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PubMed2004

Comparative proteomic analysis of GS-NS0 murine myeloma cell lines with varying recombinant monoclonal antibody production rate.

We have employed an inverse engineering strategy based on quantitative proteome analysis to identify changes in intracellular protein abundance that correlate with increased specific recombinant monoclonal antibody production (qMab) by engineered murine myeloma (NS0) cells. Four homogeneous NS0 cell lines differing in qMab were isolated from a pool of primary transfectants. The proteome of each stably transfected cell line was analyzed at mid-exponential growth phase by two-dimensional gel electrophoresis (2D-PAGE) and individual protein spot volume data derived from digitized gel images were compared statistically. To identify changes in protein abundance associated with qMab datasets were screened for proteins that exhibited either a linear correlation with cell line qMab or a conserved change in abundance specific only to the cell line with highest qMab. Several proteins with altered abundance were identified by mass spectrometry. Proteins exhibiting a significant increase in abundance with increasing qMab included molecular chaperones known to interact directly with nascent immunoglobulins during their folding and assembly (e.g., BiP, endoplasmin, protein disulfide isomerase). 2D-PAGE analysis showed that in all cell lines Mab light chain was more abundant than heavy chain, indicating that this is a likely prerequisite for efficient Mab production. In summary, these data reveal both the adaptive responses and molecular mechanisms enabling mammalian cells in culture to achieve high-level recombinant monoclonal antibody production.

Adaptation, Physiological↗
PubMed2026

Exogenous ABA enhances cold tolerance of Rhododendron yedoense var. poukhanense under subzero temperature: integrating physiology, transcriptome, and proteome.

Low temperature limits the growth and ornamental value of evergreen shrubs. Rhododendron yedoense var. poukhanense, an important ornamental shrub from Northeast China, frequently suffers freezing damage during winter. While exogenous abscisic acid (ABA) enhances cold tolerance in many plants, its molecular mechanisms at subzero temperatures remain poorly understood in non-model species lacking chromosome-level reference genomes. This study investigated the effects of exogenous ABA on freezing tolerance in R. yedoense var. poukhanense at -4 °C using an integrated physiological, transcriptomic, and proteomic approach. Cutting seedlings were subjected to four treatments: CK (22°C control), A (22°C + ABA), LT (-4°C), and ALT (-4°C + ABA). Photosynthetic pigments, osmotic regulation substances, antioxidant enzyme activities, and malondialdehyde (MDA) content were measured. Transcriptome sequencing and quantitative proteomics were performed, and transcriptome data were validated by quantitative real-time PCR (qRT-PCR) of 15 selected genes. ABA pretreatment reduced visible cold injury severity, partially preserved photosynthetic pigments, decreased MDA content by 28.7%, and promoted recovery of catalase (+43.6%), superoxide dismutase (+31.1%), and peroxidase (+20.0%) activities under freezing stress. Transcriptome analysis revealed 8, 444 differentially expressed genes (DEGs) in LT versus CK and 6, 481 DEGs in ALT versus CK, representing a 23% reduction in transcriptional reprogramming scope attributable to ABA priming. The ALT versus LT comparison identified only 1, 690 additional DEGs, indicating that most cold-responsive genes were pre-activated during the ABA priming phase. Proteome analysis identified 1, 461 differentially expressed proteins (DEPs) in ALT versus CK. Integrated analysis revealed extensive post-transcriptional regulation, with transcript-protein concordance of only 1.0-4.1%, and co-enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in both omics layers. qRT-PCR validation confirmed high reliability of the transcriptome data (R2 = 0.8500). These findings demonstrate that exogenous ABA enhances freezing tolerance through multi-layered molecular regulation encompassing transcriptional buffering, translational reprogramming, and functional reallocation from photosynthesis to stress protection. This study provides the first integrated physiology-transcriptome-proteome framework for ABA-mediated freezing tolerance in an evergreen ornamental shrub and offers theoretical support for ABA-based winter protection strategies.

Rhododendron yedoense var. Poukhanense↗
PubMed2006

Analysis of the HUPO Brain Proteome reference samples using 2-D DIGE and 2-D LC-MS/MS.

Within the Human Proteome Organization (HUPO) Brain Proteome Project, a pilot study was launched with reference samples shipped to nine international laboratories (see Hamacher et al., this Special Issue) to evaluate different proteome approaches in neuroscience and to build up a first version of a brain protein database. One part of the study addresses quantitative proteome alterations between three developmental stages (embryonic day 16; postnatal day 7; 8 weeks) of mouse brains. Five brains per stage were differentially analyzed by 2-D DIGE using internal standardization and overlapping pH gradients (pH 4-7 and 6-9). In total, 214 protein spots showing stage-dependent intensity alterations (> two-fold) were detected, 56 of which were identified. Several of them, e.g. members of the dihydropyrimidinase family, are known to be associated with brain development. To feed the HUPO BPP brain protein database, a robust 2-D LC-MS/MS method was applied to murine postnatal day 7 and human post-mortem brain samples. Using MASCOT and the IPI database, 350 human and 481 mouse proteins could be identified by at least two different peptides. The data are accessible through the PRIDE database (http://www.ebi.ac.uk/pride/).

Aging↗
PubMed2025

Multi-Omics and Integrative Analytics in Natural Products Discovery.

Natural products (NPs) have long been an essential source of new bioactive compounds for drug discovery; however, traditional methods for screening and isolating these compounds can be slow and often yield diminishing returns. Fortunately, advanced multi-omics and computational approaches present powerful solutions to these challenges. This review highlights innovative methodologies that integrate metabolomics, genomics, transcriptomics, and proteomics with bioinformatics and analytical chemistry to accelerate NP discovery. For instance, untargeted metabolomics platforms like high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Products Social (GNPS) molecular networking allow for comprehensive profiling of new compounds, while targeted isotope-labeling strategies enhance this process. Additionally, genome and metagenome mining tools such as antibiotics and secondary metabolite analysis shell (antiSMASH), Deep Biosynthetic Gene Cluster (DeepBGC), and Pipeline for Reconstructing Integrated Syntheses of Metabolites (PRISM) quickly identify biosynthetic gene clusters (BGCs) in both cultured and uncultured organisms, often using heterologous expression to validate products. Transcriptomic analyses, including RNA sequencing (RNA-seq), co-expression networks, and fluxomics, help clarify how pathways are regulated, while quantitative proteomics techniques like tandem mass tags/isobaric tags for relative and absolute quantitation (TMT/iTRAQ) and label-free methods, along with chemoproteomics approaches such as cellular thermal shift assay and thermal proteome profiling (TPP), uncover molecular targets and their mechanisms of action. This review also places significant emphasis on the role of artificial intelligence (AI) and machine learning (ML) in integrating multi-omics data, spanning activities from constructing gene-metabolite correlation networks to leveraging knowledge graphs and graph neural networks for data fusion and functional prediction. Finally, this review concludes by discussing the synergistic benefits of multi-omics for natural-product discovery, addressing current technical challenges, and exploring future directions toward high-throughput, intelligent data integration for next-generation NP research.

Biological Products↗
PubMed2007

Material surfaces affect the protein expression patterns of human macrophages: A proteomics approach.

Monocyte-derived macrophages (MDM) are key inflammatory cells and are central to the foreign body response to implant materials. MDM have been shown to exhibit changes in actin cytoskeleton, multinucleation, cell size, and function in response to small alterations in polycarbonate-urethane (PCNU) surface chemistry. Although PCNU chemistry has an influence on de novo protein synthesis, no assessments of the protein expression profiles of MDM have yet been reported. The rapid emerging field of expression proteomics facilitates the study of changes in cellular protein profiles in response to their microenvironment. The current study applied proteomic techniques, 2-dimensional electrophoresis (2-DE) combined with MALDI-ToF (matrix assisted laser desorption ionization-time of flight) mass spectrometry, to determine differences in MDM protein expression influenced by PCNU. Results indicated that MDM responded to material chemistry by modulation of structural proteins (i.e. actin, vimentin, and tubulin). Additionally, intracellular protein modulation which requires proteins responsible for trafficking (i.e. chaperone proteins) and protein structure modification (i.e. bond rearrangement and protein folding) were also altered. This study demonstrated for the first time that a proteomics approach was able to detect protein expression profile changes in MDM cultured on different material surfaces, forming the basis for utilizing further quantitative proteomics techniques that could assist in elucidation of the mechanisms involved in MDM-material interaction.

Biocompatible Materials↗
PubMed2026

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↗
PubMed2006

Proteomic identification of a stress protein, mortalin/mthsp70/GRP75: relevance to Parkinson disease.

Functional impairment of mitochondria and proteasomes and increased oxidative damage comprise the main pathological phenotypes of Parkinson disease (PD). Using an unbiased quantitative proteomic approach, we compared nigral mitochondrial proteins of PD patients with those from age-matched controls. 119 of 842 identified proteins displayed significant differences in their relative abundance (increase/decrease) between the two groups. We confirmed that one of these, mortalin (mthsp70/GRP75, a mitochondrial stress protein), is substantially decreased in PD brains as well as in a cellular model of PD. In addition, nine candidate mortalin-binding partners were identified as potential mediators of PD pathology. Manipulations of mortalin level in dopaminergic neurons resulted in significant changes in sensitivity to PD phenotypes via pathways involving mitochondrial and proteasomal function as well as oxidative stress.

Age Factors↗
PubMed2003

HysTag--a novel proteomic quantification tool applied to differential display analysis of membrane proteins from distinct areas of mouse brain.

A novel isotopically labeled cysteine-tagging and complexity-reducing reagent, called HysTag, has been synthesized and used for quantitative proteomics of proteins from enriched plasma membrane preparations from mouse fore- and hindbrain. The reagent is a 10-mer derivatized peptide, H(2)N-(His)(6)-Ala-Arg-Ala-Cys(2-thiopyridyl disulfide)-CO(2)H, which consists of four functional elements: i) an affinity ligand (His(6)-tag), ii) a tryptic cleavage site (-Arg-Ala-), iii) Ala-9 residue that contains four (d(4)) or no (d(0)) deuterium atoms, and iv) a thiol-reactive group (2-thiopyridyl disulfide). For differential analysis cysteine residues in the compared samples are modified using either (d(4)) or (d(0)) reagent. The HysTag peptide is preserved in Lys-C digestion of proteins and allows charge-based selection of cysteine-containing peptides, whereas subsequent tryptic digestion reduces the labeling group to a di-peptide, which does not hinder effective fragmentation. Furthermore, we found that tagged peptides containing Ala-d(4) co-elute with their d(0)-labeled counterparts. To demonstrate effectiveness of the reagent, a differential analysis of mouse forebrain versus hindbrain plasma membranes was performed. Enriched plasma membrane fractions were partially denatured, reduced, and reacted with the reagent. Digestion with endoproteinase Lys-C was carried out on nonsolubilized membranes. The membranes were sedimented by ultra centrifugation, and the tagged peptides were isolated by Ni(2+) affinity or cation-exchange chromatography. Finally, the tagged peptides were cleaved with trypsin to release the histidine tag (residues 1-8 of the reagent) followed by liquid chromatography tandem mass spectroscopy for relative protein quantification and identification. A total of 355 unique proteins were identified, among which 281 could be quantified. Among a large majority of proteins with ratios close to one, a few proteins with significant quantitative changes were retrieved. The HysTag offers advantages compared with the isotope-coded affinity tag reagent, because the HysTag reagent is easy to synthesize, economical due to use of deuterium instead of (13)C isotope label, and allows robust purification and flexibility through the affinity tag, which can be extended to different peptide functionalities.

Amino Acid Sequence↗
PubMed2026

Resolving cellular signaling in space and time: From organelle proteomics to spatial phosphoproteomics.

Cellular signaling is inherently organized in space and time, requiring coordinated control of protein localization, molecular interactions, and enzymatic activity across subcellular compartments. Recent advances in chemical biology, protein engineering, and quantitative proteomics have made it possible to interrogate these dimensions in an integrated manner. Here, we highlight emerging strategies to resolve signaling organization across three interconnected dimensions: organelle-resolved proteome mapping to define spatial context, proximity labeling to capture local protein interaction networks, and spatially resolved phosphoproteomics to quantify signaling outputs. Developments in proximity labeling, including split, conditionally activated and light-gated enzymes, enable temporally controlled, context-dependent profiling of transient protein assemblies in living cells. Advances in high-throughput and low-input phosphoproteomics, together with improved computational frameworks for kinase activity inference and subcellular enrichment strategies, are enabling spatially resolved measurement of signaling activity. Together, these approaches are shifting the field from static localization maps toward dynamic models of signaling networks.

Proteomics↗
PubMed2006

Analyzing chromatin remodeling complexes using shotgun proteomics and normalized spectral abundance factors.

Mass spectrometry-based approaches are commonly used to identify proteins from multiprotein complexes, typically with the goal of identifying new complex members or identifying post-translational modifications. However, with the recent demonstration that spectral counting is a powerful quantitative proteomic approach, the analysis of multiprotein complexes by mass spectrometry can be reconsidered in certain cases. Using the chromatography-based approach named multidimensional protein identification technology, multiprotein complexes may be analyzed quantitatively using the normalized spectral abundance factor that allows comparison of multiple independent analyses of samples. This study describes an approach to visualize multiprotein complex datasets that provides structure function information that is superior to tabular lists of data. In this method review, we describe a reanalysis of the Rpd3/Sin3 small and large histone deacetylase complexes previously described in a tabular form to demonstrate the normalized spectral abundance factor approach.

Chromatin Assembly and Disassembly↗
PubMed2006

Organellar proteomics: turning inventories into insights.

Subcellular organization is yielding to large-scale analysis. Researchers are now applying robust mass-spectrometry-based proteomics methods to obtain an inventory of biochemically isolated organelles that contain hundreds of proteins. High-resolution methods allow accurate protein identification, and novel algorithms can distinguish genuine from co-purifying components. Organellar proteomes have been analysed by bioinformatic methods and integrated with other large-scale data sets. The dynamics of organelles can also be studied by quantitative proteomics, which offers powerful methods that are complementary to fluorescence-based microscopy. Here, we review the emerging trends in this rapidly expanding area and discuss the role of organellar proteomics in the context of functional genomics and systems biology.

Animals↗
PubMed2026

Mapping the covalent cysteine interactome of Ebselen reveals high-sensitivity target engagement and redox proteome remodeling.

Ebselen is a covalent organoselenium compound with broad pharmacological activity, yet its cellular cysteine targets and downstream proteomic consequences remain incompletely defined. Here, we integrated competitive gel-based activity-based protein profiling, reactivity-dependent tandem orthogonal proteolysis-activity-based protein profiling, and TMT-based quantitative proteomics to map Ebselen-induced cysteine engagement and proteome remodeling in living cancer cells. Ebselen exhibited dose-dependent cytotoxicity and markedly perturbed intracellular thiol-redox balance, as reflected by glutathione depletion and altered reactive oxygen species-associated fluorescence readouts. Competitive gel-based profiling confirmed concentration-dependent engagement of protein cysteine residues in live cells. Quantitative rdTOP-ABPP further identified hundreds of dose-responsive cysteine sites in HeLa and HepG2 cells and revealed a preference for cysteine microenvironments enriched with basic residues. Cross-cell-line comparison highlighted CDK5 Cys53, SMU1 Cys298, and RPSA2 Cys163 as conserved covalent nodes, among which CDK5 Cys53 showed high sensitivity to Ebselen treatment, a finding validated by competitive labeling and MS-based site assignment. Global TMT proteomics revealed extensive remodeling of redox-related and cell-survival-associated pathways, including compensatory upregulation of selenoproteins such as TXNRD1 and GPX family members. Together, these results define a chemical proteomic atlas of Ebselen-cysteine interactions and provide a framework for understanding and optimizing covalent organoselenium therapeutics.

Humans↗
PubMed2001

Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.

We demonstrate an integrated approach to build, test, and refine a model of a cellular pathway, in which perturbations to critical pathway components are analyzed using DNA microarrays, quantitative proteomics, and databases of known physical interactions. Using this approach, we identify 997 messenger RNAs responding to 20 systematic perturbations of the yeast galactose-utilization pathway, provide evidence that approximately 15 of 289 detected proteins are regulated posttranscriptionally, and identify explicit physical interactions governing the cellular response to each perturbation. We refine the model through further iterations of perturbation and global measurements, suggesting hypotheses about the regulation of galactose utilization and physical interactions between this and a variety of other metabolic pathways.

Computational Biology↗
PubMed2005

A proteomic study of the apolipoproteins in LDL subclasses in patients with the metabolic syndrome and type 2 diabetes.

The exchangeable apolipoproteins present in small, dense LDL (sdLDL) and large, buoyant LDL subclasses were evaluated with a quantitative proteomic approach in patients with the metabolic syndrome and with type 2 diabetes, both with subclinical atherosclerosis and the B LDL phenotype. The analyses included surface-enhanced laser adsorption/ionization, time-of-flight mass spectrometry, and subsequent identification by mass spectrometry or immunoblotting and were carried out in LDL subclasses isolated by ultracentrifugation in deuterium oxide gradients with near physiological salt concentrations. The sdLDLs of both types of patients were enriched in apolipoprotein C-III (apoC-III) and were depleted of apoC-I, apoA-I, and apoE compared with matched healthy controls with the A phenotype. The LDL complexes formed in serum from patients with diabetes with the arterial proteoglycan (PG) versican were also enriched in apoC-III. In addition, there was a significant correlation between the apoC-III content in sdLDL in patients and the apparent affinity of their LDLs for arterial versican. The unique distribution of exchangeable apolipoproteins in the sdLDLs of the patients studied, especially high apoC-III, coupled with the augmented affinity with arterial PGs, may contribute to the strong association of the dyslipidemia of insulin resistance with increased risk for cardiovascular disease.

Animals↗
PubMed2025

Exploring proteomic immunoprofiles: common neurological and immunological pathways in multiple sclerosis and type 1 diabetes mellitus.

BACKGROUND: Interest in the study of type 1 diabetes mellitus (T1DM) and multiple sclerosis (MS) has increased because of their significant negative impact on the patient quality of life and the profound implications for the health care system. Although the clinical symptoms of T1DM differ from those of MS, such as pancreatic β-cell failure in T1DM and demyelination in the central nervous system (CNS) in MS, both pathologies are considered as autoimmune-related diseases with shared pathogenic pathways, which include autophagy, inflammation and degeneration, among others. Considering the challenges in obtaining pancreatic β-cells and CNS tissue from patients with T1DM and MS, respectively, it is fundamental to explore alternative methods for evaluating disease status. Proteomic analysis of peripheral blood mononuclear cells (PBMCs) is an ideal approach for identifying novel and potential biomarkers for both autoimmune diseases. METHODS: We conducted a proteomic analysis of PBMCs from patients with T1DM and relapsing remitting Multiple Sclerosis (herein forth MS) patients (n = 9 per condition), using a label-free quantitative proteomics approach. The patients were diagnosed following the American Diabetes Association (ADA) criteria for T1DM and McDonald criteria for MS respectively, and were aged over 18 years and more than 2 years from the onset respectively. RESULTS: A total of 2476 proteins were differentially expressed in PBMCs from patients with T1DM and MS patients compared with those form healthy controls (H). Predictive analysis highlighted 15 common proteins, up- or downregulated in PBMCs from patients with T1DM and MS patients vs. healthy controls, involved in the immune system activity (BTF3, TTR, CD59, CSTB), diseases of the neuronal system (TTR), signal transduction (STMN1, LAMTOR5), metabolism of nucleotides (RPS21), proteins (TTR, ENAM, CD59, RPS21, SRP9) and RNA (SRSF10, RPS21). In addition, this study revealed both shared and distinct molecular patterns between the two conditions. CONCLUSIONS: Compared with H, patients with T1DM and MS presented a specific expression pattern of common proteins has been identified. This pattern underscores the shared mechanisms involved in their immune responses and neurological complications, alongside dysregulation of the autophagy pathway. Notably, CSTB has emerged as a differential biomarker, distinguishing between these two autoimmune diseases.

Humans↗
PubMed2026

Structure-resolved virus-host interactomics by cross-linking mass spectrometry.

Viruses depend on host protein networks to replicate, assemble progeny, and spread between cells and organisms. Defining these virus-host protein interactions is challenging because they are highly dependent on infection stage, cell type, species, and because mechanistic interpretation requires information about structural interfaces and conformational states. Cross-linking mass spectrometry (XL-MS) addresses these challenges by adding a spatial and structural dimension to virus-host interactomics in native systems. In this review, we discuss how XL-MS has advanced from targeted analysis of viral protein complexes to structure-resolved mapping of virion architecture and infected-cell virus-host interactomes. We highlight how XL-MS complements AP-MS, cryo-EM/cryo-ET, quantitative proteomics, genetic perturbation, and structure prediction to connect physical proximity with molecular mechanisms. Finally, we discuss current limitations in sensitivity, chemical coverage, temporal resolution, and model interpretation, and outline how future quantitative and integrative XL-MS workflows may enable systems-level structural virology.

Mass Spectrometry↗
PubMed2026

Proteome-level evidence that tebuconazole, both alone and in interaction with thiacloprid, affects epigenetic events in bumblebee heads.

Tebuconazole, a widely used ergosterol biosynthesis-inhibiting fungicide, can affect nontargets, especially when combined with insecticides. We employed label-free quantitative proteomics to investigate the effects of long-term exposure to sublethal concentrations (100 μg/L) of tebuconazole, either by itself or alongside the neonicotinoid thiacloprid (100 μg/L), on the heads of Bombus terrestris workers. A Bayesian factor power analysis revealed that the experiment produced conclusive proteomic results. Tebuconazole treatment revealed eleven differentially abundant proteins, which increased elevenfold with thiacloprid. The proteins that changed in the same direction in both treatments suggest the occurrence of epigenetic events because they are involved in histone trimethylation (H3K4me3), pre-mRNA processing, and folate (vitamin B9) metabolism. Following co-exposure, the abundance of histone H2A.V and its associated proteins was affected. Two important detoxification-related proteins, CYP6BE1 and CYP6AQ1 (honey bee homologs), were identified, as well as proteins that suggest hormonal and neurotoxic effects. Overall, this study suggests that tebuconazole affects key epigenetic processes in bumblebee heads at the proteome level, though this was not confirmed at the biological level or through orthogonal methods. The tested chemicals were previously found to affect trimethylations, but not H3K4me3. We suggest analyzing the different trimethylations, their interplay, and associated hallmarks, such as folate levels. SIGNIFICANCE: The effects of pesticides and their combinations on organisms can be unexpected until they are examined using modern, complex methods. High-throughput proteomics can provide data on important biochemical processes affected by pesticides, offering a different perspective to that at the expression level. Despite their low acute toxicity, a group of fungicides that inhibit (ergo)sterol biosynthesis (EBI or SBI) are considered dangerous to pollinators, including bumblebees. This is due to the increasing toxicity of insecticides through the inhibition of cytochrome P450 detoxification enzymes. We found that tebuconazole had a similar effect on epigenetic events when used alone or in combination with the insecticide thiacloprid. Key proteins suggest that H3K4 histone trimethylation (H3K4me3) was impacted. To our knowledge, this expands the existing evidence suggesting that tebuconazole/triazole fungicides affect histone trimethylation H3K27me3. Since literature shows that thiacloprid affects H3K9me3, it is possible that thiacloprid and tebuconazole interact in these epigenetic events that affect each other. Overall, our results suggest that tebuconazole affects proteins involved in histone trimethylation, pre-mRNA processing, and folate metabolism. These are all hallmarks of epigenetic processes and were further extended by the co-exposure of tebuconazole and thiacloprid to more differently abundant proteins. Additionally, the results provide data on cytochrome P450s of the CYP6 family, which act as detoxifying proteins, as well as proteins that indicate hormonal and neurotoxic effects in bumblebee heads. Finally, the results of the Bayesian power analysis confirmed the meaningfulness of the proteomic data analyzed in this study. If the new findings obtained at the proteome level are verified by different methods, the full extent of the side effects of tebuconazole can be revealed.

Animals↗
PubMed2006

Proteomic analysis of plasma membrane from hypoxia-adapted malignant melanoma.

Hypoxic conditions often persist within poorly vascularized tumors. At the cellular level constitutive activation of transcriptional regulators of the hypoxic response leads to the emergence of clones with aggressive phenotypes. The primary interface between the cell and the hypoxic environment is the plasma membrane. A detailed investigation of this organelle is expected to yield further targets for therapeutic perturbation of the response to hypoxia. In the present study, quantitative proteomic analysis of plasma membrane from hypoxia-adapted murine B16F10 melanoma was performed using differential 16O/18O stable isotopic labeling and multidimensional liquid chromatography-tandem mass spectrometry. The analysis resulted in the identification of 24,853 tryptic peptides, providing quantitative information for 2,433 proteins. For a subset of plasma membrane and secreted proteins, quantitative RT-PCR was used to gain further insight into the genomic regulatory events underlying the response to hypoxia. Consistent increases at the proteomic and transcriptomic levels were observed for aminopeptidase N (CD13), carbonic anhydrase IX, potassium-transporting ATPase, matrix metalloproteinase 9, and stromal cell derived factor I (SDF-1). Antibody-based analysis of a panel of human melanoma cell lines confirmed that CD13 and SDF-1 were consistently upregulated during hypoxia. This study provides the basis for the discovery of novel hypoxia-induced membrane proteins.

Amino Acid Sequence↗