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PubMedDate not supplied

The normal human amniotic fluid supernatant proteome.

Proteomic analysis combining two-dimentional electrophoresis (2DE) and mass spectrometry (MS) has the potential for a wide range of applications in biological and medical sciences, as protein screening in tissues obtained from healthy and diseased conditions can determine drug targets and diagnostic markers. Conventionally, amniotic fluid (AF) samples are routinely used for prenatal diagnosis of a wide range of fetal abnormalities. Proteomics have already been applied in the analysis of tissues from fetuses with Down's syndrome, in order to detect differences in their protein profile as compared to the normal profiles and to determine possible diagnostic tools. A detailed protein 2DE for the normal human AF has not been reported. In the present study, the 2D protein database of the normal human AF supernatant (AFS) was constructed. Ten AFS samples from women carrying normal fetuses were analysed by 2DE. A mean of 412 spots per gel were analyzed and protein identification was carried out by MALDI-MS and MALDI-MS-MS. A 2D protein map comprising of 136 different gene products was constructed. The majority of the identified proteins are regulatory proteins, enzymes, secreted proteins, carriers and immunoglobulins. Twelve hypothetical proteins were also included. The normal AFS proteome map is a valuable tool for the study of aberrant protein expression and the search for proteins as possible markers for the prediction of abnormal fetuses.

Amniotic Fluid↗

PubMed2000

Antimalarial drug development and new targets.

The Molecular Approaches to Malaria (MAM2000) conference, Lorne, Australia, 2-5 February 2000, brought together world-class malaria research scientists. The development of new tools and technologies - transfection, DNA microarrays and proteomic analysis - and the availability of DNA sequences generated by the Malaria Genome Project, along with more classic approaches, have facilitated the identification of novel drug targets, the development of new antimalarials and the generation of a deeper understanding of the molecular mechanism(s) of drug resistance in malaria. It is hoped that combinations of these technologies could lead to strategies that enable the development of effective, efficient and affordable new drugs to overcome drug-resistant malaria, as discussed at MAM2000 and outlined here by Ian Macreadie and colleagues.

Animals↗

PubMed2025

How Does Tendon Region, Donor, and the Presence of Disease Affect Protein Composition of the Achilles Tendon?

BACKGROUND: Response to treatment for tendinopathy is variable, which may reflect variability in underlying etiology and capacity for the tendon to respond to treatment. Understanding variability in tendon protein composition may help improve our understanding of the mechanistic underpinnings of painful tendon degeneration and inform treatment targets. QUESTIONS/PURPOSES: (1) What factors (tendon region, individual characteristics, presence of disease) contribute to protein compositional (proteomic) and structural variation in human Achilles tendons? (2) What compositional changes characterize tendinopathy, and what protein interactions might contribute to tendon degeneration? (3) How does diabetes influence tendon composition, and what mechanisms might underlie tendon dysfunction in individuals with diabetes? METHODS: In this exploratory, cross-sectional study, human Achilles tendon specimens were obtained from individuals with (diabetes group, n = 5) or without diabetes (control group, n = 5) undergoing lower extremity amputation and from individuals undergoing tendon debridement surgeries for tendinopathy (tendinopathy group, n = 8). Specimens were collected between 2019 and 2023. Protein abundances were quantified and analyzed using mass spectrometry, hierarchical clustering, and principal component analysis. To evaluate the role of tendon region and donor on tendon protein compositional variability, we assessed proteomic differences between three regions in nontendinopathic tendons from three individuals. To identify the contribution of disease (that is, presence of tendinopathy or diabetes) on protein composition, we compared tendons from the tendinopathy (n = 8 [2 males, 6 females], mean ± SD age 48 ± 11 years), diabetes (n = 5 [3 males, 2 females], age 54 ± 9 years), and control (n = 5 [3 males, 2 females], age 42 ± 12 years) groups. Proteomic differences associated with tendinopathy and diabetes were further examined using functional enrichment and protein-protein interaction network analysis. RESULTS: Variability in tendon protein composition was primarily from presence of disease, followed by donor and then tendon region. Protein composition distinguished tendons with tendinopathy from controls, with 311 proteins differentially expressed (152 overexpressed and 159 underexpressed; fold change ≥ 1.5, p < 0.05) and higher Bonar scores indicating greater degeneration (mean ± SD Bonar score tendinopathy group 8.6 ± 1.2 versus control group 2.1 ± 0.7; p = 0.01). Pathway analysis identified dysregulation in extracellular matrix remodeling (TIMP1, MMP3, MMP10), inflammatory response (TNF-α, EGFR1), and metabolic reprogramming. Tendons from individuals with diabetes exhibited minimal proteomic changes compared with the control group, with 66 differentially expressed proteins (31 overexpressed and 35 underexpressed; fold change ≥ 1.5, p < 0.05) with no histopathologic differences between diabetes and control group tendons (mean ± SD Bonar score diabetes group 3.4 ± 1.0 versus control group 2.1 ± 0.7; p = 0.19). Tendons in the diabetes group showed reductions in Type I collagen, enrichment of pathways associated with fibrosis and metabolic dysfunction, and inflammatory pathways associated with α 6 β 4 integrin. CONCLUSION: Our findings indicate that Achilles tendon composition primarily differs based on disease etiology, with tendinopathy showing extensive extracellular matrix disruption and inflammatory activity, whereas tendons from individuals with diabetes exhibit more subtle compositional changes. This distinction suggests that tendinopathy may require targeted interventions addressing tissue remodeling and inflammation, whereas diabetes may predispose tendons to injury but not directly result in degeneration. Understanding these protein compositional variations can help refine hypotheses about disease progression, treatment response, and potential therapeutic targets. CLINICAL RELEVANCE: While proteomic analysis is not currently a part of routine clinical assessment, these findings provide a framework for identifying protein markers that may aid in early diagnosis or patient stratification to improve treatment alignment. Future studies could determine whether these proteomic changes correlate with treatment response and further inform our understanding of early-stage degeneration from chronic disease. By bridging molecular findings with clinical presentation, this study lays the groundwork for future research on precision medicine approaches for tendon disorders, with the long-term goal of tailoring treatment based on both biological and symptomatic characteristics.

Humans↗

PubMed2003

High-throughput proteomic analysis of human infiltrating ductal carcinoma of the breast.

Large-scale proteomics will play a critical role in the rapid display, identification and validation of new protein targets, and elucidation of the underlying molecular events that are associated with disease development, progression and severity. However, because the proteome of most organisms are significantly more complex than the genome, the comprehensive analysis of protein expression changes will require an analytical effort beyond the capacity of standard laboratory equipment. We describe the first high-throughput proteomic analysis of human breast infiltrating ductal carcinoma (IDCA) using OCT (optimal cutting temperature) embedded biopsies, two-dimensional difference gel electrophoresis (2-D DIGE) technology and a fully automated spot handling workstation. Total proteins from four breast IDCAs (Stage I, IIA, IIB and IIIA) were individually compared to protein from non-neoplastic tissue obtained from a female donor with no personal or family history of breast cancer. We detected differences in protein abundance that ranged from 14.8% in stage I IDCA versus normal, to 30.6% in stage IIB IDCA versus normal. A total of 524 proteins that showed > or = three-fold difference in abundance between IDCA and normal tissue were picked, processed and identified by mass spectrometry. Out of the proteins picked, approximately 80% were unambiguously assigned identities by matrix-assisted laser desorbtion/ionization-time of flight mass spectrometry or liquid chromatography-tandem mass spectrometry in the first pass. Bioinformatics tools were also used to mine databases to determine if the identified proteins are involved in important pathways and/or interact with other proteins. Gelsolin, vinculin, lumican, alpha-1-antitrypsin, heat shock protein-60, cytokeratin-18, transferrin, enolase-1 and beta-actin, showed differential abundance between IDCA and normal tissue, but the trend was not consistent in all samples. Out of the proteins with database hits, only heat shock protein-70 (more abundant) and peroxiredoxin-2 (less abundant) displayed the same trend in all the IDCAs examined. This preliminary study demonstrates quantitative and qualitative differences in protein abundance between breast IDCAs and reveals 2-D DIGE portraits that may be a reflection of the histological and pathological status of breast IDCA.

Adult↗

PubMed2006

Novel gene and gene model detection using a whole genome open reading frame analysis in proteomics.

BACKGROUND: Defining the location of genes and the precise nature of gene products remains a fundamental challenge in genome annotation. Interrogating tandem mass spectrometry data using genomic sequence provides an unbiased method to identify novel translation products. A six-frame translation of the entire human genome was used as the query database to search for novel blood proteins in the data from the Human Proteome Organization Plasma Proteome Project. Because this target database is orders of magnitude larger than the databases traditionally employed in tandem mass spectra analysis, careful attention to significance testing is required. Confidence of identification is assessed using our previously described Poisson statistic, which estimates the significance of multi-peptide identifications incorporating the length of the matching sequence, number of spectra searched and size of the target sequence database. RESULTS: Applying a false discovery rate threshold of 0.05, we identified 282 significant open reading frames, each containing two or more peptide matches. There were 627 novel peptides associated with these open reading frames that mapped to a unique genomic coordinate placed within the start/stop points of previously annotated genes. These peptides matched 1,110 distinct tandem MS spectra. Peptides fell into four categories based upon where their genomic coordinates placed them relative to annotated exons within the parent gene. CONCLUSION: This work provides evidence for novel alternative splice variants in many previously annotated genes. These findings suggest that annotation of the genome is not yet complete and that proteomics has the potential to further add to our understanding of gene structures.

Alternative Splicing↗

PubMed2006

Proteomic analysis of secreted proteins in early rheumatoid arthritis: anti-citrulline autoreactivity is associated with up regulation of proinflammatory cytokines.

OBJECTIVES: To identify peripheral blood autoantibody and cytokine profiles that characterise clinically relevant subgroups of patients with early rheumatoid arthritis using arthritis antigen microarrays and a multiplex cytokine assay. METHODS: Serum samples from 56 patients with a diagnosis of rheumatoid arthritis of <6 months' duration were tested. Cytokine profiles were also determined in samples from patients with psoriatic arthritis (PsA) and ankylosing spondylitis (n = 21), and from healthy individuals (n = 19). Data were analysed using Kruskal-Wallis test with Dunn's adjustment for multiple comparisons, linear correlation tests, significance analysis of microarrays (SAM) and hierarchical clustering software. RESULTS: Distinct antibody profiles were associated with subgroups of patients who exhibited high serum levels of tumour necrosis factor (TNF)alpha, interleukin (IL)1beta, IL6, IL13, IL15 and granulocyte macrophage colony-stimulating factor. Significantly increased autoantibody reactivity against citrullinated epitopes was observed in patients within the cytokine "high" subgroup. Increased levels of TNFalpha, IL1alpha, IL12p40 and IL13, and the chemokines eotaxin/CCL11, monocyte chemoattractant protein-1 and interferon-inducible protein 10, were present in early rheumatoid arthritis as compared with controls (p<0.001). Chemokines showed some of the most impressive differences. Only IL8/CXCL8 concentrations were higher in patients with PsA/ankylosing spondylitis (p = 0.02). CONCLUSIONS: Increased blood levels of proinflammatory cytokines are associated with autoantibody targeting of citrullinated antigens and surrogate markers of disease activity in patients with early rheumatoid arthritis. Proteomic analysis of serum autoantibodies, cytokines and chemokines enables stratification of patients with early rheumatoid arthritis into molecular subgroups.

Adult↗

PubMed2005

Building the mitochondrial proteome.

Mitochondria are essential organelles for cellular homeostasis. A variety of pathologies including cancer, myopathies, diabetes, obesity, aging and neurodegenerative diseases are linked to mitochondrial dysfunction. Therefore, mapping the different components of mitochondria is of particular interest to gain further understanding of such diseases. In recent years, proteomics-based approaches have been developed in attempts to determine the complete set of mitochondrial proteins in yeast, plants and mammals. In addition, proteomics-based methods have been applied not only to the analysis of protein function in the organelle, but also to identify biomarkers for diagnosis and therapeutic targets of specific pathologies associated with mitochondria. Altogether, it is becoming clear that proteomics is a powerful tool not only to identify currently unknown components of the mitochondrion, but also to study the different roles of the organelle in cellular homeostasis.

Animals↗

PubMed2002

Proteomic analysis of cytokine induced proteins in human intestinal epithelial cells: implications for inflammatory bowel diseases.

A role for cytokine regulated proteins in epithelial cells has been suggested in the pathogenesis of inflammatory bowel diseases (IBD). The aim of this study was to identify such cytokine regulated targets using a proteomic functional approach. Protein patterns from (35)S-radiolabeled homogenates of cultured colon epithelial cells were compared before and after exposure to interferon-gamma, interleukin-1beta and interleukin-6. Proteins were separated by two-dimensional polyacrylamide gel electrophoresis. Both autoradiographies and silver stained gels were analyzed. Proteins showing differential expression were identified by tryptic in-gel digestion and mass spectrometry. Metabolism related proteins were also investigated by Western blot analysis. Tryptophanyl-tRNA synthetase, indoleamine-2,3-dioxygenase, heterogeneous nuclear ribonucleoprotein JKTBP, interferon-induced 35kDa protein, proteasome subunit LMP2 and arginosuccinate synthetase were identified as cytokine modulated proteins in vitro. Using purified epithelial cells from patients, overexpression of indoleamine-2,3-dioxygenase, an enzyme involved in tryptophan metabolism, was confirmed in Crohn's disease as well as in ulcerative colitis, as compared to normal mucosa. No such difference was found in diverticulitis. Potentially, this observation opens new avenues in the treatment of IBD.

Argininosuccinate Synthase↗

PubMed2005

Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy.

Mapping tumor cell protein networks in vivo will be critical for realizing the promise of patient-tailored molecular therapy. Cancer can be defined as a dysregulation or hyperactivity in the network of intracellular and extracellular signaling cascades. These protein signaling circuits are the ultimate targets of molecular therapy. Each patient's tumor may be driven by a distinct series of molecular pathogenic defects. Thus, for any single molecular targeted therapy, only a subset of cancer patients may respond. Individualization of therapy, which tailors a therapeutic regimen to a tumor molecular portrait, may be the solution to this dilemma. Until recently, the field lacked the technology for molecular profiling at the genomic and proteomic level. Emerging proteomic technology, used concomitantly with genomic analysis, promises to meet this need and bring to reality the clinical adoption of molecular stratification. The activation state of kinase-driven signal networks contains important information relative to cancer pathogenesis and therapeutic target selection. Proteomic technology offers a means to quantify the state of kinase pathways, and provides post-translational phosphorylation data not obtainable by gene arrays. Case studies using clinical research specimens are provided to show the feasibility of generating the critical information needed to individualize therapy. Such technology can reveal potential new pathway interconnections, including differences between primary and metastatic lesions. We provide a vision for individualized combinatorial therapy based on proteomic mapping of phosphorylation end points in clinical tissue material.

Antineoplastic Combined Chemotherapy Protocols↗

PubMedDate not supplied

[Proteomics and autoantibody].

Autoimmune response is diverse. This diversity is thought not to take place at the beginning of the autoimmune process but to occur as the disease evolves. It is mainly the consequence of the so-called epitope-spreading phenomenon and of the cross-reactivity of antibodies. Analysing autoantibody repertoire constitutes a powerful means to understand physiopathological processes at work in various diseases, mainly autoimmune diseases. In particular this analysis opens the way to precisely identify autoantigens and their changes in various pathological situations, and allows providing new biological markers in chronic inflammatory diseases. New methodologies have recently emerged for the analysis of the autoantibody repertoire in a given individual. They propose diagnostic approaches no more related upon few markers but founded upon analysis of global changes of the antibody repertoire. They belong to methodologies called target-oriented proteomics. Their common feature is to isolate autoantigens by means of affinity chromatography based upon antibody/antigen reactions. Autoantibodies to be studied interact with a protein substratum susceptible to include autoantibody targets. These interactions take place on solid macro- or microsurfaces, i.e. membrane filters or chips. Several strategies can be used for locating the specific autoantibody/autoantigen complexes and for identifying behind autoantigens. In this paper three approaches, namely, the recombinant protein chips, the SELDI techniques and the 2-D gel electrophoresis linked to mass spectrometry are described and compared.

Autoantibodies↗

PubMed2006

Proteomic analysis of the autoantibody response following immunization with a single autoantigen.

In most autoimmune diseases, the autoantibody response is directed against several antigens of the target organ whose identification is crucial for understanding the physiopathological process. Thus, technologies allowing a characterization of the whole autoantibody pattern of both human and experimental autoimmune diseases are required. Here we have used immunoproteomic analysis of human epidermal extracts to characterize the diversity of the anti-desmosome antibody response induced in normal mice immunized with desmoglein 1, the major autoantigen of pemphigus foliaceus, an autoimmune blistering skin disease. In particular, this analysis enables us to characterize the binding properties of anti-desmosome mAbs derived from these mice and to show that the autoantibody response induced upon immunization with a single autoantigen targets different epidermal autoantigens with a pattern similar to that observed in certain variety of human pemphigus.

Amino Acid Sequence↗

PubMed2006

Proteomic analysis of malignant ovarian cancer effusions as a tool for biologic and prognostic profiling.

PURPOSE: Malignant epithelial ovarian cancer effusions are important in disease dissemination and clinical outcome. The identification of biochemical events active in effusions may improve our identification and application of targeted therapeutics. EXPERIMENTAL DESIGN: Archival effusion samples for which outcome information was known were studied. Clinical variables were comparable between these groups. Two cohorts of patients with malignant effusion were assessed: those with effusion at presentation (Tap1) or at first recurrence (Tap2). Expression and activated fraction of selected signaling proteins were quantitated on serial protein microarrays using validated antibodies. Proteomic results and clinical variables were analyzed by univariate analysis followed by Cox proportional hazards model analysis. RESULTS: Malignant effusions (>80% malignant cells) were distinguished from benign effusions by higher expression of AKT, activated extracellular signal-regulated kinase, activated (P < or = 0.001) and total cAMP-responsive element binding protein (P = 0.01), and JNK (P = 0.03). Malignant pleural effusions could not be differentiated from ascites by signaling profiles. Both had signal expression clusters for survival, proliferation and metastasis, and injury pathways. Cox proportional hazards model analysis revealed high p38 and pEGFR/EGFR ratio as jointly associated with poor survival in Tap1 cases (both P < or = 0.002). Phospho-JNK quantity was associated with worse outcome in Tap2 patients (P = 0.004), when taking other factors into consideration. CONCLUSIONS: Proliferation, survival, and apoptosis signaling dysregulation can be identified in ovarian cancer effusion samples. Biochemical characterization of clinical effusions may provide either predictive and/or correlative information on patient outcome from which to further understand the mechanisms of effusion development and target clinical intervention.

Apoptosis↗

PubMed2025

Identifying novel protein biomarkers with cross-psychiatric disorders effects and potential intervention targets: Evidence from proteomic-Mendelian randomization.

Plasma proteins are the potential therapeutic targets for psychiatric disorders due to their important roles in signal transduction. We aimed to explore the plasma protein biomarkers with cross-psychiatric disorders effects. Proteome-wide Mendelian randomization (MR) and colocalization analyses were performed to investigate the potential causal relationship between plasma protein biomarkers and 12 psychiatric disorders and further identify the potential proteins with cross-effects. To assess the directionality and exclude potential reverse causation, Steiger directionality tests and reverse MR analyses were additionally conducted. Then, validation analysis was performed by employing summary data from cross-psychiatric disorder GWAS to validate the cross-psychiatric effects of proteins. Protein-protein interactions were conducted to evaluate the interaction between candidate proteins and druggability assessment was used to prioritize potential drug targets for psychiatric disorders. We identified novel plasma proteins that possessed cross-psychiatric disorder effects, especially BTN2A1 and BTN3A2 associated with major depressive disorder (MDD), schizophrenia (SCZ), and bipolar disorder (BIP); ITIH1, ITIH3, ITIH4 and FES associated with SCZ and BIP, and the cross-effects of these proteins on SCZ and BIP were confirmed by validation analyses. Steiger tests and reverse MR supported causal directionality. Besides, the protein-protein interactions (PPI) analysis indicated cross-effects proteins had significant interaction, especially ITIH1-ITIH3. The druggability assessment prioritized eight proteins, two of which (ITIH3 and NCAM1) has been targeted by antipsychotic drugs. Our findings provided insights into shared biological mechanisms underlying these conditions.

Humans↗

PubMed2026

Identification and genetic validation of potential therapeutic targets for pulmonary hypertension through multi-omics causal inference.

Pulmonary hypertension (PH) underscores the urgent need for novel therapeutic targets. This study aimed to employ a proteome-wide Mendelian randomization (MR) approach to systematically identify circulating proteins causally associated with PH, thereby providing genetically validated candidate targets for drug development. We adopted a 2-sample MR design, integrating large-scale plasma proteomic quantitative trait loci (pQTL) data (encompassing 4148 proteins) and summary statistics from a large-scale PH genome-wide association study (2047 cases, 8301 controls). Candidate targets were screened through a multilayered analytical pipeline comprising proteomic MR, transcriptomic MR, and summary-data-based Mendelian randomization. The ultimately identified MR-Identified Causal Candidate Targets (MR-ICTs) underwent rigorous Bayesian colocalization analysis, followed by biological characterization through functional enrichment analysis, single-cell transcriptomics, and phenome-wide association studies. Through robust genetic causal inference, this study provides that circulating proteins such as LYZ, GREM2, NID1, and PF4V1 play causal roles in PH pathogenesis. These findings offer a set of rigorously genetically validated, high-priority therapeutic targets for developing novel PH treatments, specifically addressing key pathological mechanisms such as innate immunity, BMP signaling pathway dysregulation, and platelet activation. Our multi-dimensional analysis ultimately identified 6 MR-ICTs causally associated with PH. Notably, the causal associations for lysozyme C (LYZ), gremlin-2 (GREM2), nidogen-1 (NID1), and platelet factor 4 variant 1 (PF4V1) were stringently validated by Bayesian colocalization analysis (posterior probability for hypothesis 4 [PPH4], indicating a shared causal variant, > 0.99). Functional enrichment analysis revealed significant involvement of these targets in immune response and TGF-β signaling pathways. Single-cell analysis further elucidated their cell-type-specific expression, with LYZ predominantly expressed in monocytes and PF4V1 almost exclusively in platelets.

Hypertension, Pulmonary↗

PubMed2006

A comprehensive analysis of the 14-3-3 interactome in barley leaves using a complementary proteomics and two-hybrid approach.

This study describes the identification of over 150 target proteins of the five 14-3-3 isoforms in 7-d-old barley (Hordeum vulgare) cv Himalaya seedlings using yeast two-hybrid screens complemented with 14-3-3 protein affinity purification and tandem mass spectrometry. Independent experiments for a subset of genes confirmed the yeast two-hybrid interactions, demonstrating a low false positive identification rate. These combined approaches resulted in the identification of more than 150 putative targets; 15% were previously reported to be 14-3-3 interactors, including, for example, Serpin, RF2A, WPK4 kinase, P-type proton-translocating adenosine triphosphatase, EF1A, glutamine synthetase, and invertases. The affinity purification resulted in 30 interactors, of which 44% function in metabolism, while the yeast two-hybrid screens identified 132 different proteins, with 35% of the proteins involved in signal transduction. A number of proteins have a well-described function in hormonal signaling, such as the auxin transport protein PIN1 and NPH3 and components of the brassinosteroid pathway, such as the receptor kinase BAK1 (OsPERK1) and BRI1-kinase domain-interacting protein 129. However, 14-3-3 interactions with these signal mediators have not been confirmed in the affinity purification. Confirmations of the 14-3-3 interaction with the three ABF-like transcription factors are shown using far western analysis. Also, a REPRESSION OF SHOOT GROWTH ortholog named RF2A was identified; these transcription factors play important roles in the abscisic acid and gibberellin pathways, respectively. We speculate that 14-3-3 proteins have a role in cross talk between these hormonal pathways. The specificity and complementary nature of both the affinity purification and the yeast two-hybrid approaches is discussed.

14-3-3 Proteins↗

PubMed2004

Mapping enzyme active sites in complex proteomes.

Genome sequencing projects have uncovered many novel enzymes and enzyme classes for which knowledge of active site structure and mechanism is limited. To facilitate mechanistic investigations of the numerous enzymes encoded by prokaryotic and eukaryotic genomes, new methods are needed to analyze enzyme function in samples of high biocomplexity. Here, we describe a general strategy for profiling enzyme active sites in whole proteomes that utilizes activity-based chemical probes coupled with a gel-free analysis platform. We apply this gel-free strategy to identify the sites of labeling on enzymes targeted by sulfonate ester probes. For each enzyme examined, probe labeling was found to occur on a conserved active site residue, including catalytic nucleophiles (e.g., C32 in glutathione S-transferase omega) and bases/acids (e.g., E269 in aldehyde dehydrogenase-1; D204 in enoyl CoA hydratase-1), as well as residues of unknown function (e.g., D127 in 3 beta-hydroxysteroid dehydrogenase/isomerase-1). These results reveal that sulfonate ester probes are remarkably versatile activity-based profiling reagents capable of labeling a diversity of catalytic residues in a range of mechanistically distinct enzymes. More generally, the gel-free strategy described herein, by consolidating into a single step the identification of both protein targets of activity-based probes and the specific residues labeled by these reagents, provides a novel platform in which the proteomic comparison of enzymes can be accomplished in unison with a mechanistic analysis of their active sites.

Aldehyde Dehydrogenase↗

PubMed2026

Profiler: an open web platform for multi-omics analysis.

MOTIVATION: High-throughput multi-omics technologies produce increasingly large and heterogeneous datasets that are difficult to analyze without advanced computational expertise. Existing bioinformatics tools are often fragmented or limited to specific omics types, hindering reproducibility and accessibility. There is a critical need for an integrated, user-friendly, and scalable platform capable of supporting multi-omics analyses across different data modalities. RESULTS: We present Profiler, an open-source, modular platform that unifies data import, quality control, preprocessing, statistical testing, machine and deep learning, biomarker discovery, pathway and drug-target enrichment, and survival modeling within a single reproducible environment. Built in Python with Streamlit, Profiler is available as both a web-based platform deployed on high-performance computing and a desktop version for local execution, enabling flexible usage across computational infrastructures. Profiler supports diverse omics modalities, including proteomics, transcriptomics, lipidomics, and electroencephalogram data. Through applications to glioblastoma proteomic, pancancer, and multi-omics datasets, Profiler reproduced known molecular subtypes, revealed potential therapeutic targets, and generated fully traceable analysis reports within minutes. By integrating advanced analytics behind an intuitive interface, Profiler democratizes multi-omics analysis and provides a robust, scalable foundation for systems biology and precision medicine research. AVAILABILITY AND IMPLEMENTATION: Profiler is open-source and freely available via its web platform (https://prism-profiler.univ-lille.fr) and GitHub (web version: https://github.com/yanisZirem/Profiler_v1_requests_datatests, desktop version: https://github.com/yanisZirem/prism-profiler), and archived on Zenodo (DOI: https://doi.org/10.5281/zenodo.17478158).

Software↗

PubMed2006

Chip-based analysis of SUMO (small ubiquitin-like modifier) conjugation to a target protein.

A chip-based analysis of protein interactions and modifications in cell signaling pathways has been of great potential in drug discovery, diagnostics, and cell biology, because it enables rapid and high-throughput biological assays with a small amount of samples. We report a chip-based analysis of sumoylation, the post-translational modification (PTM) process that involves covalent attachment of the small ubiquitin-like modifier (SUMO) protein to a target protein through multiple enzyme reactions in eukaryotic cells. Substrate proteins were spotted onto a glass surface followed by the addition of the reaction mixture for sumoylation, and the SUMO conjugation was readily detected by using fluorescent dye-labeled antibody. Under the optimized condition, on-chip sumoylation of Ran GTPase-activating protein 1 (RanGAP1) domain resulted in highly specific fluorescence intensity compared to that of its mutant (K524A) irrelevant to SUMO conjugation. The on-chip sumoylation was also verified and quantified by using the surface plasmon resonance(SPR) spectroscopy. As the exemplary study for a parallel analysis of sumoylation, fluorescent detection of sumoylation was conducted in a microarray format on a glass slide. The chip-based analysis developed here is expected to be applicable to assay for screening of target proteins from existing protein pools and proteome arrays in a high throughput manner.

GTPase-Activating Proteins↗