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PubMedDate not supplied

The transfer of reductive energy and pace of proteome turnover: a theory of integrated catabolic control.

Hundreds of cell proteins undergo reversible transitions among redox states. Coordinate control and common functions served by redox-modified proteins are unknown. The suspect "redox code" integrating metabolome, proteome, and genome remains undefined. Protein redox control involves coupling of the population redox partition to transfer of reductive energy from source to sink. Lessons in metabolic programs under redox coordination might be found in nutritional desperation where reductive transfer from fuel fails to feed pathways to protein reduction. Upon nutritional interruption, proteolysis initially increases. However, catabolism secondarily declines in later starvation so as to postpone loss of the minimal proteome under synthetic failure and delay death. Integrated proteome turnover is paced by reductive transfer coupled to redox states of proteins serving diverse functions. Some continuing proteolysis is redox-independent. Cathepsin B is a model, redox-responsive, catabolic machine among proteins involved in turnover. The CysHis pair is simultaneously a redox-responsive site, an inhibitory metal-binding site, and a peptidolytic reaction mechanism. Pro-region cleavage generates permissive reaction conditions, but not necessarily the maximal peptidolytic rate. Mature cathepsin B can be inactivated by partition into multiple oxidation states. Cathepsin B can be reductively activated by glutathione or disulfhydryl reductases, and redox-buffered by glutathione homodisulfide/glutathione. Topics in protease regulation include: (a) the rate of total cell transfer of nutrient reductive energy from NADPH source potential to reductive pathways, (b) the distribution of reductive energy routed through parallel interactive pathways to protease, (c) the rate of transfer from protease through pathways to oxygen (reactive oxygen species) acceptor at sink potential, and (d) the linkage of protease state partition to relative rates of reductions and oxidations. Cell iron, sulfur, and oxygen redox are inseparable. The interaction of the CysHis site with iron provides a sensor, integrator, and effector switch coupling cathepsin B to metal-sulfuroxygen redox. Artificial metal-redox-proton switching is a new concept in protein engineering; however, nature has already applied "nanotechnology" to protein redox control.

Animals↗

PubMed2003

Thylakoid membrane at altered metabolic state: challenging the forgotten realms of the proteome.

Analysis of the membrane integral proteome is mainly dependent on the ability of protein separation. Blue-native polyacrylamide gel electrophoresis (BN-PAGE) is a technique capable of efficient membrane protein separation, so far mainly applied to the mitochondrial oxidative phosphorylation machinery. Applying BN-PAGE to the thylakoid membranes after mild solubilization with digitonin we succeeded in displaying the response of the green algae Chlamydomonas reinhardtii to altered culture conditions. In addition, by peptide mass fingerprinting and matrix assisted laser desorption/ionization-mass spectrometry (MALDI-MS) extremely hydrophobic subunits of the photosystem complexes with 5-11 transmembrane helices were identified, which could not be accessed by in-gel digestion in previous studies.

Adaptation, Physiological↗

PubMed2026

Molecular Determinants and Therapeutic Targeting of Stop Codon Readthrough in Eukaryotic Translation.

Accurate translation termination is essential for proteome integrity and in eukaryotes is primarily governed by the release factors eRF1 and eRF3, which ensure precise recognition of stop codons and efficient release of nascent polypeptides. However, proteome integrity is challenged by mutations that generate premature termination codons (PTCs), leading to truncated, nonfunctional proteins and degradation of the aberrant transcript via nonsense-mediated mRNA decay (NMD). Collectively, these events account for ∼1800 human genetic diseases. Translational readthrough, the process by which near-cognate tRNAs decode stop codons and allow ribosomes to continue elongation beyond the stop codon, represents a possibility to suppress PTCs and restore full-length protein synthesis. Initially discovered in viruses as a mechanism to expand coding capacity, readthrough is now recognized as a regulated feature of eukaryotic gene expression influenced by both cis-acting sequence elements and trans-acting factors. Recent evidence highlights the remarkable context dependence of readthrough, revealing variation across transcripts, tissues, and developmental stages. In this review, we examine the molecular determinants that define stop codon recognition and readthrough efficiency, with particular emphasis on nucleotide context. We further discuss the mechanisms and binding sites of small molecules that promote PTC readthrough, and summarize the clinical development landscape of readthrough-inducing compounds for the treatment of diseases caused by nonsense mutations.

Humans↗

PubMed2006

Integrating synapse proteomics with transcriptional regulation.

The mammalian postsynaptic proteome (PSP) comprises a highly interconnected set of approximately 1,000 proteins. The PSP is organized into macromolecular complexes that have a modular architecture defined by protein interactions and function. Signals initiated by neurotransmitter receptors are integrated by these complexes and their constituent enzymes to orchestrate multiple downstream cellular changes, including transcriptional regulation of genes at the nucleus. Genome wide transcriptome studies are beginning to map the sets of genes regulated by the synapse proteome. Conversely, understanding the transcriptional regulation of genes encoding the synapse proteome will shed light on synapse formation. Mutations that disrupt synapse signalling complexes result in cognitive impairments in mice and humans, and recent evidence indicates that these mutation change gene expression profiles. We discuss the need for global approaches combining genetics, transcriptomics and proteomics in order to understand cognitive function and disruption in diseases.

Animals↗

PubMed2025

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Understanding the tumor immune microenvironment (TIME) is crucial towards personalized therapeutic strategies. OBJECTIVES: This study aims to systematically characterize the heterogeneity and complexity of the TIME in Lu-NECs by integrating proteomic, transcriptomic, and genomic data. METHODS: We performed comprehensive immune-proteomic profiling of 76 Lu-NECs across diverse histopathological subtypes to elucidate intra-tumoral TIME heterogeneity at the proteomic level. Validation was conducted in multiple independent cohorts, including 112 Lu-NECs using immunohistochemistry, 147 Lu-NECs, and 17 small cell lung carcinoma samples using transcriptomics. We integrated proteomic, transcriptomic, genomic, and clinical data to assess molecular, immunological, and clinical features, as well as therapeutic vulnerabilities across different immune subtypes. RESULTS: We delineated the immuno-proteomic landscape of Lu-NECs and identified two major immuno-proteomic clusters with distinct immunological, molecular, and clinical characteristics. IPC1 was characterized by high immune cell infiltration, while IPC2 exhibited sparse immune cell presence. Genomic analysis revealed distinct mutational patterns, with IPC1 showing a higher incidence of APOBEC-associated mutation signatures and IPC2 being enriched for mutations associated with defective DNA mismatch repair and tobacco-related mutagens. Functional analyses indicated that IPC1 was related to immune and oncogenic signaling activity, whereas IPC2 was associated with cancer stemness and proliferation-related features. Furthermore, IPC1 and IPC2 demonstrated histological subtype-specific clinical benefits from postoperative chemotherapy. Finally, we developed a machine learning model (iPROM) to predict Lu-NECs immune classification and improve risk stratification, which was validated across multiple independent cohorts. CONCLUSIONS: This study advances the understanding of the tumor immune microenvironment in Lu-NECs through multi-omics characterization and highlights potential personalized therapeutic vulnerabilities tailored to the specific immune landscapes of Lu-NECs.

Humans↗

PubMed2001

Nuclear envelope proteomics: novel integral membrane proteins of the inner nuclear membrane.

The nuclear envelope (NE) is one of the least characterized structures of eukaryotic cells. The study of its functional roles is hampered by the small number of proteins known to be specifically located to it. Here, we present a comprehensive characterization of the NE proteome. We applied different fractionation procedures and isolated protein subsets derived from distinct NE compartments. We identified 148 different proteins by 16-benzyl dimethyl hexadecyl ammonium chloride (16-BAC) gel electrophoresis and matrix-assisted laser desorption ionization (MALDI) mass spectrometry; among them were 19 previously unknown or noncharacterized. The identification of known proteins in particular NE fractions enabled us to assign novel proteins to NE substructures. Thus, our subcellular proteomics approach retains the screening character of classical proteomic studies, but also allows a number of predictions about subcellular localization and interactions of previously noncharacterized proteins. We demonstrate this result by showing that two novel transmembrane proteins, a 100-kDa protein with similarity to Caenorhabditis elegans Unc-84A and an unrelated 45-kDa protein we named LUMA, reside in the inner nuclear membrane and likely interact with the nuclear lamina. The utility of our approach is not restricted to the investigation of the NE. Our approach should be applicable to the analysis of other complex membrane structures of the cell as well.

Animals↗

PubMed2005

Global strategies to integrate the proteome and metabolome.

A fundamental goal of proteomics is to assign physiological functions to all proteins encoded by eukaryotic and prokaryotic genomes. Of the many activities performed by proteins, the chemical transformations catalyzed by enzymes form the basis for most, if not all, metabolic and signaling pathways. Elucidation of these pathways and their integration into larger cellular networks require new strategies to rapidly and systematically identify physiological substrates of enzymes. Here, we review emerging technologies that aim to assign endogenous biochemical functions to enzymes by profiling the metabolome.

Animals↗

PubMed2006

A study of Streptococcus thermophilus proteome by integrated analytical procedures and differential expression investigations.

Streptococcus thermophilus is a Gram-positive bacterium belonging to the group of lactic acid bacteria, among which several genera play an essential role in manufacture of food products. Recently, a genomic consortium sequenced and annotated its entire genome, which has been demonstrated to contain 1900 coding sequences. In this study, we have revealed the expression products of almost 200 different genes using a proteomic strategy combining 2-DE plus MALDI-TOF PMF and differential 1-DE plus muLC-ESI-IT-MS/MS. Thus, a number of cellular pathways related to important physiological processes were described at the proteomic level. Almost 50 genes were related to multiple electrophoretic species, whose heterogeneity was mainly due to variability in pI values. A 2-DE reference map obtained for lactose-grown cells was compared with those obtained after heat, cold, acid, oxidative and starvation stresses. Protein up/down-regulation measurements demonstrated that adaptation to different environmental challenges may involve the contribution of unique as well as combined physiological mechanisms. Common regulatory sites in the promoter region of genes whose expression was induced after stress were identified. These results provide a better comprehension of biochemical processes related to stress resistance in S. thermophilus, allowing defining the molecular bases of adaptative responses or markers for the identification of strains with potential industrial applications.

Bacterial Proteins↗

PubMed2026

The Multi-Omics Landscape of Enzymatic Alterations in Systemic Lupus Erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is an autoimmune disease closely associated with enzyme dysfunction, yet its underlying molecular mechanisms remain incompletely understood. This study aims to characterize enzyme-network alterations associated with SLE status and disease activity and to identify candidate molecules with potential clinical relevance. METHODS: We integrated proteomic and phosphoproteomic data from peripheral blood mononuclear cells (PBMCs) of 130 SLE patients and 90 healthy controls (HC), along with transcriptomic data from 1461 SLE patients. Through systematic analysis of key enzyme phosphorylation sites, upstream transcription factors (TFs), and computationally prioritized candidate compounds, we sought to characterize enzyme-centered regulatory associations. RESULTS: Integrated proteomic and phosphoproteomic analyses revealed significant metabolic and signaling pathway disturbances, along with distinct phosphorylation patterns in SLE immune cells. Multiple SLE-associated and disease-activity-associated candidate molecules were identified. Regulatory network analysis uncovered an upstream transcription factor cluster centered around STAT1. Computational drug screening identified computationally prioritized candidate compounds with multi-gene DSigDB associations, which require further clinical safety evaluation and experimental validation. CONCLUSIONS: This study constructs a molecular map of SLE, highlighting associations between enzyme-network alterations, catalytic dysregulation, and SLE-related immune molecular signatures, and identifies candidate molecules for future clinical and functional evaluation.

Humans↗

PubMed2003

PCAS--a precomputed proteome annotation database resource.

BACKGROUND: Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources. RESULTS: We report here the development of PCAS (ProteinCentric Annotation System) as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome.PCAS is available at http://pak.cbi.pku.edu.cn/proteome/gca.php CONCLUSION: PCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms identified.

Algorithms↗

PubMedDate not supplied

Analysis of altered protein expression patterns of Chlamydia pneumoniae by an integrated proteome-works system.

We have identified, analyzed, and quantified differential protein expression profile of five C. pneumoniae proteins, Adk (adenylate kinase), AhpC (thiol-specific antioxidant), CrpA (15 KD cysteine rich protein), Map (methionine aminopeptidae), and Cpn0710 (hypothetical protein) under normal versus persistent growth conditions induced by interferon-gamma, at different time intervals of their replicative cycle by successfully employing the latest proteomic analysis tool, PDQuest 2-D analysis software. We have also determined that this software represents a reliable analytical tool for mapping protein expression patterns in C. pneumoniae.

Bacterial Proteins↗

PubMed2003

Integration of proteomics and genomics in platelets: a profile of platelet proteins and platelet-specific genes.

Platelets, while anucleate, contain RNA, some of which is translated into protein upon activation. Hypothesising that the platelet proteome is reflected in the transcriptome, we identified 82 proteins secreted from activated platelets and compared these, as well as published proteomic data, to the transcriptional profile. We also compared the transcriptome of platelets to other tissues to identify platelet-specific genes and used ontology to determine gene categories over-represented in platelets. RNA was isolated from highly pure platelet preparations for hybridization to Affymetrix oligonucleotide arrays. We identified 2,928 distinct messages as being present in platelets. The platelet transcriptome was compared with the proteome by relating both to UniGene clusters. Platelet proteomic data correlated well with the transcriptome, with 69% of secreted proteins detectable at the mRNA level, and similar concordance was obtained using two published datasets. While many of the most abundant mRNAs are for known platelet proteins, messages were detected for proteins not previously reported in platelets. Some of these may represent residual megakaryocyte messages; however, proteomic analysis confirmed the expression of many previously unreported genes in platelets. Transcripts for well-described platelet proteins are among the most platelet-specific messages. Ontological categories related to signal transduction, receptors, ion channels, and membranes are over-represented in platelets, while categories involved in protein synthesis are depleted. Despite the absence of gene transcription, the platelet proteome is mirrored in the transcriptome. Conversely, transcriptional analysis predicts the presence of novel proteins in the platelet. Transcriptional analysis is relevant to platelet biology, providing insights into platelet function and the mechanisms of platelet disorders.

Blood Platelets↗

PubMed2003

Metabolic networks of microbial systems.

In contrast to bioreactors the metabolites within the microbial cells are converted in an impure atmosphere, yet the productivity seems to be well regulated and not affected by changes in operation variables. These features are attributed to integral metabolic network within the microorganism. With the advent of neo-integrative proteomic approaches the understanding of integration of metabolic and protein-protein interaction networks have began. In this article we review the methods employed to determine the protein-protein interaction and their integration to define metabolite networks. We further present a review of current understanding of network properties, and benefit of studying the networks. The predictions using network structure, for example, in silico experiments help illustrate the importance of studying the network properties. The cells are regarded as complex system but their elements unlike complex systems interact selectively and nonlinearly to produce coherent rather than complex behaviors.

Journal Article↗

PubMed2026

DORSSAA: Drug-Target interactOmics Resource Based on Stability/Solubility Alteration Assay.

Advancements in high-throughput techniques such as Thermal Proteome Profiling and the high-throughput Proteome Integral Solubility Alteration assay have revolutionized our understanding of drug-protein interactions. Despite these innovations, the absence of an integrative platform for cross-study analysis of stability and solubility alteration data represents a significant bottleneck. To address this gap, we introduce Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay (DORSSAA), an interactive and expandable web-based platform for the systematic analysis and visualization of proteome stability and solubility alteration assay datasets. Currently, DORSSAA features 1,135,985 records spanning 38 cell lines and organisms, 135 compounds, and 40,742 protein targets. Through its user-friendly interface, the resource supports comparative drug-protein interaction analysis and facilitates the discovery of actionable therapeutic targets. Through two case studies, methotrexate target profiling in A549 cells and combinatorial-therapy drug-target interactions in leukemia cell lines, we demonstrate DORSSAA's utility for identifying protein-drug interactions across diverse experimental contexts. This resource empowers researchers to accelerate drug discovery and enhance our understanding of protein behavior. Compared with data repositories and interaction databases, DORSSAA provides direct protein-level evidence of mechanisms of action with strict statistical control for each study. This enables more reliable identification of drug targets, off-target effects, and potential drug combinations.

Humans↗

PubMed2001

ToothPrint, a proteomic database for dental tissues.

Increasing demand exists to disseminate and integrate proteomic data as proteome analysis assumes a commanding role in the postgenome era. Databases on the World Wide Web are an effective means to share information obtained from two-dimensional gels and allied proteomic approaches. Here we report the establishment of ToothPrint, a proteomic database for dental tissues accessed at http://toothprint.otago.ac.nz. Using developing rat enamel as a prototype, ToothPrint provides a variety of functionally relevant data (ligand binding, subcellular localisation, developmental regulation) in addition to protein identification maps. Features designed to enhance usability of the website and simplify its computing requirements are also outlined. Customized for mineralizing tissues, ToothPrint should prove to be an effective bioinformatic resource for investigations of dental biology.

Animals↗

PubMed2004

Evaluation of an integrated strategy for proteomic profiling of skeletal muscle.

Proteomic analysis of skeletal muscle presents particular challenges when trying to identify valid biomarkers of phenotypic change in small biopsies from genetically diverse human subjects. Currently, two-dimensional (2-D) gel electrophoresis and mass spectrometry are the chosen analytical strategies but 2-D gels are not appropriate for analyzing proteins less than 11 kDa, they can suffer from problems of reproducibility and in routine use are not a viable high-throughput technique. We have evaluated an integrated proteomic strategy employing Ciphergen ProteinChip arrays, one-dimensional polyacrylamide gel electrophoresis and mass spectrometry. Protein fingerprints characteristic of fast and slow contracting muscles from normal and kyphoscoliosis (ky) mutant mice were obtained from Ciphergen protein arrays. Eight statistically validated protein biomarkers have so far been identified capable of discriminating fast from slow muscle. Five of these showed further differential expression in ky versus normal BDL soleus muscles. Several biomarkers have been formally identified, and were myosin light chain isoforms shown previously to be expressed differentially by fast versus slow skeletal muscles. This integrated experimental approach using a model mouse muscle system shows the potential of Ciphergen protein array technology for proteomic analysis of small proteins in small muscle samples and its applicability for phenotypic characterization of skeletal muscle in general.

Animals↗

PubMed2005

Toward functional proteomics of alveolar macrophages.

Alveolar macrophages (AM) belong to a phenotype of macrophages with distinct biological functions and important pathophysiological roles in lung health and disease. The molecular details determining AM differentiation from blood monocytes and AM roles in lung homeostasis are largely unknown. With the use of different technological platforms, advances in the field of proteomics have made it possible to search for differences in protein expression between AM and their precursor monocytes. Proteome features of each cell type provide new clues into understanding mononuclear phagocyte biology. In-depth analyses using subproteomics and subcellular proteomics offer additional information by providing greater protein resolution and detection sensitivity. With the use of proteomic techniques, large-scale mapping of phosphorylation differences between the cell types have become possible. Furthermore, two-dimensional gel proteomics can detect germline protein variants and evaluate the impact of protein polymorphisms on an individual's susceptibility to disease. Finally, surface-enhanced laser desorption and ionization (SELDI) time-of-flight mass spectrometry offers an alternative method to recognizing differences in protein patterns between AM and monocytes or between AM under different pathological conditions. This review details the current status of this field and outlines future directions in functional proteomic analyses of AM and monocytes. Furthermore, this review presents viewpoints of integrating proteomics with translational topics in lung diseases to define the mechanisms of disease and to uncover new diagnostic and therapeutic targets.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2026

Multi-Omics Analysis Reveals Molecular Networks and Key Pathways Associated with Cysteine- and Methionine-Mediated Biosynthesis of Sulfur-Containing Flavor Metabolites in Lentinula edodes.

Lentinula edodes is renowned for its unique aroma, which is characterized by various volatile sulfur-containing flavor metabolites (SCFMs). Cysteine and methionine could enhance the SCFMs biosynthesis in L. edodes; however, the underlying metabolic pathways remain unclear. To bridge this gap, integrated proteomic and metabolomic analysis were performed to decipher pathways through which cysteine and methionine regulate SCFM biosynthesis. Results showed that exogenous cysteine and methionine supplementation significantly increased the content of lenthionine, the key aroma compound of shiitake mushrooms. Both treatments induced substantial changes in the proteomic and metabolomic profiles. Proteomic analysis revealed that differentially expressed proteins were predominantly enriched in cysteine and methionine metabolism and sulfur metabolism following cysteine treatment, whereas methionine treatment mainly affected proteins associated with tryptophan metabolism and sulfur metabolism. Metabolomic analysis showed that differentially accumulated metabolites were significantly enriched in D-amino acid metabolism and cysteine and methionine metabolism, with glutathione metabolism specifically enriched under cysteine treatment. Integrated omics analysis further uncovered distinct sulfur metabolite-protein regulatory networks under different sulfur nutrition and identified treatment-specific hub proteins. These findings establish a molecular regulatory framework linking SCFM biosynthesis with broader primary metabolic pathways involved in sulfur intermediate generation and regulation, providing new insights into the potential regulatory networks underlying SCFM formation in L. edodes.

Methionine↗