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Immune Regulatory Signatures Associated with Different Recovery Durations of Delayed Graft Function after Kidney Transplantation.

Delayed graft function (DGF) is a common early complication of kidney transplantation characterized by immune activation. The duration of DGF may significantly affect long-term graft survival, yet the immune mechanisms underlying the different DGF durations remain unclear. Using a functional definition of delayed graft function (fDGF), defined as a failure of serum creatinine to decrease by at least 10% per day for three consecutive days within the first postoperative week, patients were stratified into short-term DGF (SDGF) and long-term DGF (LDGF) groups according to recovery periods. In this exploratory study, targeted proteomic analysis indicated that proteins enriched in SDGF were primarily involved in innate immune responses and acute inflammatory processes, including neutrophil chemotaxis and migration, whereas LDGF exhibited features related to adaptive immune responses and chronic inflammation, such as T-cell differentiation and activation. IL-7 and CCL20 were identified as candidate molecules potentially associated with different DGF durations. Targeted metabolomics revealed disturbances in amino acid metabolism, particularly alanine, aspartate, and glutamate metabolism, as well as in energy metabolism, including the tricarboxylic acid (TCA) cycle, which may be involved in LDGF. These findings provide preliminary insights into immune metabolic features associated with different DGF recovery durations.

Humans↗

[Proteomics of breast cancer: From differential to functional analysis].

From differential analysis to identify biomarkers, to functional analysis for finding new therapeutic targets, proteomics bring new comprehensive information for a better understanding of the molecular basis of oncology and new perspectives for the clinic. However the major limitation of proteomic investigations, more generally of post-genomic approaches, remains the molecular and cellular complexity of the mammary gland that is still a major challenge.

Biomarkers, Tumor↗

[Proteomics and breast cancer: new perspectives and limitations].

From differential analysis for the identification of biomarkers, to functional analysis for the evidencing of new therapeutic targets, proteomics brings new comprehensive information for a better understanding of the molecular basis of oncology and new perspectives for the clinic. However the major limitation of proteomic investigations and more generally of post-genomic approaches remains the molecular and cellular complexity of biological systems. This will be illustrated with the case of breast cancer.

Antineoplastic Agents↗

Proteomics-based approaches to neutrophil biology.

INTRODUCTION: Neutrophils are central effectors of innate immunity and key contributors to inflammation, host defense, and tissue injury across a wide range of physiological and pathological contexts. Due to their short lifespan, rapid activation, and extensive post-translational regulation, comprehensive molecular characterization of neutrophil function requires approaches that go beyond transcriptomics or marker-based analyses. AREAS COVERED: This review summarizes how proteomic technologies have advanced the understanding of neutrophil biology by enabling unbiased, system-wide profiling of protein abundance, subcellular organization, post-translational modifications, and functional heterogeneity. We discuss global and subcellular proteomics, PTM-centric analyses, and emerging low-input and single-cell proteomic strategies, highlighting recent studies of infection, cancer, metabolic disorders, aging, autoimmune disease, and inflammation. The literature covered includes current large-scale quantitative proteomics, targeted PTMs, and integrative multi-omics studies in both human samples and relevant experimental models. EXPERT OPINION: Proteomics has established neutrophils as highly plastic and context-dependent cells whose functions are governed by coordinated remodeling of signaling, metabolism, and effector pathways. Future progress will depend on expanding neutrophil-specific PTM maps, improving low-input workflows, and integrating single-cell and spatial proteomics. Together, these advances are expected to redefine neutrophil functional states and accelerate translation toward clinically meaningful biomarkers and therapeutic strategies.

Humans↗

Proteomics in the post-genome age.

The genome sequencing effort has helped spawn the burgeoning field of proteomics. This review article examines state-of-the-art proteomics methods that are helping change the discovery paradigm in a variety of biological disciplines and, in particular, protein biochemistry. The review discusses both classical and novel methods to perform high-throughput qualitative and quantitative "global" as well as targeted proteome analysis of complex biological systems. From a drug discovery standpoint, the synergy between genomics and proteomics will help elucidate disease mechanisms, identify novel drug targets, and identify surrogate biomarkers that could be used to conduct clinical trials.

Animals↗

Translational proteomics: developing a predictive capacity -- a review.

Over the past decade, proteomics has undergone a rapid development and radiation, diversifying across the biochemical landscape. While no single technique yet delivers complete proteomic coverage, application-specific adaptations afford significant opportunity for discovery and the development of predictive capacity (e.g. surrogate biomarker and clinical diagnostics). Targeted proteomic approaches, protein profiling strategies using affinity capture mass spectrometry and solution array represent realistic opportunities to deliver predictive capacity. The aim of this review is to provide an overview of proteomic technologies and how the outcomes delivered by such platforms may be translated into applications of predictive utility in clinical and basic science. In particular, recent applications in protein/peptide profiling (solid-phase affinity capture mass spectrometry and the targeted approach of antibody arrays) and the opportunities they afford researchers within the discipline of reproductive biology to develop new diagnostic and prognostic tests and surrogate biomarkers to improve the delivery of women's health care are considered.

Animals↗

Hepatocyte proteome destabilization and novel targets for PFASs unveiled through combined thermal proteome profiling and deep transfer learning.

Identifying protein targets for per- and polyfluoroalkyl substances (PFASs) is essential to understand their toxicity and health risks. However, knowledge about their interacting proteins is limited since reliable identification methods are lacking. We developed an integrated approach combining thermal proteome profiling (TPP) and deep transfer learning (DTL) modeling to efficiently identify cellular targets of PFAS. TPP measured PFAS binding proteins and the affinities by nanospray liquid chromatography tandem mass spectrometry, while DTL models were constructed to predict PFAS-protein affinities using neural network algorithms. TPP results revealed that PFASs uniquely destabilized the proteome of HepG2 cells, unlike the stabilizing effects by other xenobiotics. Key protein targets for three representative PFASs (PFOA, GenX and Novec 649) were identified, which exhibited weak binding affinities (median EC50 ≈ 30 μM). The number of protein targets increased with molecular weights among the three PFASs. The DTL model achieved a higher Pearson correlation coefficient of 0.89, and reduced mean squared errors by 54 % over previous models for drug-protein interactions. Notably, TPP and DTL jointly pinpointed ribosomal proteins as novel targets of GenX, potentially linking it to cell apoptosis through disrupted protein synthesis. Biolayer interferometry validated GenX binding to RPL4 protein, driven by electrostatic interactions and halogen bonds. This integrated approach effectively uncovers novel PFASs targets, advancing insights into their adverse health effects.

Humans↗

Multiomic Integration Reveals Novel miRNA-mRNA-Protein Expression Profile in the Aged Female Retina.

PURPOSE: Aging is a leading risk factor for retinal degeneration. MicroRNAs (miRNAs) regulate posttranscriptional gene suppressors and influence inflammation and oxidative stress, two processes disrupted during retinal aging. This study aimed to identify age-related miRNA-mRNA-protein associations between young and older retinas and uncover dysregulated pathways that may contribute to retinal degeneration. METHODS: Retinal function was assessed using electroretinography (ERG), and microgliosis was quantified by microglial immunohistochemistry (IHC). A multiomics approach was used to examine molecular changes in older (30-month-old) female C57BL/6J mouse retinas and compared with young female (3-month-old) controls. Illumina sequencing profiled short miRNAs (20 bp) and bulk mRNAs (150 bp), while total proteomics via mass spectrometry assessed protein expression. Bioinformatic analyses included targetome analysis (miRNet), pathway enrichment (Gene Ontology), and clustering to identify age-associated molecular targets and pathways. RESULTS: Retinas from older mice displayed neuronal dysfunction and increased microgliosis. Sequencing revealed significant dysregulation of miRNAs linked to immune and inflammatory pathways, supported by enrichment of their predicted mRNA targets. In the older mice, mRNA expression showed broad inflammatory activation, though only 14% of dysregulated mRNAs overlapped with predicted miRNA targets. Proteomic profiling revealed a disconnect between RNA and protein expression, yet all omics layers showed enrichment in inflammatory pathways. Integrated analysis identified associations involving several gene regulatory networks in the older retina. CONCLUSIONS: This study demonstrates that at an advanced age, miRNA expression and their predicted downstream regulatory networks are dysregulated, highlighting potential molecular mechanisms underlying age-related retinal degeneration.

Animals↗

From proteins to proteomics.

During the second half of the 20th century, biochemistry and subsequently molecular biology blossomed into the core upon which all biological and biomedical sciences now depend. A major part of these closely related disciplines has been the study of the structure and function of proteins and the diverse biological functions that they perform. Early experimentation necessarily focused on individual entities, selected mainly for their activities, but as technology improved there developed a tendency to look at proteins as larger, interactive groups or clusters. Spurred by the recent exponential production of genomic sequence data for a rapidly increasing number of species, protein chemistry has now evolved into a new discipline, proteomics. In addition to embracing the methods and approaches that have served protein scientists well in the past, it includes, and is perhaps best defined by, high-throughput analyses based in large part on 2D gel electrophoresis, MALDI and ESI mass spectrometry and combinatorial arrays. Proteomic targets include the identification of all genome products and a mapping of their interactions and expression profiles. These hold great promise for the identification of disease markers and drug targets, but are not without their challenges and pitfalls.

Animals↗

Cross-Platform Proteomics and Machine Learning Algorithms Nominate Plasma Biomarkers of Stroke Diagnosis.

BACKGROUND: Blood-based biomarkers for stroke subtyping could improve triage in emergency settings. We used cross-platform proteomics to identify plasma biomarkers differentiating major stroke diagnostic groups. METHODS: We conducted a case-control study using 2 biorepositories. Plasma was collected in the emergency department from adults with suspected stroke before therapeutic intervention. Differentially enriched proteins were identified across acute ischemic stroke, intracerebral hemorrhage, transient ischemic attack, and stroke mimics using SomaScan discovery proteomics (Grady). Differentially enriched proteins were nominated using pairwise and multigroup comparisons and adjusted for clinical covariates. Protein panels were created using least absolute shrinkage and selection operator logistic regression. Internal validation used repeated nested cross-validation (rCV) and targeted mass spectrometry (MS), while external validation used data-independent acquisition  mass spectrometry in an independent cohort (Yale). RESULTS: We included 100 subjects (40 with acute ischemic stroke, 20 with intracerebral hemorrhage, 20 with transient ischemic attack, 20 with stroke mimics) in discovery and 80 subjects (20 per group) in external validation cohorts. SomaScan quantified 7307 proteins, of which 61 differentiated stroke subtypes. We identified 7 protein classifiers for acute ischemic stroke (rCV-area under the curve, 0.82 [95% CI, 0.78-0.86]), 6 for intracerebral hemorrhage (rCV-area under the curve, 0.70 [95% CI, 0.64-0.76]), 8 for transient ischemic attack (rCV-area under the curve, 0.78 [95% CI, 0.73-0.84]), and 7 for stroke mimics (rCV-area under the curve, 0.81 [95% CI, 0.77-0.86]). Targeted proteomics internally validated 11 proteins, and data-independent acquisition-mass spectrometry externally validated 32 proteins, including VTN (vitronectin), PLG (plasminogen), and S100A9 as top stroke mimics, transient ischemic attack, and intracerebral hemorrhage classifiers. CONCLUSIONS: This study highlights plasma proteomics as a valuable tool for discovering protein biomarkers of stroke diagnosis. These findings support further validation in larger, multicenter cohorts to facilitate biomarker-guided stroke diagnosis in acute care.

Humans↗

Functional and Proteomic Profiles of CD3(+) Plasma-Derived Small Extracellular Vesicles Differentiate Cancer Patients From Healthy Donors.

Small extracellular vesicles (sEV) released by T cells play a key role in immune regulation. Immune capture with anti-CD3 antibodies was used to isolate and study T cell-derived CD3(+)sEV from the plasma of patients with melanoma (MPs) or healthy donors (HDs). Functional responses induced in recipient target cells by CD3(+)sEV of MPs differed from responses induced by CD3(+)sEV of HDs. Approximating functions mediated by melanoma cell-derived sEV (MTEX), CD3(+)sEV of MPs reduced metabolic activity and proliferation of T cells while promoting activity in Mel526 cell targets. Proteomics profiling confirmed functional differences between CD3(+)sEV of MPs and HDs. Of 294 sEV-specific proteins identified in CD3(+)sEV, 226 were detected in the parent T cell proteome, confirming that the CD3(+)sEV proteome mimics that of the parent T lymphocytes. Among them were 66 differentially expressed proteins (DEPs) that differentiated vesicles from MPs and HDs. These DEPs were associated with processes linked to cancer-related functions. DEPs upregulated in CD3(+)sEV of MPs were associated with RHO-GTPase, cytokine, and MAPK signaling pathways. Thus, T cells of MPs were reprogrammed by MTEX to produce CD3(+)sEV that functionally resembled MTEX, partly recapitulated features of the tumor proteome, and differed from CD3(+)sEV of HDs. In cancer, the TEX-rewired T cells produce CD3(+)sEV that potentially could serve as a liquid biopsy of patients' T cells.

Humans↗

Exploratory proteomic and metabolomic profiling of pleural effusions identifies histone H4 and alanine as promising complementary markers for pleural tuberculosis.

The diagnosis of pleural tuberculosis (Pl-TB) remains challenging. Histopathological analysis and pathogen detection in pleural biopsies are informative but limited. We investigated differentially expressed proteins and metabolites in pleural effusions from patients with Pl-TB, malignancies, and other pathologies. A proteomic analysis of pooled pleural effusions identified 45 proteins exclusively detected or upregulated in Pl-TB samples, many linked to infectious processes. Conversely, 18 proteins were uniquely found or upregulated in malignant pleural effusions, mainly associated with detoxification and hemostasis. To validate these findings, we employed targeted proteomics in individual samples. Eight proteins were validated: S100-A9, histone H4, insulin-like growth factor-binding protein 2, fibrinogen beta chain, ficolin-3, immunoglobulin heavy constant alpha 1, sulfhydryl oxidase 1, and histidine-rich glycoprotein. Additionally, NMR-based metabolomics identified 13 metabolites with differential abundance between Pl-TB and non-TB samples. Notably, N-acetyl-glycoprotein and the branched-chain amino acids, alanine and lysine differed between groups. Proteomic and metabolomic analyses revealed distinct molecular profiles between Pl-TB and non-TB patients, despite intra-group variability. To address this, we applied classification models. Histone H4 and alanine consistently emerged as discriminative features. Overall, this study provides novel insights into the molecular landscape of Pl-TB. The combined quantification of proteins and metabolites may improve differential diagnosis, although should be further validated in larger, independent cohorts before clinical application.

Humans↗

A proteomic approach to the identification of cytochrome P450 isoforms in male and female rat liver by nanoscale liquid chromatography-electrospray ionization-tandem mass spectrometry.

Nanoscale reversed-phase liquid chromatography (LC) combined with electrospray ionization-tandem mass spectrometry (ESI-MS/MS) has been used as a method for the direct identification of multiple cytochrome P450 (P450) isoforms found in male and female rat liver. In this targeted proteomic approach, rat liver microsomes were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis followed by in-gel tryptic digestion of the proteins present in the 48- to 62-kDa bands. The resultant peptides were extracted and analyzed by LC-ESI-MS/MS. P450 identifications were made by searching the MS/MS data against a rat protein database containing 21,576 entries including 47 P450s using Sequest software (Thermo Electron, Hemel Hempstead, UK). Twenty-four P450 isoforms from the subfamilies 1A, 2A, 2B, 2C, 2D, 2E, 3A, 4A, 4F, CYP17, and CYP19 were positively identified in rat liver.

Amino Acid Sequence↗

Analysis of the Saccharomyces cerevisiae proteome with PeptideAtlas.

We present the Saccharomyces cerevisiae PeptideAtlas composed from 47 diverse experiments and 4.9 million tandem mass spectra. The observed peptides align to 61% of Saccharomyces Genome Database (SGD) open reading frames (ORFs), 49% of the uncharacterized SGD ORFs, 54% of S. cerevisiae ORFs with a Gene Ontology annotation of 'molecular function unknown', and 76% of ORFs with Gene names. We highlight the use of this resource for data mining, construction of high quality lists for targeted proteomics, validation of proteins, and software development.

Codon↗

Integrating a functional proteomic approach into the target discovery process.

Functional proteomics is a promising technique for the rational identification of novel therapeutic targets by elucidation of the function of newly identified proteins in disease-relevant cellular pathways. Of the recently described high-throughput approaches for analyzing protein-protein interactions, the yeast two-hybrid (Y2H) system has turned out to be one of the most suitable for genome-wide analysis. However, this system presents a challenging technical problem: the high prevalence of false positives and false negatives in datasets due to intrinsic limitations of the technology and the use of a high-throughput, genetic assay. We discuss here the different experimental strategies applied to Y2H assays, their general limitations and advantages. We also address the issue of the contribution of protein interaction mapping to functional biology, especially when combined with complementary genomic and proteomic analyses. Finally, we illustrate how the combination of protein interaction maps with relevant functional assays can provide biological support to large-scale protein interaction datasets and contribute to the identification and validation of potential therapeutic targets.

Animals↗

Lipid hydroperoxides and oxylipins are mediators of denervation induced muscle atrophy.

Loss of innervation is a key driver of age associated muscle atrophy and weakness (sarcopenia). Our laboratory has previously shown that denervation induced atrophy is associated with the generation of mitochondrial hydroperoxides and lipid mediators produced downstream of cPLA2 and 12/15 lipoxygenase (12/15-LOX). To define the pathological impact of lipid hydroperoxides generated in denervation-induced atrophy in vivo, we treated mice with liproxstatin-1, a lipid hydroperoxide scavenger. We treated adult male mice with 5 mg/kg liproxstain-1 or vehicle one day prior to sciatic nerve transection and daily for 7 days post-denervation before tissue analysis. Liproxstatin-1 treatment protected gastrocnemius mass and fiber cross sectional area (∼40% less atrophy post-denervation in treated versus untreated mice). Mitochondrial hydroperoxide generation was reduced 80% in vitro and by over 65% in vivo by liproxstatin-1 treatment in denervated permeabilized muscle fibers and decreased the content of 4-HNE by ∼25% post-denervation. Lipidomic analysis revealed detectable levels of 25 oxylipins in denervated gastrocnemius muscle and significantly increased levels for eight oxylipins that are generated by metabolism of fatty acids through 12/15-LOX. Liproxstatin-1 treatment reduced the level of three of the eight denervation-induced oxylipins, specifically 15-HEPE, 13-HOTrE and 17-HDOHE. Denervation elevated protein degradation rates in muscle and treatment with liproxstatin-1 reduced rates of protein breakdown in denervated muscle. In contrast, protein synthesis rates were unchanged by denervation. Targeted proteomics revealed a number of proteins with altered expression after denervation but no effect of liproxstain-1. Transcriptomic analysis revealed 203 differentially expressed genes in denervated muscle from vehicle or liproxstatin-1 treated mice, including ER stress, nitric oxide signaling, Gαi signaling, glucocorticoid receptor signaling, and other pathways. Overall, these data suggest lipid hydroperoxides and oxylipins are key drivers of increased protein breakdown and muscle loss associated with denervation induced atrophy and a potential target for sarcopenia intervention.

Male↗

Identification of protein expression signatures associated with Helicobacter pylori infection and gastric adenocarcinoma using recombinant antibody microarrays.

Antibody microarray based technology is a powerful emerging tool in proteomics, target discovery, and differential analysis. Here, we report the first study where recombinant antibody fragments have been used to construct large scale antibody microarrays, composed of 127 different antibodies against mostly immunoregulatory antigens. The arrays were based on single framework recombinant antibody fragments (SinFabs) designed for high on-chip stability and functionality and were used for the analysis of malignant and normal stomach tissue samples from Helicobacter pylori-positive and -negative patients. Our results demonstrate that distinct tumor- as well as infection-associated protein expression signatures could be identified from these complex tissue proteomes, as well as biomarkers such as IL-9, IL-11, and MCP-4, previously not found in these diseases. In a longer perspective, this study may improve the understanding of H. pylori-induced stomach cancer and lead to development of improved diagnostics.

Adenocarcinoma↗

DNA Methylation and Proteomic Profiling of Postmortem Brain Tissue Reveals Epigenetic Dysregulation and Neuroinflammatory in Fragile X-associated Tremor/Ataxia Syndrome (FXTAS).

BACKGROUND: Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a late-onset neurodegenerative disorder caused by FMR1 premutation CGG repeat expansions (55-200 repeats). The epigenetic landscape of the FXTAS brain remains uncharacterized. We performed genome-wide DNA methylation profiling of postmortem prefrontal cortex tissue to identify differentially methylated positions (DMPs) and candidate genes, and sought protein-level support for a neuroinflammatory signal. METHODS: DNA methylation was profiled in postmortem prefrontal cortex (Brodmann area 9) from 27 male FXTAS cases and 29 male controls using the Illumina MethylationEPIC array (EPICv1 and EPICv2 platforms), merging 721,802 common probes. Surrogate variable analysis (SVA) controlled for confounders. DMPs were defined by |&#x394;&#x3b2;| > 0.10 and FDR < 0.05; exploratory Reactome 2024 pathway analysis was performed on the DMP-associated gene list. Targeted proteomic profiling was performed in the same brain region using the Olink (proximity extension assay) Inflammation panel in 9 FXTAS cases and 12 controls, with SVA-adjusted differential abundance analysis, and concordance assessment against a prior mass spectrometry dataset. RESULTS: We identified 108 significant cg-type DMPs mapping to 80 genes (50 hypermethylated, 58 hypomethylated in FXTAS). The strongest signal was CYP2E1 (7 concordant hypomethylated DMPs, mean &#x394;&#x3b2; = -0.143), an oxidative stress gene also implicated in Parkinson's disease. FTCD, a one-carbon cycle enzyme, carried 5 hypermethylated DMPs (mean &#x394;&#x3b2; = +0.210). A cluster of DMP-associated genes with established roles in innate immune and NF-&#x3ba;B signaling, TRAF3 (the single most significant DMP among the inflammation genes, hypermethylated), BATF, RCOR1, and MSI2; they pointed toward neuroinflammatory dysregulation. Additional genes included LINGO1 (myelination inhibitor), SYT3 (synaptic vesicle), and SLC39A4 (zinc transporter). Exploratory Reactome enrichment using the DMP-associated gene set nominated themes including neuroinflammation resolution, axonal growth inhibition, zinc homeostasis, and CYP2E1 metabolism at nominal significance (p<0.05); however, the gene-to-pathway mapping rate was low and no pathway survived correction for multiple testing. Olink proteomic analysis independently identified 60 significantly altered inflammation proteins (59 downregulated), including CXCL8, CXCL10, IL6, IL15, IL18, TLR3, IRAK1/4, and complement C1QA, which were directionally concordant with prior mass spectrometry data. CONCLUSIONS: This integrated study reveals a genome-wide epigenetic signature in the FXTAS prefrontal cortex implicating oxidative stress, myelination failure, zinc dysregulation, one-carbon cycle disruption, and most notably a coordinated set of epigenetically altered genes governing innate immune and NF-&#x3ba;B signaling. Convergence of TRAF3 hypermethylation with independent downregulation of TLR3 and NF-&#x3ba;B-pathway proteins at the protein level supports a coherent, cross-platform model of dysregulated neuroinflammatory signaling in FXTAS, identified here through individual gene- and protein-level convergence rather than formal pathway enrichment. FTCD hypermethylation proposes a self-reinforcing epigenetic loop via SAM depletion. These multi-omic findings establish FXTAS as a disorder of pervasive epigenetic reprogramming and nominate candidate genes for future mechanistic and therapeutic investigation.

CYP2E1↗