ProteomeXchange provides globally coordinated proteomics data submission and dissemination

Promoting lignocellulosic biorefinery by machine learning: progress, perspectives and challenges

The lignocellulosic biorefinery involves pretreatment, enzymatic hydrolysis, mixed sugar fermentation, and optional anaerobic digestion. This pipeline could be effectively implemented through machine learning (ML)-guided process optimization and strain modification rather than experimental or experience-based ones. This review takes a holistic perspective on the entire pipeline, discussing how ML could aid lignocellulosic, while other published work has focused on individual modules within the pipeline. This review also explores the model construction and evaluation strategies and highlights the emerging potential of transfer learning and hybrid ML models to address data insufficiency and improve model interpretability. Furthermore, challenges and future prospects of ML in lignocellulosic biorefinery will be elaborated in this review. Integrating ML into lignocellulosic biorefinery offers a promising pathway towards sustainable and competitive biorefinery systems.

Metabolic traits shape responses to LSD1-directed therapy in glioblastoma tumor-initiating cells

Lysine-specific histone demethylase 1A (LSD1) is an epigenetic regulator involved in various biological processes, including metabolic pathways. We demonstrated the therapeutic potential of its pharmacological inhibition in glioblastoma using DDP_38003 (LSD1i), which selectively targets tumor-initiating cells (TICs) by hampering their adaptability to stress. Through biological, metabolic, and omic approaches, we now show that LSD1i acts as an endoplasmic reticulum (ER) stressor, activating the integrated stress response and altering mitochondrial structure and function. These effects impair TICs' oxidative metabolism and generate reactive oxygen species, further amplifying cellular stress. LSD1i also impairs TICs' glycolytic activity, causing their metabolic decline. TICs with enhanced glycolysis benefit from LSD1-directed therapy. Conversely, metabolically silent TICs mantain ER and mitochondrial homeostasis, adapting to stress conditions, including LSD1i treatment. A dropout short hairpin RNA screening identifies postglycosylphosphatidylinositol attachment to proteins inositol deacylase 1 (PGAP1) as a mediator of resistance to LSD1i. Disruptions in ER and mitochondrial balance holds promise for improving LSD1-targeted therapy efficacy and overcoming treatment resistance.

HDAC6 inhibition by ITF3756 modulates PD-L1 expression and monocyte phenotype: insights for a promising immune checkpoint blockade co-treatment therapy

Introduction

Tumor immunotherapy has revolutionized cancer treatment, particularly through the use of immune checkpoint inhibitors targeting the PD-L1/PD-1 axis. While PD-L1 expression on tumor cells is an established predictive biomarker for therapeutic response, emerging evidence highlights the importance of PD-L1 expression on myeloid cells, both in the periphery and within the tumor microenvironment (TME). This study explores the immunomodulatory effects of the selective HDAC6 inhibitor ITF3756 on monocytes and dendritic cells (DCs).

Methods

Monocytes were stimulated with the pro-inflammatory cytokine TNF-α and treated with ITF3756. PD-L1 and CD40 expression levels were assessed by flow cytometry. Transcriptomic and proteomic analyses were performed to characterize changes in gene and protein expression profiles. T cell proliferation was evaluated in co-culture assays. Additionally, the impact of ITF3756 was assessed in an in vivo murine model of colon cancer.

Results

ITF3756 effectively downregulated PD-L1 expression in TNF-α-activated monocytes and enhanced their costimulatory capacity by increasing CD40 expression. Transcriptomic and proteomic analyses revealed that ITF3756 counteracted TNF-α pathway activation and downregulated multiple inhibitory immune checkpoint molecules, promoting a less immunosuppressive phenotype. In co-culture assays, ITF3756-treated monocytes and DCs significantly enhanced T cell proliferation. In vivo, ITF3756 treatment led to reduced tumor growth in a colon cancer model.

Discussion

These findings demonstrate that selective HDAC6 inhibition by ITF3756 modulates myeloid cell functionality by diminishing inhibitory signals and promoting T cell activation. Thus, ITF3756 represents a promising immunomodulatory agent that could enhance the efficacy of immune checkpoint blockade in cancer immunotherapy.

Aging-related alternative splicing drive neoantigen emergence revealed by transcriptome analysis of 1,255 human blood samples

This study aimed to identify age-related genes and alternative splicing (AS) events by comprehensive transcriptome analysis of 1,255 healthy blood samples from individuals aged 8-87 years. We identified 1,029 up-regulated and 1,186 down-regulated genes in older individuals, including 17 genes overlapped with known aging-associated genes, such as TFAP2A and Klotho. Gene set enrichment analysis revealed significant alterations in immunoregulatory and metabolic pathways during aging. However, many senescence-associated secretory phenotypes (SASP) involved genes did not exhibit changes in gene expression, suggesting that AS events may reveal additional age-related mechanisms. Aging also altered 6,320 AS events in 4,566 genes, impacting immune-related protein domains. The RNA-binding protein RBMS3 emerged as a key regulator of aging-specific AS events. In addition, neoantigen prediction analyses further identified potential neoantigens generated by aging-related AS events, with the HLA-C14:02 allele presenting the most neoantigenic peptides. Notably, 60 neoantigenic peptides were confirmed using proteomic data from elderly individuals, suggesting their potential as novel targets for anti-aging immunotherapy. Our study provides new insights into the role of alternative splicing in aging, highlights promising avenues for anti-aging immunotherapy.

MGAT3 and MGAT5 overexpression alters the protein cargo of extracellular vesicles released by metastatic melanoma cells

Extracellular vesicles (EVs) are potential non-invasive diagnostic, prognostic and therapeutic tools. Additionally, they are important contributors to tumorigenesis. Glycosylation has been found to modulate the composition of the EV proteome. Increased amounts of β1,6-branched N-glycans, synthesized by N-acetylglucosaminyltransferase V (GnT-V), are most commonly observed in melanoma and are associated with decreased cell adhesion and increased metastasis. The opposite effect is caused by the addition of bisecting GlcNAc by N-acetylglucosaminyltransferase III (GnT-III). To date, the impact of these enzymes on EV cargo in melanoma remains unexplored. Flow cytometry was used to study the surface glycosylation of genetic variants of WM266-4 melanoma cells with induced overexpression of GnT-III or GnT-V encoding genes (MGAT3 or MGAT5) and EVs released by these cells. LC-MS/MS proteomics was applied to analyze the effect of altered glycosylation on the proteome of released EVs, followed by detailed bioinformatic analysis. Flow cytometry analysis revealed dynamic changes in the surface glycosylation of EVs derived from melanoma cells overexpressing MGAT3 or MGAT5. Induced overexpression of MGAT3 or MGAT5 also caused significant changes in the proteome of EVs. The proteomic analysis identified a total of 1770 microvesicular and 704 exosomal proteins that play different roles in melanoma progression, including those with established diagnostic/prognostic potential and those closely associated with melanoma onset. Proteomic profiling of EVs derived from cells overexpressing MGAT3 and MGAT5 revealed functional changes in EV protein content driven by glycosylation modifications. The study presented a potential multifaced application of melanoma-derived EVs for diagnostic and prognostic purposes.

Rustims: An Open-Source Framework for Rapid Development and Processing of timsTOF Data-Dependent Acquisition Data

Mass spectrometry is essential for analyzing and quantifying biological samples. The timsTOF platform is a prominent commercial tool for this purpose, particularly in bottom-up acquisition scenarios. The additional ion mobility dimension requires more complex data processing, yet most current software solutions for timsTOF raw data are proprietary or closed-source, limiting integration into custom workflows. We introduce rustims, a framework implementing a flexible toolbox designed for processing timsTOF raw data, currently focusing on data-dependent acquisition (DDA-PASEF). The framework employs a dual-language approach, combining efficient, multithreaded Rust code with an easy-to-use Python interface. This allows for implementations that are fast, intuitive, and easy to integrate. With imspy as its main Python scripting interface and sagepy for Sage search engine bindings, rustims enables fast, integrable, and intuitive processing. We demonstrate its capabilities with a pipeline for DDA-PASEF data including rescoring and integration of third-party tools like the Prosit intensity predictor and an extended ion mobility model. This pipeline supports tryptic proteomics and nontryptic immunopeptidomics data, with benchmark comparisons to FragPipe and PEAKS. Rustims is available on GitHub under the MIT license, with installation packages for multiple platforms on PyPi and all analysis scripts accessible via Zenodo.

Lack of AtMC1 catalytic activity triggers autoimmunity dependent on NLR stability

Plants utilize cell surface-localized pattern recognition receptors (PRRs) and intracellular nucleotide-binding leucine-rich repeat (NLR) receptors to detect non-self and elicit robust immune responses. Fine-tuning the homeostasis of these receptors is critical to prevent their hyperactivation. Here, we show that Arabidopsis plants lacking metacaspase 1 (AtMC1) display autoimmunity dependent on immune signalling components downstream of NLR and PRR activation. Overexpression of a catalytically inactive AtMC1 in an atmc1 background triggers severe autoimmunity partially dependent on the same immune signalling components. Overexpression of the E3 ligase SNIPER1, a master regulator of NLR homeostasis, fully reverts the AtMC1-dependent autoimmunity phenotype, inferring that a broad defect in NLR turnover may underlie the severe phenotype observed. Catalytically inactive AtMC1 localizes to punctate structures that are degraded through autophagy. Considering also previous evidence on the proteostatic functions of AtMC1, we speculate that Wt AtMC1 may either directly or indirectly control NLR protein levels, thereby preventing autoimmunity.

Benchmarking SILAC Proteomics Workflows and Data Analysis Platforms

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful metabolic labeling technique with broad applications and various study designs. SILAC proteomics relies on the accurate identification and quantification of all isotopic versions of proteins and peptides during both data acquisition and analysis. However, a comprehensive comparison and evaluation of SILAC data analysis platforms is currently lacking. To address this critical gap and offer practical guidelines for SILAC proteomics data analysis, we designed a comprehensive benchmarking pipeline to evaluate various in vitro SILAC workflows and commonly used data analysis software. Ten different SILAC data analysis workflows using five software packages (MaxQuant, Proteome Discoverer, FragPipe, DIA-NN, and Spectronaut) were evaluated for static and dynamic SILAC labeling with both DDA and DIA methods. For benchmarking, we used both in-house generated and repository SILAC proteomics datasets from HeLa and neuron culture samples. We assessed 12 performance metrics for SILAC proteomics including identification, quantification, accuracy, precision, reproducibility, filtering criteria, missing values, false discovery rate, protein half-life measurement, data completeness, unique software features, and speed of data analysis. Each method/software has its strengths and weaknesses when evaluated for these performance metrics. Most software reaches a dynamic range limit of 100-fold for accurate quantification of light/heavy ratios. We do not recommend using Proteome Discoverer for SILAC DDA analysis despite its wide use in label-free proteomics. To achieve greater confidence in SILAC quantification, researchers could use more than one software packages to analyze the same dataset for cross-validation. In summary, this study offers the first systematic evaluation of various SILAC data analysis platforms, providing practical guidelines to support decision-making in SILAC proteomics study design and data analysis.

Collagen VII Is Associated with Airway Remodeling, Honeycombing, and Fibroblast Foci in Usual Interstitial Pneumonia/Idiopathic Pulmonary Fibrosis

Collagen VII is an essential anchoring protein in the basement membrane zone, maintaining the attachment of stratified and pseudostratified epithelia to the underlying interstitial matrix. However, collagen VII is largely unexplored in normal lungs and idiopathic pulmonary fibrosis (IPF), a disease characterized by excessive accumulation of extracellular matrix and aberrant re-epithelialization of fibrotic lung parenchyma. Analysis of collagen VII mRNA and protein in IPF distal lungs demonstrated elevated levels compared with normal lungs. To investigate its cellular source and spatial distribution in lung tissue, immunohistochemistry, RNAscope in situ hybridization, and cell culture experiments in combination with analysis of public transcriptomic data sets were performed. In IPF lungs, collagen VII was abundant in pathologic remodeled airways and honeycomb cysts, associated with increased basal cell populations. In contrast, in the control lungs, collagen VII was mainly localized in larger airways. RNA sequencing data revealed that epithelial basal cells and keratin 5-/keratin 17+ aberrant basaloid cells are the primary sources of COL7A1 expression. Furthermore, COL7A1 expression was found in mesenchymal subsets, and both collagen VII mRNA and protein were observed in fibroblast foci, another histopathologic feature of IPF. In vitro, COL7A1 expression was found to be increased in normal human lung fibroblasts treated with transforming growth factor-β1. These findings suggest that collagen VII could be involved in the process of abnormal re-epithelialization in lung fibrosis.

Structure-based discovery of highly bioavailable, covalent, broad-spectrum coronavirus MPro inhibitors with potent in vivo efficacy

The main protease (MPro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a validated drug target. Starting with a lead-like dihydrouracil chemotype identified in a large-library docking campaign, we improved MPro inhibition >1000-fold by engaging additional MPro subsites and using a latent electrophile to engage Cys145. Advanced leads from this series show pan-coronavirus antiviral activity, low clearance in mice, and for AVI-4773, a rapid reduction in viral titers >1,000,000 after just three doses. Both compounds are well distributed in mouse tissues, including brain, where concentrations >1000× the 90% effective concentration are observed 8 hours after oral dosing for AVI-4773. AVI-4516 shows minimal inhibition of major cytochrome P450s and human proteases. AVI-4516 also exhibits synergy with the RNA-dependent RNA polymerase inhibitor, molnupiravir, in cellular infection models. Related analogs strongly inhibit nirmatrelvir-resistant MPro mutant virus. The properties of this chemotype are differentiated from existing clinical and preclinical MPro inhibitors and will advance therapeutic development against emerging SARS-CoV-2 variants and other coronaviruses.

Exploring the molecular mechanisms of subarachnoid hemorrhage and potential therapeutic targets: insights from bioinformatics and drug prediction

Subarachnoid hemorrhage (SAH) is a fatal pathological condition in the central nervous system (CNS), characterized by severe clinical consequences. Its treatment remains a significant challenge, especially due to the incomplete understanding of its molecular mechanisms. In this study, we integrated comprehensive bioinformatics analyses with experimental validation to explore the potential pathogenic mechanisms and immune cell infiltration characteristics of SAH, aiming to identify novel diagnostic biomarkers and therapeutic targets. We selected relevant gene expression data from the gene expression omnibus (GEO) database and obtained a gene set associated with SAH from the GeneCards database. Through bioinformatics analysis, we constructed a protein-protein interaction (PPI) network and performed functional enrichment analysis using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) databases. The analysis revealed 11 key genes and indicated 3 main signaling pathways. Additionally, Drug target prediction and molecular docking analyses revealed that Isorhynchophylline (IRN) exhibits a strong binding affinity to these hub proteins. Importantly, Western blot (WB) experiments confirmed that IRN significantly downregulates the expression of CCL20, IL6, TLR4, and MMP9 in LPS-induced microglial cells, validating its anti-inflammatory effects. In conclusion, our findings not only elucidate the molecular mechanisms underlying SAH but also provide robust bioinformatics and experimental evidence supporting IRN as a promising therapeutic candidate, offering novel insights for future intervention strategies in SAH.

Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network

The molecular control of epigenetic information relies on hundreds of proteins of diverse function, which cooperate in defining chromatin structure and DNA methylation landscapes. While many individual pathways have been characterized, how different classes of epigenetic regulators interact to build a resilient epigenetic regulatory network (ERN) remains poorly understood. Here, we show that most individual regulators are dispensable for somatic cell fitness, and that robustness emerges from multiple layers of functional cooperation and degeneracy among network components. By disrupting 200 epigenetic regulator genes, individually or in combination, we generated network-wide maps of functional interactions for representative regulators. We found that paralogues represent only a first layer of functional compensation within the ERN, with intra- or inter-class interactions buffering the effects of perturbation in a gene-specific manner: while CREBBP cooperates with multiple acetyltransferases to form a subnetwork that ensures robust chromatin acetylation, ARID1A interacts with regulators from across all functional classes. When combined with oncogene activation, the accumulated epigenetic disorder exposes a synthetic fragility and broadly sensitizes ARID1A-deficient cells to further perturbation. Our findings reveal homeostatic mechanisms through which the ERN sustains somatic cell fitness and uncover how the network remodels as the epigenome is progressively deregulated in disease.

Algorithms and tools for data-driven omics integration to achieve multilayer biological insights: a narrative review

Systems biology is a holistic approach to biological sciences that combines experimental and computational strategies, aimed at integrating information from different scales of biological processes to unravel pathophysiological mechanisms and behaviours. In this scenario, high-throughput technologies have been playing a major role in providing huge amounts of omics data, whose integration would offer unprecedented possibilities in gaining insights on diseases and identifying potential biomarkers. In the present review, we focus on strategies that have been applied in literature to integrate genomics, transcriptomics, proteomics, and metabolomics in the year range 2018-2024. Integration approaches were divided into three main categories: statistical-based approaches, multivariate methods, and machine learning/artificial intelligence techniques. Among them, statistical approaches (mainly based on correlation) were the ones with a slightly higher prevalence, followed by multivariate approaches, and machine learning techniques. Integrating multiple biological layers has shown great potential in uncovering molecular mechanisms, identifying putative biomarkers, and aid classification, most of the time resulting in better performances when compared to single omics analyses. However, significant challenges remain. The high-throughput nature of omics platforms introduces issues such as variable data quality, missing values, collinearity, and dimensionality. These challenges further increase when combining multiple omics datasets, as the complexity and heterogeneity of the data increase with integration. We report different strategies that have been found in literature to cope with these challenges, but some open issues still remain and should be addressed to disclose the full potential of omics integration.

A general approach for activity-based protein profiling of oxidoreductases with redox-differentiated diarylhalonium warheads

Activity-based protein profiling (ABPP) is a unique proteomic tool for measuring the activity of enzymes in their cellular context, which has been well established for enzyme classes exhibiting a characteristic nucleophilic residue (e.g., hydrolases). In contrast, the enzyme class of oxidoreductases has received less attention, as its members rely mainly on cofactors instead of nucleophilic amino acid residues for catalysis. ABPP probes have been designed for specific oxidoreductase subclasses, which rely on the oxidative conversion of the probes into strong electrophiles. Here we describe the development of ABPP probes for the simultaneous labeling of various subclasses of oxidoreductases. The probe warheads are based on hypervalent diarylhalonium salts, which show unique reactivity as their activation proceeds via a reductive mechanism resulting in aryl radicals leading to covalent labeling of liver proteins at several different amino acids in close proximity to the active sites. The redox potential of the probes can be tuned by isosteric replacement varying the halonium central atom. ABPP experiments with liver using 16 probes differing in warhead, linker, and structure revealed distinct overlapping profiles and broad substrate specificities of several probes. With their capability of multi oxidoreductase subclass labeling - including rare examples for the class of reductases - and their unique design, the herein reported probes offer new opportunities for the investigation of the "oxidoreductome" of microorganisms, plants, animal and human tissues.

Quetzal: Comprehensive Peptide Fragmentation Annotation and Visualization

Proteomics data-dependent acquisition data sets collected with high-resolution mass-spectrometry (MS) can achieve very high-quality results, but nearly every analysis yields results that are thresholded at some accepted false discovery rate, meaning that a substantial number of results are incorrect. For study conclusions that rely on a small number of peptide-spectrum matches being correct, it is thus important to examine at least some crucial spectra to ensure that they are not one of the incorrect identifications. We present Quetzal, a peptide fragment ion spectrum annotation tool to assist researchers in annotating and examining such spectra to ensure that they correctly support study conclusions. We describe how Quetzal annotates spectra using the new Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) mzPAF standard for fragment ion peak annotation, including the Python-based code, a web-service end point that provides annotation services, and a web-based application for annotating spectra and producing publication-quality figures. We illustrate its functionality with several annotated spectra of varying complexity. Quetzal provides easily accessible functionality that can assist in the effort to ensure and demonstrate that crucial spectra support study conclusions. Quetzal is publicly available at https://proteomecentral.proteomexchange.org/quetzal/.

Insights into the transcriptional regulation of CD22 in B cell chronic lymphocytic leukemia

CD22 (also known as Siglec-2) is a member of the Siglec family of glycan-recognition proteins and functions as a negative regulator of the B-cell receptor-mediated calcium signaling. Although the low level of CD22 expression on the B cells in patients with chronic lymphocytic leukemia (CLL) has been documented, CD22's role and its downregulation mechanism in CLL are yet to be fully studied. In this study, we confirmed that the surface CD22 protein and its mRNA are downregulated in the B cells of CLL patients. We analyzed a public transcriptomic dataset and found that the CD22 mRNA level is negatively associated with the prognosis of patients with CLL. To investigate the mechanism of CD22 downregulation, we characterized the minimal promoter of the human CD22 gene required for its transcriptional activation in B cell lines. We employed an unbiased proteomic approach to identify several transcription factors binding to the minimal CD22 promoter, including PU.1, Spi-B, and IRF4. The chromatin immunoprecipitation-quantitative PCR revealed that PU.1 was enriched in a CD22-high cell line, while IRF4 was enriched in a CD22-low cell line. We then conducted overexpression/knockout/knockdown experiments, which validated that PU.1 and Spi-B positively, and IRF4 negatively, regulate CD22 transcription. Our study thus provides insights into the transcriptional regulation of CD22 and the mechanism by which CD22 expression is downregulated in the B cells of patients with CLL.

Proteostasis and lysosomal repair deficits in transdifferentiated neurons of Alzheimer's disease

Ageing is the most prominent risk factor for Alzheimer's disease (AD). However, the cellular mechanisms linking neuronal proteostasis decline to the characteristic aberrant protein deposits in the brains of patients with AD remain elusive. Here we develop transdifferentiated neurons (tNeurons) from human dermal fibroblasts as a neuronal model that retains ageing hallmarks and exhibits AD-linked vulnerabilities. Remarkably, AD tNeurons accumulate proteotoxic deposits, including phospho-tau and amyloid β, resembling those in APP mouse brains and the brains of patients with AD. Quantitative tNeuron proteomics identify ageing- and AD-linked deficits in proteostasis and organelle homeostasis, most notably in endosome-lysosomal components. Lysosomal deficits in aged tNeurons, including constitutive lysosomal damage and ESCRT-mediated lysosomal repair defects, are exacerbated in AD tNeurons and linked to inflammatory cytokine secretion and cell death. Providing support for the centrality of lysosomal deficits in AD, compounds ameliorating lysosomal function reduce amyloid β deposits and cytokine secretion. Thus, the tNeuron model system reveals impaired lysosomal homeostasis as an early event of ageing and AD.

Monitoring Functional Posttranslational Modifications Using a Data-Driven Proteome Informatic Pipeline

Posttranslational modifications (PTMs) are of significant interest in molecular biomedicine due to their crucial role in signal transduction across various cellular and organismal processes. Characterizing PTMs, distinguishing between functional and inert modifications, quantifying their occupancies, and understanding PTM crosstalk are challenging tasks in any biosystem. Studying each PTM often requires a specific, labor-intensive experimental design. Here, we present a PTM-centric proteome informatic pipeline for predicting relevant PTMs in mass spectrometry-based proteomics data without prior information. Once predicted, these in silico identified PTMs can be incorporated into a refined database search and compared to measured data. As a practical application, we demonstrate how this pipeline can be used to study glycoproteomics in oral squamous cell carcinoma based on the proteome profile of primary tumors. Subsequently, we experimentally identified cellular proteins that are differentially expressed in cells treated with multikinase inhibitors dasatinib and staurosporine using mass spectrometry-based proteomics. Computational enrichment analysis was then employed to determine the potential PTMs of differentially expressed proteins induced by both drugs. Finally, we conducted an additional round of database search with the predicted PTMs. Our pipeline successfully analyzed the enriched PTMs, and detected proteins not identified in the initial search. Our findings support the effectiveness of PTM-centric searching of MS data in proteomics based on computational enrichment analysis, and we propose integrating this approach into future proteomics search engines.

The molecular basis of immunosuppression by soluble CD52 is defined by interactions of N-linked and O-linked glycans with HMGB1 box B

Human soluble CD52 is a short glycopeptide comprising 12 amino acids (GQNDTSQTSSPS) which functions as an immune regulator by sequestering the pro-inflammatory high mobility group box protein 1 (HMGB1) and suppressing immune responses. Recombinant CD52 has been shown to act as a broad anti-inflammatory agent, dampening both adaptive and innate immune responses. This short glycopeptide is heavily glycosylated, with a complex sialylated N-linked glycan at N3 and reported O-linked glycosylation possible on several serine and threonine residues. Previously we demonstrated that specific glycosylation features of CD52 are essential for its immunosuppressive function, with terminal α-2,3-linked sialic acids required for binding to the inhibitory SIGLEC-10 receptor leading to T-cell suppression. Using high resolution mass spectrometry, we have further characterized the N- and O-linked glycosylation of Expi293 recombinantly produced CD52 at a glycopeptide and released glycan level, accurately determining glycan heterogeneity of both N- and O-linked glycosylation, and localizing the site of O-glycosylation to T8 with high confidence and direct spectral evidence. This detailed knowledge of CD52 glycosylation informed the construction of a model system, which we analyzed by molecular dynamics simulations to understand the mechanism of recognition and define interactions between bioactive CD52, HMGB1 and the SIGLEC-10 receptor. Our results confirm the essential role of glycosylation, more specifically hyper-sialylation, in the function of CD52, and identify at the atomistic level specific interactions between CD52 glycans and the Box B domain of HMGB1 that determine recognition, and the stability of the CD52/HMGB1 complex. These insights will inform the development of synthetic CD52 as an immunotherapeutic agent.

Exploring the mechanisms of PANoptosis in osteoarthritis and the therapeutic potential of andrographolide through bioinformatics and single-cell analysis

BACKGROUND

Osteoarthritis (OA) is a degenerative joint disease marked by the breakdown of cartilage, where apoptosis plays a key role. Although apoptosis-related genes in OA have been studied, a detailed analysis of PANoptosis-related genes and the search for therapeutic drugs remains limited.

METHODS

We performed a bioinformatics analysis combined with single-cell RNA sequencing to examine PANoptosis-related gene expression in OA cartilage. Key PANoptosis genes and critical cell populations involved in OA progression were identified. Drug prediction led to the selection of Andrographolide (AG), whose effects were validated through molecular docking, Western blotting, and qRT-PCR in chondrocyte models.

RESULTS

Several PANoptosis-related genes, including CASP8, TLR3, CASP1, and IL18, were significantly differentially expressed in OA. These genes are linked to processes such as apoptosis, pyroptosis, and the inflammasome complex. Pathway analysis revealed necroptosis, Toll-like receptor, and apoptosis signaling pathways as important in OA pathology. Single-cell analysis identified HomC, EC, and preHTC as key cell populations. AG was predicted to regulate PANoptosis genes, which was confirmed experimentally, demonstrating AG's potential to modulate key genes involved in cartilage degeneration.

CONCLUSION

This study highlights PANoptosis-related genes in OA and identifies Andrographolide as a promising therapeutic drug, offering new insights into OA treatment strategies.

Regulatory T cells in the mouse hypothalamus control immune activation and ameliorate metabolic impairments in high-calorie environments

The hypothalamus in the central nervous system (CNS) has important functions in controlling systemic metabolism. A calorie-rich diet triggers CNS immune activation, impairing metabolic control and promoting obesity and Type 2 Diabetes (T2D), but the mechanisms driving hypothalamic immune activation remain unclear. Here we identify regulatory T cells (Tregs) as key modulators of hypothalamic immune responses. In mice, calorie-rich environments activate hypothalamic CD4+ T cells, infiltrating macrophages and microglia while reducing hypothalamic Tregs. mRNA profiling of hypothalamic CD4+ T cells reveals a Th1-like activation state, with increased Tbx21, Cxcr3 and Cd226 but decreased Ccr7 and S1pr1. Importantly, results from Treg loss-of function and gain-of-function experiments show that Tregs limit hypothalamic immune activation and reverse metabolic impairments induced by hyper-caloric feeding. Our findings thus help refine the current model of Treg-centered immune-metabolic crosstalk in the brain and may contribute to the development of precision immune modulation for obesity and diabetes.

Development and Validation of a Capillary Electrophoresis Coupled to Mass Spectrometry Pipeline for Comparable Assessment of the Plasma Peptidome

Although capillary electrophoresis coupled to mass spectrometry (CE-MS) holds promise for urinary peptide profiling, only a limited number of studies have used CE-MS to study plasma peptides. Here we describe the establishment of a workflow, including sample preparation, CE-MS analysis, data processing and normalization optimized for the analysis of plasma peptides. Using 291 plasma samples from 136 patients with end stage kidney failure (including pre- and post-dialysis samples) and 20 patients with chronic kidney disease, we identified and quantified the abundance of 3920 unique plasma peptides. The repeatability and intermediate precision of the analysis were high (with a coefficient of variation of 5% on average for all peptides). Six hundred sixty-one out of 3920 peptides were sequenced by CE-MS/MS. These peptide fragments belonged to 135 parent proteins. Using the pipeline, we identified 169 sequenced plasma peptides with different plasma abundance pre- and post-dialysis. These peptides combined in a support vector machine (SVM) classifier successfully discriminated between pre- and post-dialysis samples in a blinded validation cohort of 45 dialysis patients. Enriched peptides post-dialyses were for the major part associated to inflammation and the coagulation contact systems that may serve as signatures for optimizing dialysis materials. In conclusion, this high-throughput strategy focuses on the plasma peptidome, an understudied component of the plasma, as a promising area for further exploration. Due to their close proximity to the vascular bed, plasma peptides hold significant potential to serve as reliable biomarkers for systemic complications associated with kidney disease.

Searching for Sulfotyrosines (sY) in a HA(pY)STACK

Protein sulfation can be crucial in regulating protein-protein interactions but remains largely underexplored. Sulfation is nearly isobaric to phosphorylation, making it particularly challenging to investigate using mass spectrometry. The degree to which tyrosine sulfation (sY) is misidentified as phosphorylation (pY) is, thus, an unresolved concern. This study explores the extent of sY misidentification within the human phosphoproteome by distinguishing between sulfation and phosphorylation based on their mass difference. Using Gaussian mixture models (GMMs), we screened ∼45 M peptide-spectrum matches (PSMs) from the PeptideAtlas human phosphoproteome build for peptidoforms with mass error shifts indicative of sulfation. This analysis pinpointed 104 candidate sulfated peptidoforms, backed up by Gene Ontology (GO) terms and custom terms linked to sulfation. False positive filtering by manual annotation resulted in 31 convincing peptidoforms spanning 7 known and 7 novel sY sites. Y47 in calumenin was particularly intriguing since mass error shifts, acidic motif conservation, and MS2 neutral loss patterns characteristic of sulfation provided strong evidence that this site is sulfated rather than phosphorylated. Overall, although misidentification of sulfation in phosphoproteomics data sets derived from cell and tissue intracellular extracts can occur, it appears relatively rare and should not be considered a substantive confounding factor in high-quality phosphoproteomics data sets.

Cysteine-Directed Isobaric Labeling Combined with GeLC-FAIMS-MS for Quantitative Top-Down Proteomics

The quantification of proteoforms, i.e., all molecular forms in which proteins can be present, by top-down proteomics provides essential insights into biological processes at the molecular level. Isobaric labeling-based quantification strategies are suitable for multidimensional separation strategies and allow for multiplexing of the samples. Here, we investigated cysteine-directed isobaric labeling by iodoTMT in combination with a gel- and gas-phase fractionation (GeLC-FAIMS-MS) for in-depth quantitative proteoform analysis. We optimized the acquisition workflow (i.e., the FAIMS compensation voltages, isolation windows, acquisition strategy, and fragmentation method) using a two-proteome mix to increase the number of quantified proteoforms and reduce ratio compression. Additionally, we implemented a mass feature-based quantification strategy in the widely used deconvolution algorithm FLASHDeconv, which improves and facilitates data analysis. The optimized iodoTMT GeLC-FAIMS-MS workflow was applied to quantitatively analyze the proteome of Escherichia coli grown under glucose or acetate as the sole carbon source, resulting in the identification of 726 differentially abundant proteoforms.

Integration of proteomics profiling data to facilitate discovery of cancer neoantigens: a survey

Cancer neoantigens are peptides that originate from alterations in the genome, transcriptome, or proteome. These peptides can elicit cancer-specific T-cell recognition, making them potential candidates for cancer vaccines. The rapid advancement of proteomics technology holds tremendous potential for identifying these neoantigens. Here, we provided an up-to-date survey about database-based search methods and de novo peptide sequencing approaches in proteomics, and we also compared these methods to recommend reliable analytical tools for neoantigen identification. Unlike previous surveys on mass spectrometry-based neoantigen discovery, this survey summarizes the key advancements in de novo peptide sequencing approaches that utilize artificial intelligence. From a comparative study on a dataset of the HepG2 cell line and nine mixed hepatocellular carcinoma proteomics samples, we demonstrated the potential of proteomics for the identification of cancer neoantigens and conducted comparisons of the existing methods to illustrate their limits. Understanding these limits, we suggested a novel workflow for neoantigen discovery as perspectives.

HSC70 coordinates COP9 signalosome and SCF ubiquitin ligase activity to enable a prompt stress response

The SCF (SKP1/CUL1/F-box protein) ubiquitin ligase complex plays a protective role against external stress, such as ultraviolet irradiation. The emergence of substrates activates SCF through neddylation, the covalent attachment of ubiquitin-like protein NEDD8 to CUL1. After substrate degradation, SCF is inactivated through deneddylation by COP9-signalosome (CSN), a solo enzyme that can deneddylate SCF. How the activity of CSN and SCF is coordinated within the cell is not fully understood. Here, we find that heat-shock cognate 70 (HSC70) chaperone coordinates SCF and CSN activation dependent on the neddylation status and substrate availability. Under basal conditions and low substrate availability, HCS70 directly enhances CSN deneddylation activity, thereby reducing SCF activity. Under SCF-activated conditions, HSC70 interacts with neddylated SCF and enhances its ubiquitination activity. The alternative interaction between HSC70 and CSN or neddylated SCF is regulated by the presence or absence of SCF substrates. The knockdown of HSC70 decreases SCF-mediated substrate ubiquitination, resulting in vulnerability against ultraviolet irradiation. Our work demonstrates the pivotal role of HSC70 in the alternative activation of CSN deneddylation and SCF substrate ubiquitination, which enables a prompt stress response.

DNA damage response regulator ATR licenses PINK1-mediated mitophagy

Defective DNA damage response (DDR) and mitochondrial dysfunction are a major etiology of tissue impairment and aging. Mitochondrial autophagy (mitophagy) is a mitochondrial quality control (MQC) mechanism to selectively eliminate dysfunctional mitochondria. ATR (ataxia-telangiectasia and Rad3-related) is a key DDR regulator playing a pivotal role in DNA replication stress response and genomic stability. Paradoxically, the human Seckel syndrome caused by ATR mutations exhibits premature aging and neuropathies, suggesting a role of ATR in nonreplicating tissues. Here, we report a previously unknown yet direct role of ATR at mitochondria. We find that ATR and PINK1 (PTEN-induced kinase 1) dock at the mitochondrial translocase TOM/TIM complex, where ATR interacts directly with and thereby stabilizes PINK1. ATR deletion silences mitophagy initiation thereby altering oxidative phosphorylation functionality resulting in reactive oxygen species overproduction that attack cytosolic macromolecules, in both cells and brain tissues, prior to nuclear DNA. This study discloses ATR as an integrated component of the PINK1-mediated MQC program to ensure mitochondrial fitness. Together with its DDR function, ATR safeguards mitochondrial and genomic integrity under physiological and genotoxic conditions.

Retina-Targeted 17β-Estradiol by the DHED Prodrug Rescues Visual Function and Actuates Neuroprotective Protein Networks After Optic Nerve Crush in a Rat Model of Surgical Menopause

The association between 17β-estradiol (E2) deprivation, seen in menopause, and a risk for developing glaucoma has been shown. Thus, exogenous supplementation of E2 may protect against retinal ganglion cell (RGC) degradation and vision loss. Here, we investigated the utility of topical 10β,17β-dihydroxyestra-1,4-dien-3-one (DHED), a prodrug of E2 that selectively produces the neuroprotective hormone in the retina, on visual function after optic nerve crush (ONC) and ovariectomy (OVX). We used female Brown Norway rats that underwent either Sham or OVX surgeries. After ONC, OVX animals received DHED or vehicle eye drops for 12 weeks. Visual function, via the optomotor reflex, and retinal thickness, via optical coherence tomography, were followed longitudinally. Afterward, we performed mass spectrometry-based label-free retina proteomics to survey retinal protein interaction networks in our selected animal model and to identify E2-responsive proteins after OVX on neurodegeneration. We found that ONC with OVX caused a significant decline in visual functions that were ameliorated by DHED treatments. Discovery-driven retina proteomics identified numerous proteins associated with neurodegenerative processes due to ONC that were remediated by DHED eye drops. Altogether, our three-pronged phenotypic preclinical evaluation of the topical DHED in the OVX + ONC model of glaucoma reveals the therapeutic potential of the prodrug to prevent visual deficits after glaucomatous retinal injury.

A pan-gene catalogue of Asian cultivated rice

The rice genome underpins fundamental research and breeding, but the Nipponbare (japonica) reference does not fully encompass the genetic diversity of Asian rice. To address this gap, the Rice Population Reference Panel (RPRP) was developed, comprising high-quality assemblies of 16 rice cultivars to represent japonica , indica , aus , and aromatic varietal groups. The RPRP has been consistently annotated, supported by extensive experimental data and here we report the computational assignment, characterization and dissemination of stably identified pan-genes. We identified 25,178 core pan-genes shared across all cultivars, alongside cultivar-specific and family-enriched genes. Core genes exhibit higher gene expression and proteomic evidence, higher confidence protein domains and AlphaFold structures, while cultivar-specific genes were enriched for domains under selective breeding pressure, such as for disease resistance. This resource, integrated into public databases, enables researchers to explore genetic and functional diversity via a population-aware "reference guide" across rice genomes, advancing both basic and applied research.

Safety assessment and exploration of the mechanism of toxic effects of diallyl trisulfide: Based on acute and subacute toxicity and proteomics experiments

ETHNOPHARMACOLOGICAL RELEVANCE

Garlic (Allium sativum L.) is a widely consumed spice and condiment around the world, applied both as a food and as a traditional medicine, and is a natural strengthening agent for the body's circulatory and nervous systems. Diallyl trisulfide (DATS) is the major volatile organosulfur phytochemical found in garlic, with antithrombotic, anticoagulant, and antiplatelet activities as well as antioxidant, anti-infective, and other pharmacological effects. However, the safe dose and the underlying mechanisms of its toxic effects remain elusive.

AIM OF THE STUDY

DATS, an important pharmacologically active compound found in garlic, has garnered attention for its ability to fight cancer, antioxidant, anti-infective, and cardioprotective. The aim of this study was to evaluate the safety of DATS and to elucidate the potential mechanisms of its toxicity.

MATERIALS AND METHODS

In this study, ICR mice were selected for acute and subacute toxicity experiments according to OECD guidelines. The toxicity profile of DATS was analyzed by computer prediction software. Also, key differential proteins in spleen and serum were analyzed by proteomics. The binding stability of DAST to differential proteins was analyzed by molecular docking. Additionally, the regulatory relationship between DATS and differential proteins was verified by Western blot and ELISA experiments.

RESULTS

The results showed that the LD50 value of DATS in acute toxicity was 188.67 mg/kg. In subacute toxicity, water consumption and food intake were reduced in both male and female mice. In addition, the spleen and small intestinal organ coefficients were significantly elevated in male mice at the high dose of DATS; the blood biochemical indices ALB and TP were also significantly elevated. HE staining results showed significant damage to the spleen, liver, small intestine, and kidney of mice at high doses of DATS. Spleen and serum proteomics analyses showed that DATS significantly inhibited ZBP1 expression and upregulated TEC. ADMETlab 2.0 software predictions identified DATS as having potential genotoxicity, dermal sensitization, carcinogenicity, and respiratory and ocular toxicity. Docking results showed that the binding energies between DATS and TEC protein (PDB: 6F3F) and ZBP1 protein (PDB: 4KA4) were -3.7 kcal/mol, -2.4 kcal/mol, respectively. Western blot results showed that DATS-H significantly inhibited the expression of ZBP1 (only in male mice) and Bcl-2 proteins. ELISA results showed that DATS-H significantly increased the level of TEC protein both in male and female mice.

CONCLUSIONS

Long-term administration of high-dose DATS may carry some risk of toxicity. Based on the amount of DATS in garlic, it is recommended that adults should not take more than 359 mg of DATS and 84.5 g of garlic per day. The mechanism of toxicity may be related to the fact that DATS significantly inhibits ZBP1 expression, upregulates TEC, and promotes apoptosis. This study provides valuable toxicological data for the effective evaluation of the long-term toxicity of DATS and offers an additional experimental basis for developing DATS as a healthy food or drug.

Plasticity of the Arabidopsis leaf lipidome and proteome in response to pathogen infection and heat stress

Plants must cope with a variety of stressors during their life cycle, and the adaptive responses to these environmental cues involve all cellular organelles. Among them, comparatively little is known about the contribution of cytosolic lipid droplets (LDs) and their core set of neutral lipids and associated surface proteins to the rewiring of cellular processes in response to stress. Here, we analyzed the changes that occur in the lipidome and proteome of Arabidopsis (Arabidopsis thaliana) leaves after pathogen infection with Botrytis cinerea or Pseudomonas syringae, or after heat stress. Analyses were carried out in wild-type plants and the oil-rich double mutant trigalactosyldiacylglycerol1-1 sugar dependent 1-4 (tgd1-1 sdp1-4) that allowed for an allied study of the LD proteome in stressed leaves. Using liquid chromatography-tandem mass spectrometry-based methods, we showed that a hyperaccumulation of the primary LD core lipid TAG is a general response to stress and that acyl chain and sterol composition are remodeled during cellular adaptation. Likewise, comparative analysis of the LD protein composition in stress-treated leaves highlighted the plasticity of the LD proteome as part of the general stress response. We further identified at least two additional LD-associated proteins, whose localization to LDs in leaves was confirmed by confocal microscopy of fluorescent protein fusions. Taken together, these results highlight LDs as dynamic contributors to the cellular adaptation processes that underlie how plants respond to environmental stress.

A Multiyear Longitudinal Harmonization Study of Quality Controls in Mass Spectrometry Proteomics Core Facilities

Quality control procedures play a pivotal role in ensuring the reliability and consistency of data generated in mass spectrometry-based proteomics laboratories. However, the lack of standardized quality control practices across laboratories poses challenges for data comparability and reproducibility. In response, we conducted a harmonization study within proteomics laboratories of the Core for Life alliance with the aim of establishing a common quality control framework, which facilitates comprehensive quality assessment and identification of potential sources of performance drift. Through collaborative efforts, we developed a consensus quality control standard for longitudinal assessment and adopted common processing software. We generated a 4-year longitudinal data set from multiple instruments and laboratories, which enabled us to assess intra- and interlaboratory variability, to identify causes of performance drift, and to establish community reference values for several quality control parameters. Our study enhances data comparability and reliability and fosters a culture of collaboration and continuous improvement within the proteomics community to ensure the integrity of proteomics data.

Virulence factor discovery identifies associations between the Fic gene family and Fap2+ fusobacteria in colorectal cancer microbiomes

Fusobacterium is a bacterium associated with colorectal cancer (CRC) tumorigenesis, progression, and metastasis. Fap2 is a fusobacteria-specific outer membrane galactose-binding lectin that mediates Fusobacterium adherence to and invasion of CRC tumors. Advances in omics analyses provide an opportunity to profile and identify microbial genomic features that correlate with the cancer-associated bacterial virulence factor Fap2. Here, we analyze genomes of Fusobacterium colon tumor isolates and find that a family of post-translational modification enzymes containing Fic domains is associated with Fap2 positivity in these strains. We demonstrate that Fic family genes expand with the presence of Fap2 in the fusobacterial pangenome. Through comparative genomic analysis, we find that Fap2+ Fusobacteriota are highly enriched with Fic gene families compared to other cancer-associated and human gut microbiome bacterial taxa. Using a global data set of CRC shotgun metagenomes, we show that fusobacterial Fic and Fap2 genes frequently co-occur in the fecal microbiomes of individuals with late-stage CRC. We further characterize specific Fic gene families harbored by Fap2+ Fusobacterium animalis genomes and detect recombination events and elements of horizontal gene transfer via synteny analysis of Fic gene loci. Exposure of a F. animalis strain to a colon adenocarcinoma cell line increases gene expression of fusobacterial Fic and virulence-associated adhesins. Finally, we demonstrate that Fic proteins are synthesized by F. animalis as Fic peptides are detectable in F. animalis monoculture supernatants. Taken together, our study uncovers Fic genes as potential virulence factors in Fap2+ fusobacterial genomes.IMPORTANCEAccumulating data support that bacterial members of the intra-tumoral microbiota critically influence colorectal cancer progression. Yet, relatively little is known about non-adhesin fusobacterial virulence factors that may influence carcinogenesis. Our genomic analysis and expression assays in fusobacteria identify Fic domain-containing genes, well-studied virulence factors in pathogenic bacteria, as potential fusobacterial virulence features. The Fic family proteins that we find are encoded by fusobacteria and expressed by Fusobacterium animalis merit future investigation to assess their roles in colorectal cancer development and progression.

Multi-omics profiling in spinal muscular atrophy (SMA): investigating lipid and metabolic alterations through longitudinal CSF analysis of Nusinersen-treated patients

Spinal muscular atrophy (SMA) is a rare neuromuscular disease caused by biallelic mutations in the SMN1 gene, leading to progressive muscle weakness due to degeneration of the anterior horn cells. Since 2017, SMA patients can be treated with the anti-sense oligonucleotide Nusinersen, which promotes alternative splicing of the SMN2 gene, by regular intrathecal injections. In this prospective study, we applied metabolomic, lipidomic, and proteomic analysis to examine sequential CSF samples from 13 SMA patients and controls. This multi-omic approach identified over 800 proteins and 400 small molecules including lipids. Multivariate analysis of multi-omic data successfully discriminated between the CSF derived from SMA patients and control subjects. Lipidomic analysis revealed increased levels of cholesteryl esters and lyso-phospholipids, along with reduced levels of cholesterol and phospholipids in the CSF of SMA patients as compared to healthy controls. These data, combined with results from functional assays, led us to conclude that SMA patients exhibit altered levels and function of high-density-lipoprotein (HDL)-like particles in the CSF. Notably, Nusinersen therapy was observed to reverse disease-specific profile changes toward a physiological state, potentially explicable by restoring HDL function.

Microflow LC-MS Bottom-Up Proteomics Using 1.5 mm Internal Diameter Columns

Microbore columns with a 1.0 mm inner diameter (i.d.) have gained popularity in microflow liquid chromatography-mass spectrometry (LC-MS) workflows for exploratory proteomics applications due to their high throughput, robustness, and reproducibility. However, obtaining highly efficient separation using these columns remains unachievable, primarily due to significant radial flow heterogeneity caused by uneven particle packing density across the column cross-section. In this study, we evaluated the integration of a 1.5 mm i.d. column, which offers greater packing uniformity and reduced radial flow dispersion, into a microflow LC-MS setup for bottom-up proteomics analysis. The performance of the 1.5 mm i.d. column was compared with that of the 1.0 mm i.d. column using protein samples of varying complexity. The results demonstrate that 1.5 mm i.d. columns provide superior chromatographic separation and better compatibility with conventional-flow LC systems, yielding higher reproducibility and comparable protein and peptide identifications to the 1.0 mm i.d. columns at higher sample amounts. These findings suggest that 1.5 mm i.d. columns could be a suitable alternative to 1.0 mm i.d. columns for microflow LC-MS/MS proteomic analysis, particularly in laboratories with only conventional-flow LC systems.

Quantitative proteome-wide O-glycoproteomics analysis with FragPipe

Identification of O-glycopeptides from tandem mass spectrometry data is complicated by the near complete dissociation of O-glycans from the peptide during collisional activation and by the combinatorial explosion of possible glycoforms when glycans are retained intact in electron-based activation. The recent O-Pair search method provides an elegant solution to these problems, using a collisional activation scan to identify the peptide sequence and total glycan mass, and a follow-up electron-based activation scan to localize the glycosite(s) using a graph-based algorithm in a reduced search space. Our previous O-glycoproteomics methods with MSFragger-Glyco allowed for extremely fast and sensitive identification of O-glycopeptides from collisional activation data but had limited support for site localization of glycans and quantification of glycopeptides. Here, we report an improved pipeline for O-glycoproteomics analysis that provides proteome-wide, site-specific, quantitative results by incorporating the O-Pair method as a module within FragPipe. In addition to improved search speed and sensitivity, we add flexible options for oxonium ion-based filtering of glycans and support for a variety of MS acquisition methods and provide a comparison between all software tools currently capable of O-glycosite localization in proteome-wide searches.

Aged garlic extract enhances the production of β‑defensin 4 via activation of the Wnt/β‑catenin pathway in mouse gingiva

Periodontal disease is recognized as a chronic multifactorial inflammatory condition initiated by dysbiosis within subgingival plaque biofilms. Antimicrobial peptides exhibit a wide spectrum of antimicrobial action, and thus, provide one of the first lines of host defense against oral pathogens. Aged garlic extract (AGE) is effective for preventing the progression of periodontal disease. The present study examined whether AGE affects the production of antimicrobial peptides in mouse gingiva. Reverse transcription-quantitative PCR analysis demonstrated that oral administration of AGE in mice increased the mRNA level of Defb4 in gingival tissue, while the levels of Defb1, Defb14 and Cramp remained unaffected. AGE also upregulated the protein levels of β-defensin 4. To explore the underlying mechanism of the increased β-defensin 4 production induced by AGE, a comprehensive phosphoproteomic analysis in gingival tissues was performed. Proteomic profiling revealed activation of the canonical Wnt/β-catenin pathway in gingiva of mice treated with AGE. Treatment of mouse gingival epithelial GE1 cells with AGE resulted in an increase of β-defensin 4 in the culture medium. In support of proteomics experiments, LF3, a specific inhibitor of Wnt/β-catenin signaling, suppressed the AGE-induced production of β-defensin 4. In addition, β-catenin protein was found to accumulate within the nucleus in cells treated with AGE. In conclusion, the present findings suggested that AGE enhanced the production of β-defensin 4 in mouse gingiva through the canonical Wnt signal transduction pathway.

Comparative Proteomic Analysis of Popcorn Genotypes Identifies Differentially Accumulated Proteins Associated with Resistance Pathways to Southern Leaf Blight Disease

Southern leaf blight (SLB), caused by Bipolaris maydis, poses a significant threat to maize and popcorn production. To understand the molecular mechanisms underlying SLB resistance, we conducted a high-throughput proteomic analysis comparing SLB-resistant (L66) and SLB-susceptible (L51) popcorn genotypes at four and ten days after inoculation (DAI). A total of 717 proteins were identified, with 151 differentially accumulated proteins (DAPs) between the genotypes. Eighteen DAPs exhibited the same regulatory pattern in both the SLB-resistant and SLB-susceptible genotypes at four (R4/S4) and ten (R10/S10) DAI. The protein-protein interaction (PPI) network of differentially accumulated proteins (DAPs) linked to SLB resistance and susceptibility enriched specific metabolic pathways in the SLB response, including photosynthesis, ribosome, ascorbate and aldarate metabolism, glutathione metabolism, and carbon metabolism. Proteins such as photosystem II 11 kD protein (B4FRJ4, PSB27-1), which was up-regulated at both time points (R4/S4 and R10/S10), and 60S acidic ribosomal protein P0 (A0A1D6LEZ7, RPP0B), which was unique to the resistant genotype at both time points (R4 and R10), highlighted the importance of maintaining photosynthetic efficiency and protein synthesis during pathogen attack. Additionally, dehydroascorbate reductase like-3 (B4F817, DHAR3) was consistently up-regulated at both time points in resistant genotypes, emphasizing its role in redox balance and ROS detoxification. In contrast, glyceraldehyde-3-phosphate dehydrogenase (K7UGF5, GAPC2), a glycolytic enzyme, was unique to the susceptible genotype, suggesting its involvement in managing energy metabolism under stress conditions. Our findings suggest that resistance to SLB in popcorn involves a combination of enhanced photosynthetic repair, redox homeostasis, and ribosomal protein activity, providing new potential molecular targets, such as DHAR3 and RPP0B, for genetic improvement in SLB resistance. These results offer valuable insights into breeding programs aimed at developing SLB-resistant popcorn varieties.

Improving the Depth and Reliability of Glycopeptide Identification Using Protein Prospector

Glycosylation is the most common and diverse modification of proteins. It can affect protein function and stability and is associated with many diseases. While proteomic methods to study most post-translational modifications are now quite mature, glycopeptide analysis is still a challenge, particularly from the aspect of data analysis. Several software packages have been developed in the last few years that aim to support omic-level N-linked glycopeptide analysis. This study presents developments of Protein Prospector for the analysis of N-glycopeptide data. Results are compared to other software, showing that Protein Prospector reports many more glycoforms of glycopeptides than competing software. The advantages and disadvantages of considering glycan adducts are also evaluated, showing how considering them can correct previously wrong assignments.

Establishing bio-logging data collections as dynamic archives of animal life on Earth

Rapid growth in bio-logging-the use of animal-borne electronic tags to document the movements, behaviour, physiology and environments of wildlife-offers opportunities to mitigate biodiversity threats and expand digital natural history archives. Here we present a vision to achieve such benefits by accounting for the heterogeneity inherent to bio-logging data and the concerns of those who collect and use them. First, we can enable data integration through standard vocabularies, transfer protocols and aggregation protocols, and drive their wide adoption. Second, we need to develop integrated data collections on standardized data platforms that support data preservation through public archiving and strategies that ensure long-term access. We outline pathways to reach these goals, highlighting the need for resources to govern community data standards and guide data mobilization efforts. We propose the launch of a community-led coordinating body and provide recommendations for how stakeholders-including government data centres, museums and those who fund, permit and publish bio-logging work-can support these efforts.

Structural and Functional Glycosylation of the Abdala COVID-19 Vaccine

Abdala is a COVID-19 vaccine produced in Pichia pastoris and is based on the receptor-binding domain (RBD) of the SARS-CoV-2 spike. Abdala is currently approved for use in multiple countries with clinical trials confirming its safety and efficacy in preventing severe illness and death. Although P. pastoris is used as an expression system for protein-based vaccines, yeast glycosylation remains largely uncharacterised across immunogens. Here, we characterise N-glycan structures and their site of attachment on Abdala and show how yeast-specific glycosylation decreases binding to the ACE2 receptor and a receptor-binding motif (RBM) targeting antibody compared to the equivalent mammalian-derived RBD. Reduced receptor and antibody binding is attributed to changes in conformational dynamics resulting from N-glycosylation. These data highlight the critical importance of glycosylation in vaccine design and demonstrate how individual glycans can influence host interactions and immune recognition via protein structural dynamics.

N-terminomics profiling of host proteins targeted by excretory-secretory proteases of the nematode Angiostrongylus vasorum identifies points of interaction with canine coagulation and complement cascade

The cardiopulmonary nematode Angiostrongylus vasorum can cause severe disease in dogs, including coagulopathies manifesting with bleeding. We analysed A. vasorum excretory/secretory protein (ESP)-treated dog plasma and serum by N-terminome analysis using Terminal Amine Isotopic Labelling of Substrates (TAILS) to identify cleaved host substrates. In plasma and serum samples 430 and 475 dog proteins were identified, respectively. A total of eight dog proteins were significantly cleaved at higher levels upon exposure to A. vasorum ESP: of these, three were coagulation factors (factor II, V and IX) and three were complement proteins (complement C3, C4-A and C5). Comparison with human motif sequence orthologues revealed known cleavage sites in coagulation factor IX and II (prothrombin). These and further identified cleavage sites suggest direct or indirect activation or proteolysis of complement and coagulation components through A. vasorum ESP, which contains several proteases. Further studies are needed to validate their substrate specificity.

Proteostasis and lysosomal repair deficits in transdifferentiated neurons of Alzheimer's disease

Aging is the most prominent risk factor for Alzheimer's disease (AD). However, the cellular mechanisms linking neuronal proteostasis decline to the characteristic aberrant protein deposits in AD brains remain elusive. Here, we develop transdifferentiated neurons (tNeurons) from human dermal fibroblasts as a neuronal model that retains aging hallmarks and exhibits AD-linked vulnerabilities. Remarkably, AD tNeurons accumulate proteotoxic deposits, including phospho-Tau and Aβ, resembling those in AD patient and APP mouse brains. Quantitative tNeuron proteomics identify aging and AD-linked deficits in proteostasis and organelle homeostasis, most notably in endosome-lysosomal components. Lysosomal deficits in aged tNeurons, including constitutive lysosomal damage and ESCRT-mediated lysosomal repair defects, are exacerbated in AD tNeurons and linked to inflammatory cytokine secretion and cell death. Supporting lysosomal deficits' centrality in AD, compounds ameliorating lysosomal function reduce Aβ deposits and cytokine secretion. Thus, the tNeuron model system reveals impaired lysosomal homeostasis as an early event of aging and AD.

jPOST environment accelerates the reuse and reanalysis of public proteome mass spectrometry data

jPOST (https://jpostdb.org/) comprises jPOSTrepo (https://repository.jpostdb.org/) (over 2000 projects), a repository for proteome mass spectrometry data, the reanalysis of raw proteome data based on a standardised protocol using UniScore, and jPOSTdb (https://globe.jpostdb.org/) (over 600 datasets), a database that integrates the reanalysed data. The jPOST reanalysis protocol rescores MS/MS spectra using a new scale, UniScore, to evaluate the extent to which the spectral peaks correspond to the amino acid sequences identified by search engines. However, the metadata registered in the repository database is insufficient for conducting the reanalysis. To address this issue, the Japanese Proteomics Society launched a data journal, the Journal of Proteome Data and Methods (JPDM), which accepts data descriptor articles detailing metadata that can be reanalysed. Within jPOST, raw proteome data is reanalysed based on the metadata described in the JPDM data descriptor articles, utilising UniScore. The reanalysed data is deposited in jPOSTdb, and a link to the JPDM articles is added to jPOSTrepo. These reanalysis accelerations within the jPOST environment will promote FAIR data principles and open science.

The PRIDE database at 20 years: 2025 update

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's leading mass spectrometry (MS)-based proteomics data repository and one of the founding members of the ProteomeXchange consortium. This manuscript summarizes the developments in PRIDE resources and related tools for the last three years. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 534 datasets per month. This has been possible thanks to continuous improvements in infrastructure such as a new file transfer protocol for very large datasets (Globus), a new data resubmission pipeline and an automatic dataset validation process. Additionally, we will highlight novel activities such as the availability of the PRIDE chatbot (based on the use of open-source Large Language Models), and our work to improve support for MS crosslinking datasets. Furthermore, we will describe how we have increased our efforts to reuse, reanalyze and disseminate high-quality proteomics data into added-value resources such as UniProt, Ensembl and Expression Atlas.

Venom proteomics and Duvernoy's venom gland histology of Pseudoboa neuwiedii (Neuwied's false boa; Dipsadidae, Pseudoboini)

The venom of Colombian specimens of the rear-fanged snake Pseudoboa neuwiedii contains proteolytic and phospholipase A2 (PLA2) activities, but is devoid of esterases. Mass spectrometric analysis of electrophoretic bands indicated that this venom contains C-type lectins (CTL), cysteine-rich secretory proteins (CRiSP), PLA2, snake venom metalloproteinases (SVMP), and snake venom matrix metalloproteinases (svMMP). In this investigation, we extended our characterization of P. neuwiedii by undertaking a shotgun proteomic analysis of the venom and comparing the results with a transcriptomic database for Brazilian P. neuwiedii; proteomic data previously obtained by in-gel digestion of electrophoretic bands coupled with mass spectrometry were also reanalyzed by comparing them with the transcriptomic results. The histology of the Duvernoy's venom gland was also examined. Histological analysis revealed a structural organization similar to that of other colubrids that consisted of a serous venom gland and a mucous supralabial gland. When the shotgun proteomic data were run against a general UniProt database for serpents, only metalloproteinases were identified (99% SVMPs, 1% snake endogenous matrix metalloproteinases-9 or seMMP-9). In contrast, when run against a transcriptomic database derived from the venom gland of Brazilian P. neuwiedii that contains predominantly SVMP, CRiSP, type IIE PLA2 (PLA2-IIE), CTL and seMMP-9, the main components identified were seMMP-9 (49%), SVMP (47%), CRiSP (3%) and minor components that included CTL and PLA2-IIE. These findings confirmed the previously reported general composition of P. neuwiedii venom, with metalloproteinases (SVMP and seMMP-9) being the major components, and refined the identification of certain components, e.g., type IIA PLA2 now identified as PLA2-IIE and the detection of seMMP-9 rather than svMMP. The data also indicate compositional similarity between Brazilian and Colombian P. neuwiedii venoms, and stress the need for specific databases for non-front-fanged colubroid snakes to allow accurate and more comprehensive identification of the venom components of these snakes.

Multi-omics profiling reveals altered mitochondrial metabolism in adipose tissue from patients with metabolic dysfunction-associated steatohepatitis

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its more severe form steatohepatitis (MASH) contribute to rising morbidity and mortality rates. The storage of fat in humans is closely associated with these diseases' progression. Thus, adipose tissue metabolic homeostasis could be key in both the onset and progression of MASH.

METHODS

We conducted a case-control observational research using a systems biology-based approach to analyse liver, abdominal subcutaneous adipose tissue (SAT), omental visceral adipose tissue (VAT), and blood of n = 100 patients undergoing bariatric surgery (NCT05554224). MASH was diagnosed through histologic assessment. Whole-slide image analysis, lipidomics, proteomics, and transcriptomics were performed on tissue samples. Lipidomics and proteomics profiles were determined on plasma samples.

FINDINGS

Liver transcriptomics, proteomics, and lipidomics revealed interconnected pathways associated with inflammation, mitochondrial dysfunction, and lipotoxicity in MASH. Paired adipose tissue biopsies had larger adipocyte areas in both fat depots in MASH. Enrichment analyses of proteomics and lipidomics data confirmed the association of liver lesions with mitochondrial dysfunction in VAT. Plasma lipidomics identified candidates with high diagnostic accuracy (AUC = 0.919, 95% CI 0.840-0.979) for screening MASH.

INTERPRETATION

Mitochondrial dysfunction is also present in VAT in patients with obesity-associated MASH. This may cause a disruption in the metabolic equilibrium of lipid processing and storage, which impacts the liver and accelerates detrimental adaptative responses.

FUNDING

The project leading to these results has received funding from 'la Caixa' Foundation (HR21-00430), and from the Instituto de Salud Carlos III (ISCIII) (PI21/00510) and co-funded by the European Union.

Clinical Proteomics Reveals Vulnerabilities in Noninvasive Breast Ductal Carcinoma and Drives Personalized Treatment Strategies

SIGNIFICANCE

This study provides real-world evidence for DCIS, a disease for which currently no molecular tools or biomarkers exist, and gives an unbiased, comprehensive, and deep proteomic profile, identifying >380 actionable targets.

A Review of Protein Inference

Protein inference is an often neglected though crucial step in most proteomic experiments. In the bottom-up proteomic approach, the actual molecules of interest, the proteins, are digested into peptides before measurement on a mass spectrometer. This approach introduces a loss of information: The actual proteins must be inferred based on the identified peptides. While this might seem trivial, there are certain problems, one of the biggest being the presence of peptides that are shared among proteins. These amino acid sequences can, based on the database used for identification, belong to more than one protein. If such peptides are identified in a sample, it cannot be said which proteins actually were in the sample, but only an estimate on the most probable proteins or protein groups can be given based on a predefined inference strategy.Here we describe the effect of the chosen database for peptide identification on the number of shared peptides. Afterward, the mainly used protein inference methods will be sketched, and the necessity of stringent false discovery rate on peptide and protein level is discussed. Finally, we explain how the tool "PIA or protein inference algorithms" can be used together with the workflow environment KNIME and OpenMS to perform protein inference in a common proteomic experiment.