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At least 757 records · Page 42Linked to original sources
PubMed2006

Atmospheric molding of ionic copolymer MALDI-TOF/MS arrays: a new tool for protein identification/profiling.

An atmospheric molding protocol has been used to prepare an ionic methacrylate-based copolymer sample support chips for MALDI (pMALDI)-MS by targeting selected groups of various monomers copolymerized during molding, namely, carboxy, sulfo, dimethylalkyamino, and trimethylalkylammonium groups. The new disposable array chips provide analyte-oriented enhancement of protein adsorption to the modified substrates without requiring complicated surface coating or derivatization. The MALDI-MS performance of the new ionic copolymer chips was evaluated for lysozyme, beta-lactoglobulin A, trypsinogen and carbonic anhydrase I using washing with solutions prepared in pH or ionic strength steps. On cationic chips, the proteins are washed out at pH lower than their p/ values, and on anionic chips at pH higher than their p/ values. The ability of the microfabricated pMALDI chip set to selectively adsorb different proteins from real samples and to significantly increase their MS-signal was documented for the transmembrane photosystem I protein complex from the green alga Chlamydomonas reinhardtii. The proteins were almost exclusively adsorbed according to calculated pI values and grand average of hydropathy (GRAVY) indexes. The new disposable chips reduce manipulation times and increase measurement sensitivity for real-world proteomic samples. The simple atmospheric molding procedure enables additional proteomic operations to be incorporated on disposable MALDI-MS integrated platforms.

Animals↗
PubMed2003

Trypsin digestion of proteins on intact immobilized pH gradient strips for surface matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis.

Isolelectric focusing (IEF) of proteins on immobilized pH gradient (IPG) strips is an integral part of two-dimensional (2D) electrophoresis-based proteomics. Proteins can be effectively analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) on the intact strip itself, leading to the creation of a virtual 2D map giving pI and MW information, bypassing the second dimension SDS-PAGE. Further, trypsin digestion of proteins on the strip can significantly aid the identification of IPG-separated proteins. However, the small size of the peptides leads to diffusion along and outside the gel matrix. In this study, we describe a simple spray-based procedure to perform 'on-strip' trypsin digestion of proteins embedded in IPG strips. Examination of intact myoglobin and its tryptic peptides shows that post-digestion diffusion of tryptic peptides is significantly minimized using this approach.

Amino Acid Sequence↗
PubMed2026

Omics in optic neuropathies: From molecular landscapes to personalized therapeutics.

Optic neuropathies comprise a heterogeneous group of disorders involving transient or permanent injury to retinal ganglion cells (RGCs) and their axons. Clinically, these neurodegenerative conditions manifest as dyschromatopsia, decreased visual acuity, and visual field defects, and in severe cases may ultimately lead to blindness and disability. The marked heterogeneity across disease subtypes, incompletely understood etiologies, and complex pathogenic mechanisms pose substantial challenges to precise diagnosis and effective treatment. Recent advances in omics technologies - including genomics, transcriptomics, proteomics, metabolomics, lipidomics, single-cell and spatial sequencing, and integrative multi-omics approaches - have ushered optic nerve degenerative disease research into an era of high-resolution comprehensive investigation. In this review, we summarize representative applications of omics approaches to elucidate genetic alterations, signaling dysregulation, metabolic reprogramming, and immune responses in optic neuropathies. We further discuss the emerging potential of multi-omics in identifying early diagnostic biomarkers and informing individualized therapeutic strategies. Finally, we provide a forward-looking perspective on the future trajectory of omics technologies and their prospects in both fundamental research and clinical translation, with the overarching aim of accelerating the bench-to-bedside transition in this critical eye disease field.

biomarkers↗
PubMed2025

Using Large Genomic Biobanks to Generate Insights into Genetic Kidney Disease.

Chronic kidney disease (CKD) affects approximately 9% of the global population, leading to increased risks of end-stage kidney disease (ESKD), cardiovascular disease (CVD), and mortality. Patients with CKD are a huge burden on health care resources globally. CKD is a complex condition influenced by a combination of genetic, environmental, and traditional risk factors. Family studies have suggested heritability rates for CKD ranging from 30% to 75%, and large genomic biobank studies have proven essential in identifying genes with substantial effects on CKD risk and in capturing cumulative genetic risk through polygenic risk scores. These biobanks are crucial for discovering new genes associated with kidney health and disease, and their growing size enhances the power to detect novel genetic associations. Integrating multi-omics technologies such as transcriptomics, metabolomics, and proteomics further enriches our understanding of CKD, while advanced computational tools continue to expand our insights into genetic data. Polygenic risk scores, derived from hundreds of genetic variants with small effect sizes, can help identify individuals at high risk of CKD. Genomic biobanks offer valuable opportunities for early identification and personalized treatment of monogenic kidney disorders, such as autosomal dominant polycystic kidney disease and Alport syndrome. These biobanks help fill knowledge gaps, particularly in individuals with milder or asymptomatic presentations who are often underrepresented in traditional studies. Expanding genomic biobank efforts globally, especially in diverse populations, is vital to enhancing our understanding of the genetic underpinnings of kidney disease. This review highlights the significant contributions of genomic biobanks to advancing our comprehension of the genetics of CKD.

Humans↗
PubMed2026

Freezing with Light: Photo-Cross-Linking-Assisted Platform Enables GPCR Deorphanization.

Despite their success as drug targets, nearly one hundred G protein-coupled receptors (GPCRs) remain orphan without identified endogenous ligands. Defining these ligand-receptor pairs constitute a fundamental prerequisite for understanding receptor biology and rational drug discovery. However, deorphanization remains inherently challenging due to the transient and interface-specific ligand-GPCR interactions, especially for endogenous ones that are embedded within chemically complex environments. This In Focus article highlights a modularly designed platform that integrates site-specific photo-cross-linking reaction with proteomics to enable ligand-GPCR pairing directly in native biological contexts. Using this strategy, neuropeptide L-LEN was identified as the endogenous ligand for GPR50, forming a regulatory axis that controls energy expenditure and thermogenesis through brain-peripheral interactions.

Receptors, G-Protein-Coupled↗
PubMedDate not supplied

Genomic messaging system and DNA mark-up language for information-based personalized medicine with clinical and proteome research applications.

The convergence of clinical medicine and the Life Sciences, commencing with opportunities in clinical trials and clinically linked medical research, presents many novel challenges. The Genomic Messaging System (GMS) described here was originally developed as a tool for assembling clinical genomic records of individual and collective patients, and was then generalized to become a flexible workflow component that will link clinical records to a variety of computational biology research tools, for research and ultimately for a more personalized, focused, and preventative healthcare system. Prominent among the applications linked are protein science applications, including the rapid automated modeling of patient proteins with their individual structural polymorphisms. In an initial study, GMS formed the basis of a fully automated system for modeling patient proteins with structural polymorphisms as a basis for drug selection and ultimately design on an individual patient basis.

Clinical Medicine↗
PubMed2004

A subset of human 35S U5 proteins, including Prp19, function prior to catalytic step 1 of splicing.

During catalytic activation of the spliceosome, snRNP remodeling events occur, leading to the formation of a 35S U5 snRNP that contains a large group of proteins, including Prp19 and CDC5, not found in 20S U5 snRNPs. To investigate the function of 35S U5 proteins, we immunoaffinity purified human spliceosomes that had not yet undergone catalytic activation (designated BDeltaU1), which contained U2, U4, U5, and U6, but lacked U1 snRNA. Comparison of the protein compositions of BDeltaU1 and activated B* spliceosomes revealed that, whereas U4/U6 snRNP proteins are stably associated with BDeltaU1 spliceosomes, 35S U5-associated proteins (which are present in B*) are largely absent, suggesting that they are dispensable for complex B formation. Indeed, immunodepletion/complementation experiments demonstrated that a subset of 35S U5 proteins including Prp19, which form a stable heteromeric complex, are required prior to catalytic step 1 of splicing, but not for stable integration of U4/U6.U5 tri-snRNPs. Thus, comparison of the proteomes of spliceosomal complexes at defined stages can provide information as to which proteins function as a group at a particular step of splicing.

Carrier Proteins↗
PubMed2002

Mapping QTLs regulating morpho-physiological traits and yield: case studies, shortcomings and perspectives in drought-stressed maize.

Comparative analysis of a number of studies in drought-stressed maize (Zea mays L.) reporting quantitative trait loci (QTLs) for abscisic acid concentration, root characteristics, other morpho-physiological traits (MPTs) and grain yield (GY) reveals their complex genetic basis and the influence of the genetic background and the environment on QTL effects. Chromosome regions (e.g. near umc11 on chromosome 1 and near csu133 on chromosome 2) with QTLs controlling a number of MPTs and GY across populations and conditions of different water supply have been identified. Examples are presented on the use of QTL information to elucidate the genetic and physiological bases of the association among MPTs and GY. The QTL approach allows us to develop hypotheses accounting for these associations which can be further tested by developing near isogenic lines (NILs) differing for the QTL alleles. NILs also allow for a more accurate assessment of the breeding value of MPTs and, in some cases, may allow for the map-based cloning of the gene(s) underlying the QTL. Although QTL analysis is still time-consuming and resource-demanding, its integration with genomics and post-genomics approaches (e.g. transcriptome, proteome and metabolome analyses) will play an increasingly important role for the identification and validation of candidate genes affecting MPTs and GY.

Abscisic Acid↗
PubMed2006

The Universal Protein Resource (UniProt): an expanding universe of protein information.

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at http://www.uniprot.org or downloaded at ftp://ftp.uniprot.org/pub/databases/.

Databases, Protein↗
PubMed2005

AnoBase: a genetic and biological database of anophelines.

AnoBase (http://www.anobase.org) is an integrated, relational database of basic biological and genetic data on anopheline species, with a particular emphasis on Anopheles gambiae. It has been designed as an information source and research support tool for the broad vector biology community. Although AnoBase is not a primary genomic database that develops and provides tools to access the genome of the malaria mosquito, it nevertheless contains several sections that offer data of genomic interest such as in situ hybridization images, an integrated gene tool and direct online access to AnoXcel, the proteomic database of An. gambiae. Moreover, AnoBase also contains information on non-gambiae mosquito species and a novel section on studies related to insecticide resistance.

Animals↗
PubMed2004

Computational physiology and the Physiome Project.

Bioengineering analyses of physiological systems use the computational solution of physical conservation laws on anatomically detailed geometric models to understand the physiological function of intact organs in terms of the properties and behaviour of the cells and tissues within the organ. By linking behaviour in a quantitative, mathematically defined sense across multiple scales of biological organization--from proteins to cells, tissues, organs and organ systems--these methods have the potential to link patient-specific knowledge at the two ends of these spatial scales. A genetic profile linked to cardiac ion channel mutations, for example, can be interpreted in relation to body surface ECG measurements via a mathematical model of the heart and torso, which includes the spatial distribution of cardiac ion channels throughout the myocardium and the individual kinetics for each of the approximately 50 types of ion channel, exchanger or pump known to be present in the heart. Similarly, linking molecular defects such as mutations of chloride ion channels in lung epithelial cells to the integrated function of the intact lung requires models that include the detailed anatomy of the lungs, the physics of air flow, blood flow and gas exchange, together with the large deformation mechanics of breathing. Organizing this large body of knowledge into a coherent framework for modelling requires the development of ontologies, markup languages for encoding models, and web-accessible distributed databases. In this article we review the state of the field at all the relevant levels, and the tools that are being developed to tackle such complexity. Integrative physiology is central to the interpretation of genomic and proteomic data, and is becoming a highly quantitative, computer-intensive discipline.

Biophysical Phenomena↗
PubMed2026

Multimodal Analysis Reveals Aberrant Expression of SUMO2 and Its Significant Association With Key Mechanisms of Metabolic Pathways in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. However, the role of small ubiquitin-like modifier 2 (SUMO2), a core member of the small ubiquitin-like modifier (SUMO) family, regarding its expression patterns and metabolism-related functions in HCC remains inadequately understood. METHODS: A multidimensional analytical framework was applied, integrating immunohistochemistry (153 HCC vs. 21 non-HCC samples), proteomics (159 paired samples), bulk transcriptomics (3240 HCC vs. 2267 non-HCC samples), single-cell RNA sequencing (RNA-seq) (10 HCC vs. 8 non-HCC samples), spatial transcriptomics, and external CRISPR/Cas9 functional genomics data. Systematic analyses included standardized mean difference (SMD), pathway enrichment, pseudotime trajectory inference, in silico knockout, cell-cell communication, metabolic flux scoring, immune infiltration, clinical correlation, drug sensitivity prediction, and molecular docking. RESULTS: At the protein level, immunohistochemistry (nuclear positivity) and external proteomic data collectively demonstrated consistent SUMO2 overexpression in HCC. Consistent upregulation was also observed at the mRNA level across large-scale cohorts. Single-cell RNA-seq and spatial transcriptomics localized SUMO2 enrichment to malignant hepatocytes and tumor-dominant regions. CRISPR-mediated SUMO2 knockout suppressed proliferation in multiple HCC cell lines. Mechanistically, high SUMO2 expression was significantly associated with metabolic reprogramming involving glycolysis/gluconeogenesis, pyruvate metabolism, and the tricarboxylic acid cycle. SUMO2-high malignant hepatocyte subpopulations exhibited enhanced activity of the macrophage migration inhibitory factor signaling axis and enhanced iron-sensor interactions. Further, the immune infiltration analysis revealed a negative correlation between SUMO2 expression and M1 macrophages and a positive correlation between follicular helper T cells and regulatory T cells. Clinically, elevated SUMO2 levels were found to be associated with adverse prognostic features. Furthermore, high SUMO2 expression was associated with increased sensitivity to dasatinib, and molecular docking simulations predicted potential binding between SUMO2 and dasatinib, with a Vina score of -8.5 kcal/mol. CONCLUSIONS: SUMO2 is aberrantly expressed at the protein, mRNA, single-cell, and spatial transcriptomic levels in HCC and is significantly associated with metabolic reprogramming and altered migration inhibitory factor (MIF)-mediated intercellular communication, suggesting its potential as a novel biomarker for diagnosis and treatment.

Humans↗
PubMed2002

Proteolytic enzymes as therapeutic targets - Keystone Symposium. 3-8 February 2002, Keystone, CO, USA.

The Keystone Symposium 'Proteolytic Enzymes as Therapeutic Targets' was attended by approximately 150 scientists. Around two-thirds of the participants consisted of representatives from pharmaceutical companies, but representatives from academic institutes dominated the list of speakers. The meeting attracted scientists from many different fields, including biochemistry, molecular biology, structural biology, pharmacology, chemistry, and bioinformatics. The science ranged from the discovery and characterization of novel proteinases to the development and clinical trials of proteinase inhibitors and was presented as posters or in oral sessions. The discussions following the oral presentations were always very animated, but hardly ever heated. Although there were a few new drugs being presented, the real highlight was the enormous potential of recently discovered proteinases as new therapeutic targets. Both pharmaceutical companies and academic institutes are investing in programs to integrate the avalanche of new information coming from functional genomics, proteomics and structural information to create a platform for applied proteinase technology.

Journal Article↗
PubMed2004

WormBase as an integrated platform for the C. elegans ORFeome.

The ORFeome project has validated and corrected a large number of predicted gene models in the nematode C. elegans, and has provided an enormous resource for proteome-scale studies. To make the resource useful to the research and teaching community, it needs to be integrated with other large-scale data sets, including the C. elegans genome, cell lineage, neurological wiring diagram, transcriptome, and gene expression map. This integration is also critical because the ORFeome data sets, like other 'omics' data sets, have significant false-positive and false-negative rates, and comparison to related data is necessary to make confidence judgments in any given data point. WormBase, the central data repository for information about C. elegans and related nematodes, provides such a platform for integration. In this report, we will describe how C. elegans ORFeome data are deposited in the database, how they are used to correct gene models, how they are integrated and displayed in the context of other data sets at the WormBase Web site, and how WormBase establishes connection with the reagent-based resources at the ORFeome project Web site.

Animals↗
PubMedDate not supplied

Large-scale identification of Caenorhabditis elegans proteins by multidimensional liquid chromatography-tandem mass spectrometry.

A proteome of a model organism, Caenorhabditis elegans, was analyzed by an integrated liquid chromatography (LC)-based protein identification system, which was constructed by microscale two-dimensional liquid chromatography (2DLC) coupled with electrospray ionization (ESI) tandem mass spectrometry (MS/MS) on a high-resolution hybrid mass spectrometer with an automated data analysis system. Soluble and insoluble protein fractions were prepared from a mixed growth phase culture of the worm C. elegans, digested with trypsin, and fractionated separately on the 2DLC system. The separated peptides were directly analyzed by on-line ESI-MS/MS in a data-dependent mode, and the resultant spectral data were automatically processed to search a genome sequence database, wormpep 66, for protein identification. The total number of proteins of the composite proteome identified in this method was 1,616, including 110 secreted/targeted proteins and 242 transmembrane proteins. The codon adaptation indices of the identified proteins suggested that the system could identify proteins of relatively low abundance, which are difficult to identify by conventional 2D-gel electrophoresis (GE) followed by an offline mass spectrometric analysis such as peptide mass fingerprinting. Among the approximately 5,400 peptides assigned in this study, many peptides with post-translational modifications, such as N-terminal acetylation and phosphorylation, were detected. This expression profile of C. elegans, containing 571 hypothetical gene products, will serve as the basic data of a major proteome set expressed in the worm.

Animals↗
PubMed2026

Quantitative interactome mapping of skeletal muscle insulin resistance.

Protein-protein interactions (PPIs) are dynamic and critical to adaptive homeostasis. While there have been massive efforts to catalogue proteome-wide PPIs, global quantification of changes remains a challenge. Here, we integrate dynamic protein correlation profiling - mass spectrometry (PCP-MS) and quantitative cross linking-mass spectrometry (qXL-MS) using multiplexed stable isotope labelling to characterise global PPI remodelling following the development of chronic skeletal muscle insulin resistance (IR) with or without acute insulin stimulation. We quantify >7,000 unique PPIs amongst 5,346 proteins and show changes in the interactome network dominate the proteome response. Our data show the dysregulation of protein processing in the endoplasmic/sarcoplasmic reticulum involving changes in PPIs with protein chaperones and disulfide isomerases is a major hallmark of skeletal muscle IR. Mechanistically, we show the dysregulation of PPIs with Protein-Disulfide Isomerase 6 (PDIA6) regulates cysteine oxidation and insulin sensitivity. Taken together, we show in vivo quantitative interactome mapping is a powerful approach to understand disease mechanisms and provide new insights into protein network re-organisations with IR.

Insulin Resistance↗
PubMed2005

Towards building the silicon cell: a modular approach.

Systems Biology aims to understand quantitatively how properties of biological systems can be understood as functions of the characteristics of, and interactions between their macromolecular components. Whereas, traditional biochemistry focused on isolation and characterization of cellular components, the challenge for Systems Biology lies in integration of this knowledge and the knowledge about molecular interactions. Computer models play an important role in this integration. We here discuss an approach with which we aim to link kinetic models on small parts of metabolism together, so as to form detailed kinetic models of larger chunks of metabolism, and ultimately of the entire living cell. Specifically, we will discuss techniques that can be used to model a sub-network in isolation of a larger network of which it is a part, while still maintaining the dynamics of the larger complete network. We will start by outlining the JWS online system, the silicon cell project, and the type of models we propose. JWS online is a model repository, which can be used for the storage, simulation and analysis of kinetic models. We advocate to integrate a top-down approach, where measurements on the complete system are used to derive fluxes in a detailed structural model, with a bottom-up approach, consisting of the integration of molecular mechanism-based detailed kinetic models into the structural model.

Animals↗