteolysis exposing internal residues as the new N-termini. N-terminal arginine plays important biological roles, including functioning as an N-degron and modulating protein interactions/signaling through its positive charge. Curiously, prior mass spectrometry-based studies utilizing trypsin to identify proteins bearing N-terminal arginine have frequently reported low and inconsistent yields, suggesting potential systematic bias in current proteomic approaches. Here, we explored whether trypsin would affect the integrity of the N-terminal arginine. By using antibodies specifically recognizing N-terminal arginine of different peptides, and by using mass spectrometry peptide analysis, we show that trypsin can remove N-terminal arginine residues in an exopeptidase-like manner. This effect occurs across a range of digestion conditions consistent with standard proteomic workflows, on peptides or whole proteins, and depends on trypsin concentration, incubation time, and catalytic activity. In addition, we show that the alternative arginine-cleavage enzyme Arg-C can also affect N-terminal arginine in a sequence-dependent context. In contrast, Lys-C and LysargiNase do not exhibit such effects, providing suitable alternative digestion strategies. Together, these findings reveal an unappreciated enzymatic behavior of arginine-cleaving proteases and suggest that their widespread use may systematically compromise the detection of N-terminal arginine in proteomic studies.

The extracellular matrix (ECM) and cell surface glycocalyx are key components of biology and play crucial roles in development and tissue function, as well as disease. Proteoglycans, and their glycosaminoglycan (GAG) side chains, are critical components of the ECM and the glycocalyx. GAGs can bind to many different proteins, such as chemokines, and form hydrated barriers around cells. Existing and new methods are helping us to uncover more about the roles of GAGs in biology. Here, we expand on existing technologies and provide streamlined, standardised and well-documented methods that can be easily adopted in standard analytical facilities. We provide extensive detailed step-by-step guides describing sample disruption, GAG disaccharide preparation from biological tissues and their analysis by HILIC-MS/MS. In addition, we demonstrate utility of this method when using a range of different samples as biological sources. This method will sit alongside existing and new techniques to help improve access to GAG analysis, and thereby further the field of understanding GAG function in complex biological contexts.

Human milk contains structurally diverse glycans with key roles in shaping infant development, yet analytical constraints limit characterisation from low-volume samples. Glycosaminoglycans (GAGs), including chondroitin sulphate (CS), are understudied due to existing protocols requiring sample volumes of at least 5 mL and lengthy extraction steps prior to instrumental analysis. This study establishes a workflow for quantifying CS disaccharides from 25 {micro}L of human milk, enabling analysis of samples previously inaccessible to GAG profiling, such as those collected as salvage samples from neonatal intensive care units. For CS quantification, the CS is first enzymatically depolymerised using chondroitinase ABC to release repeating disaccharide units. Matrix complexity is reduced via two rounds of acetonitrile-based protein and lipid precipitation. Disaccharides are separated by hydrophilic interaction liquid chromatography and detected using a Triple Quadrupole Mass Spectrometer, providing robust sensitivity for all CS disaccharides. Method development and validation were performed using pooled mature human milk from term infants. This workflow facilitates detection of all CS disaccharides, with low but reproducible recoveries for total CS. Low- and high-level spike recoveries were 41.3% (RSDr 7.5%, RSDiR 15.9%) and 43.7% (RSDr 24.4%, RSDiR 27.9%), respectively. Despite modest absolute accuracy, precision remained sufficient to make relative comparison of CS concentrations between samples. This method expands the analytical toolkit for human milk glycomics, enabling same day preparation and CS profiling from sample volumes that are 200 times smaller than prior work, supporting future investigations into GAG-mediated functions in early life. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/723732v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@176dffborg.highwire.dtl.DTLVardef@16ae4ccorg.highwire.dtl.DTLVardef@d333c2org.highwire.dtl.DTLVardef@1eb3216_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO Schematic of sample preparation protocol 25 L of human milk is combined with lyase enzymes and TRIS buffer containing the internal standard prior to incubation. Samples then undergo multiple rounds of centrifugation and refrigeration before analysis via LC-MS/MS. Made using BioRender.com. Glycan nomenclature following Varki et al., 2015. C_FIG

In conventional native mass spectrometry (MS), one faces severe limitations when challenged with heterogenous, high mass samples, commonly failing to resolve clear peak distributions and thus mass determination. Charge detection MS (CDMS) has emerged as a premier method to analyze these samples by determining mass-to-charge ratio (m/z) and charge (z) simultaneously. Here, the two currently available commercialized CDMS systems, the Orbitrap-based Direct Mass Technology (DMT) and the electrostatic linear ion trap (ELIT)-based Xevo CDMS are applied to human norovirus capsids from two different strains, GI.1 Norwalk and GII.17 Kawasaki. The norovirus capsid is highly heterogenous due to N-terminal processing on the repeating subunits that it is built from and commonly forms T = 3 and sometimes T = 4 particles. Both CDMS approaches were able to determine similar masses in both strains. GII.17 Kawasaki exhibits both T = 3 and T = 4 particles, though the Xevo CDMS measurements were closer to the theoretical mass than the DMT instrument. Interestingly, GII.17 Kawasaki also displayed non-classical mass distributions with high abundance in-between T = 3 and T = 4 which was then confirmed by cryogenic electron microscopy (cryo-EM), demonstrating an oval capsid shape. GI.1 Norwalk displays a wide mass distribution in both instruments that exceeds the theoretical T = 3 mass by 8-10 %. Proteomics and native MS experiments suggest possible interactions with a protein from the expression system. This study demonstrates the capabilities of two distinct CDMS methodologies on two viral capsids and presents the first non-classical capsid assembly in a GII.17 noroviral capsid.

Background & AimsDiabetes mellitus has been associated with both intestinal barrier dysfunction and peripheral neuropathy leading to increased risk of infection. The mucus layer forms a physical barrier against pathogens and is a critical component of the intestinal barrier that may be impaired in diabetes. This study aimed to assess how diabetes impacts goblet cells (GCs), mucus layer integrity, and innervation in the colon. MethodsFluorescence microscopy was used to investigate GCs, the mucus layer, and innervation in the colon of db/db mice. Custom open-access image analysis pipelines were developed to quantify GC numbers, location and content, mucus thickness, bacterial colonization, and innervation density in intestinal tissue sections. We also treated mice with the clinically used glucagon-like peptide 1 receptor (GLP-1R) agonist liraglutide to assess its capacity to reverse pathological changes to GCs and the mucus layer in a model of established type 2 diabetes (T2DM). ResultsThe mucus layer was significantly thinner in the colon of db/db mice with established diabetes and bacteria more readily colonized the epithelium and crypts. Intercrypt GC numbers were significantly reduced in db/db mice. However, there were significantly more GCs per crypt, and crypts were elongated in the db/db colon. Innervation was reduced in the mucosa and external muscle of the colon, consistent with diabetic neuropathic changes. Liraglutide treatment increased the size of GCs but had no effect on GC numbers, mucus thickness, or innervation in this model of established T2DM. ConclusionsMucus barrier dysfunction and GC hyperplasia is evident in the db/db colon. Increased microbial penetrability through the mucus layer suggests potential implications for the increased risk of gastrointestinal infection in diabetes.

Background: Citrin deficiency, caused by biallelic pathogenic variants in SLC25A13, must be identified early to prevent serious complications such as hyperammonemia and liver failure. However, clinical diagnosis is often delayed due to its nonspecific presentation and limited sensitivity of amino acid-based newborn screening methods. Although genome-based evaluations are being investigated to address these issues, concerns about their cost, turnaround time, variant interpretation ability, and data handling highlight the need for a more practical yet reliable alternative. We investigated the feasibility of applying proteomic approach on dried blood spots (DBS), which are routinely used in newborn screening. Methods: We performed untargeted liquid chromatography-tandem mass spectrometry to analyze the proteome of DBS using a previously developed "non-targeted analysis of non-specifically DBS-absorbed proteins" (NANDA) workflow. SLC25A13 protein abundance was quantified in individuals with biallelic loss-of-function mutations, compound loss-of-function/missense mutations, and heterozygous carriers; this was also evaluated in healthy and diseased controls representing relevant differential diagnoses. To leverage proteomic information, we derived a multivariate proteomic signature using feature selection and evaluated its performance with leave-one-out cross-validation. Biological relevance was assessed by enrichment analysis, and complementary transcriptomics was performed using RNA sequencing. Results: A total of 7,474 proteins, including SLC25A13, were consistently detected in DBS. SLC25A13 was undetectable in individuals with biallelic loss-of-function mutations. However, individuals with compound loss-of-function/missense genotypes showed reduced but measurable SLC25A13 levels, comparable to those observed in heterozygous carriers. In contrast, a compact 15-protein signature accurately identified individuals with compound loss-of-function/missense genotypes (AUC, 0.99; sensitivity, 1.00; specificity, 0.95). The signature was enriched for Ca2+-response, and transcriptomics showed downregulation of genes related to multimodal ion channels in affected individuals compared to controls. Conclusions: DBS-based proteomic profiling may assist in the diagnosis of citrin deficiency through SLC25A13-quantification and a biologically plausible multivariate signature. More broadly, this strategy offers a promising new diagnostic layer for protein disorders, providing a proteomic readout in a clinically practical DBS format with potential utility for future diagnostic and screening applications.

Transcriptomic and proteomic measurements from the same single cell provide complementary information that cannot be inferred from either modality alone, yet methods for the parallel recovery of both analyte classes from a single-cell lysate remain limited. Here, we describe a workflow in which individual cells are isolated by automated dispensing into a minimal, MS-compatible lysis volume, followed by sequential mRNA capture and protein supernatant recovery, prior to independent downstream processing. The method is compatible with standard library preparation and data-independent acquisition proteomics pipelines and requires no dedicated instrumentation beyond a single-cell dispensing platform. We evaluated workflow performance on 67 single cells across 3 iBlastoids. Transcriptomic sequencing detected a median of 5375 genes per cell, and proteomic analysis identified a median of 2123 protein groups per cell across two mass spectrometry platforms. Compared with a standalone single-cell proteomics protocol, incorporating the mRNA extraction step reduced median proteomic depth by approximately 11% (median 1,965 vs. 2,204 protein groups per cell), while mean percell identification remained comparable across workflows (1,790 vs. 1,775 protein groups per cell). Direct comparison of paired transcript and protein abundance yielded a median Spearman correlation of {rho} {approx} 0.38; after correction for detection depth, the partial correlation was 0.067.

(1) Aims and hypothesisLoss-of-function mutations in SLC30A8, encoding the zinc ion (Zn2+) transporter ZnT8 in pancreatic beta cells, lower type 2 diabetes risk dose-dependently, but the underlying mechanisms remain unclear. Here, we combine proteomic, transcriptomic and functional approaches in human stem cell-derived islet-like clusters bearing common alleles or the inactivating variant R138X. We hypothesized that this variant protects against the deleterious effect of Zn2+ depletion on cell survival and function. (2) MethodsHuman embryonic stem cells INS(GFP/w) (MEL1), and CRISPR/Cas9-derived heterozygous or homozygous R138X lines were differentiated into stem cell-derived islet-like clusters. Intracellular Zn2+ levels were reduced using the chelator N,N,N',N'-tetrakis(2-pyridylmethyl)-1,2-ethanediamine (TPEN). Apoptosis was assessed by TUNEL staining and protein expression by immunofluorescence. Glucose-stimulated calcium (Ca2+) dynamics were measured using the intracellular probe (Cal590) and insulin secretion by homogenous time-resolved fluorescence. Transcriptomic profiling was performed by bulk mRNA sequencing and proteomics by liquid chromatography-tandem mass spectrometry. (3) ResultsIntracellular Zn2+ depletion increased apoptosis in wild-type islet-like clusters, whereas R138X clusters were protected. R138X heterozygous clusters showed a mild increase in GCG+ cells and R138X homozygous clusters exhibited increased NKX6.1+ cells, without affecting polyhormonal populations. These changes were reversed under Zn2+ depletion. Transcriptomic and proteomic analyses, assessing genotype effects while accounting for Zn2+ depletion, showed that R138X clusters (versus wild-type) exhibited upregulation of genes and proteins involved in vesicle trafficking, secretion, Ca{superscript 2} signaling and mitochondrial metabolism, consistent with enhanced glucose-stimulated insulin secretion in homozygous clusters. Conversely, genes and proteins associated with extracellular matrix remodeling, metal-ion handling, apoptosis and cellular stress were downregulated. R138X clusters displayed altered Ca2+ signaling, with decreased area under the curve and oscillation amplitude, but increased frequency. These differences were reversed by TPEN, while Zn2+ depletion impaired Ca2+ response in wild-type clusters. Despite lowered overall activity, R138X homozygous clusters showed enhanced overall cell-cell connectivity, reversed by TPEN treatment. The opposite effects were observed in R138X heterozygous clusters, showing improved connectivity and activity under Zn2+ depletion. (4) Conclusion and interpretationIntracellular Zn2+ depletion compromises islet-like cluster identity and function, while the R138X variant confers protection against these effects. Under Zn2+-depleted conditions, ZnT8 deficiency promotes a more mature and metabolically active state of the R138X clusters, with enhanced Ca2+ signaling and insulin secretion, supported by a structural remodeling and the downregulation of apoptosis and cellular stress. These findings highlight the therapeutic potential of targeting ZnT8 in type 2 diabetes and support its relevance for further improving cell-based therapies. Research in ContextO_ST_ABSWhat is already know about this subject?C_ST_ABSO_LIRare inactivating mutations in the insulin granule-associated zinc transporter gene, SLC30A8/ZnT8, drive lowered type 2 diabetes risk. C_LIO_LIPrevious studies have indicated that apoptosis is lowered, and glucose-stimulated insulin secretion enhanced, after ZnT8 inactivation. C_LIO_LIThe molecular mechanisms underlying these changes are unclear. C_LI What is the key question?O_LIHow do inactivating mutations in SL30A8/ZnT8 lead to lowered apoptosis and enhanced insulin secretion from stem cell-derived islet-like clusters, and is altered susceptibility to intracellular zinc depletion involved? C_LI What are the new findings?O_LIThe rare inactivating R138X mutation in SLC30A8 leads to gene dose-dependent changes in the transcriptome and proteome of islet-like clusters. C_LIO_LIChanges include upregulation of maturity and downregulation of immaturity genes. C_LIO_LIDepletion of intracellular Zn2+ exaggerates the protective effects of the inactivating mutation on apoptosis and insulin secretion C_LI How might this impact on clinical practice in the foreseeable future?O_LIOur findings suggest that careful monitoring of both dietary zinc intake and of circulating levels of zinc ions, whose effects are mitigated in SLC30A8 mutation carriers, may be helpful in some populations to lower diabetes risk. C_LI

Deep characterization of intact proteoforms remains an analytical challenge in functional proteomics, particularly for heterogenous multi-site post-translational modifications at distinct amino acid residues. Histones are among the most dynamically and diversely post-translationally modified proteins in eukaryote cells, carrying multiple, co-occurring and reversible modifications that can give rise to isomeric proteoform species. Tandem mass spectrometry with multimodal fragmentation capabilities is a promising approach for deep characterization of intact proteoforms, such as modified histones. We applied the novel timsOmni mass spectrometer, which incorporates the Omnitrap platform enabling multimodal MS workflows, for residue-level mapping of histone modifications, including acetylation and methylation. Recombinant histones H3.1 and H4 were in vitro acetylated by enzymes GCN5, PCAF and p300 to generate mono- and multi-acetylated proteoforms. Complementary MS2 electron- and collision-based dissociation (ECD, EID, RCID and ECciD), together with MS3 strategies, produced complete or near-complete backbone fragmentation of intact protein ions (>92% amino acid sequence coverage). For monoacetylated species generated by the more site-selective lysine acetyltransferases, the dominant proteoform matched the known catalytic preferences of the enzymes (H3.1K14ac for GCN5 and PCAF, and H4K8ac for PCAF), while minor positional isomers were also identified and their relative abundance estimated. In contrast, the broader substrate specificity of p300 produced a wide distribution of H4 proteoforms bearing up to seven acetylated lysine residues. Species carrying six and seven acetylations were characterized by multimodal MS2/MS3 experiments, enabling localization of individual acetylation sites and discrimination of positional isomers. Finally, endogenous histone proteoforms from liver extracts were analyzed, yielding sequence coverages of 92-93% for the most abundant species and enabling confident localization of multiple PTMs (acetylation and methylation). These results illustrate that multimodal MSn fragmentation of intact proteins supports residue-level assignment of combinatorial histone marks and coexisting positional isomers. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=165 HEIGHT=200 SRC="FIGDIR/small/722147v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@387ab5org.highwire.dtl.DTLVardef@2410org.highwire.dtl.DTLVardef@13fc392org.highwire.dtl.DTLVardef@140e054_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMultimodal MS{superscript 2}/MS3 maps histone PTMs on intact proteins. C_LIO_LIECD, EID, RCID, and ECciD provide complete or near-complete sequence coverage. C_LIO_LIMS3 localizes acetylation sites, distinguishes positional isomers. C_LIO_LIEndogenous H4 proteoforms are assigned with site-specific PTM mapping. C_LI

Plasma proteomics is increasingly important for biomarker discovery and disease stratification; however, comprehensive and high-throughput analysis remains challenging because of the extreme dynamic range of plasma proteins. We previously established tomato lectin affinity purification-based mass spectrometry (TomAP-MS), a workflow that enhances plasma proteome coverage via tomato lectin-mediated enrichment. The initial workflow depended on a 4% sodium dodecyl sulfate (SDS) elution, followed by SP3-based purification and digestion, which raised complexity and restricted throughput. In this study, we developed an improved TomAP-MS workflow incorporating lauryl maltose neopentyl glycol (LMNG)-assisted acid elution (LAcE), in which proteins are eluted under acidic conditions in the presence of LMNG. This process is followed by pH adjustment and direct tryptic digestion without SP3 cleanup. Compared with conventional acid elution and the original SDS/SP3 workflow, LAcE increased protein identifications while simplifying sample preparation and improving throughput. Using the optimized workflow, we identified more than 7,500 proteins from human plasma and demonstrated broader applicability in extracellular vesicle enrichment and protein interaction analysis workflows. We demonstrated that ethylenediaminetetraacetic acid plasma was the preferred specimen type, enabling the identification of over 5,000 proteins from just 1 {micro}L of plasma, with minimal impact on proteomic profiles after up to three freeze-thaw cycles. Additionally, the analysis of plasma from 200 healthy individuals reproducibly detected 4,117 proteins across all samples, including many proteins associated with inherited disorders. These findings establish TomAP-MS with LAcE as a practical platform for deep plasma proteomics, supporting its future application in proteomics-based screening and diagnostics.

Understanding proteoforms, i.e., the various molecular forms in which proteins can exist, is important for deciphering biological processes and diseases. While capillary zone electrophoresis (CZE) proved advantageous for proteoform separation, limited sample loading capabilities restrict its application. Here, we present a novel comprehensive two-dimensional nanoLCxCZE-MS platform for deep top-down proteomics (TDP). The 2D platform is highly automated, enabling robust performance and the possibility to perform proteoform quantitation as demonstrated by isobaric labeling experiments. The high orthogonality of reversed-phase LC and CZE leads to a peak capacity of 2200, leading to an increase in the number of identified proteoforms in a human Caucasian colon adenocarcinoma cell lysate sample by a factor of 3 compared to nanoLC-MS. Furthermore, CZE mobilities enable the attribution of many more proteoforms to a certain proteoform family on the MS1-level. Overall, the flexible platform enables highly efficient separation of intact proteoforms combined with sensitive MS-based TDP workflows, both for untargeted and targeted analysis of complex biological samples. Graphical AbstractWe report a robust and automated comprehensive nanoLCxCZE-MS platform for top-down proteomics. In addition to large volume sample injection and separation by hydrophobicity in the nanoLC, the orthogonal separation by CZE in the second dimension leads to a strong increase in peak capacity and, thus, in the number of identified proteoforms. CZE mobilities also enable the attribution of many more proteoforms to a proteoform family on the MS1-level. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=46 SRC="FIGDIR/small/725123v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@df07b6org.highwire.dtl.DTLVardef@736d5corg.highwire.dtl.DTLVardef@10cef1org.highwire.dtl.DTLVardef@1825b55_HPS_FORMAT_FIGEXP M_FIG C_FIG

Breast cancer (BC) remains a leading cause of morbidity and mortality worldwide. Early detection remains the most effective strategy for improving prognosis. We explored the urinary extracellular vesicle (uEV) proteome for changes linked to BC which could also be potential biomarkers. Urine samples were collected from 20 participants across four groups (n = 5 each): newly diagnosed BC patients, benign breast disease (BBD) patients, individuals with breast cancer symptoms (symptom control, SC), and age-matched healthy controls (HC). EVs were isolated using size exclusion chromatography and extracted proteins were analysed using a GeLC proteomic approach. Proteins were identified and quantified using Proteome Discoverer and further analysed using MetaboAnalystR, Funrich and Metascape. A total of 256 proteins were identified from the uEV preparations. BC comparisons with BBD, SC and HC identified 7 proteins differentially expressed proteins (DEP); SERPINB1 -- Serpin family B member 1, LCN1 -- Lipocalin 1, SIRPA -- Signal regulatory protein alpha, ACTB -- Actin, beta, YWHAZ --Tryptophan 5-monooxygenase activation protein zeta, Ig JCHAIN and APOA1 -- Apolipoprotein A1. Receiver Operator Characteristic (ROC) curve assessments suggested that each DEP protein had an area under the curve (AUC) of > 0.8. These findings highlight EV-derived proteins as promising non-invasive biomarkers for breast cancer detection, warranting further validation in larger cohorts.

BackgroundPatient-derived tumor organoids are widely used in cancer research, yet the biological impact of tissue processing during model generation remains unclear. Fragment-based and dissociation-based approaches are commonly assumed to trade fidelity for uniformity, but their molecular consequences remain incompletely defined. MethodsWe performed a proteome-wide comparison of fragment-based (CUT) and dissociation-based (DIS) glioblastoma organoid protocols using quantitative mass spectrometry. Organoids from multiple patient tumors were cultured under growth factor-free or growth factor-supplemented conditions and compared with matched primary tissue. ResultsBoth protocols produced technically robust glioblastoma organoids when maintained in their native media. However, CUT organoids matched the reproducibility of DIS cultures while preserving a broader extracellular matrix repertoire and networks linked to collagen assembly, vascular support, and cell-matrix signaling. DIS cultures were biased toward exogenous basement membrane components and proliferative, growth factor-responsive states. Across tumors, CUT organoids consistently showed greater proteomic similarity to matched primary tissue, retaining neural, glial, stromal, and extracellular features largely absent from DIS models. ConclusionsFragment-based glioblastoma organoids can be both reproducible and biologically faithful. Tissue dissociation acts as a major perturbation that reshapes extracellular matrix organization, cellular states, and tumor identity, making protocol choice a critical determinant of model fidelity and translational relevance.