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PubMed2004

The development and application of methods for activity-based protein profiling.

Recent advances in genomic and proteomic technologies have begun to address the challenge of assigning molecular and cellular functions to the numerous protein products encoded by prokaryotic and eukaryotic genomes. In particular, chemical strategies for proteome analysis have emerged that enable profiling of protein activity on a global scale. Herein, we highlight these chemical proteomic methods and their application to the discovery and characterization of disease-related enzyme activities.

Animals↗
PubMed2007

Global gene expression profiling of Bacillus subtilis in response to ammonium and tryptophan starvation as revealed by transcriptome and proteome analysis.

The global gene expression profile of Bacillus subtilis in response to ammonium and tryptophan starvation was analyzed using transcriptomics and proteomics which gained novel insights into these starvation responses. The results demonstrate that both starvation conditions induce specific, overlapping and general starvation responses. The TnrA regulon, the glutamine synthetase (glnA) as well as the sigma(L)-dependent bkd and roc operons were most strongly and specifically induced after ammonium starvation. These are involved in the uptake and utilization of ammonium and alternative nitrogen sources such as amino acids, gamma-aminobutyrate, nitrate/nitrite, uric acid/urea and oligopeptides. In addition, several carbon catabolite-controlled genes (e.g. acsA, citB), the alpha-acetolactate synthase/-decarboxylase alsSD operon and several aminotransferase genes were specifically induced after ammonium starvation. The induction of sigma(F)- and sigma(E)-dependent sporulation proteins at later time points in ammonium-starved cells was accompanied by an increased sporulation frequency. The specific response to tryptophan starvation includes the TRAP-regulated tryptophan biosynthesis genes, some RelA-dependent genes (e.g. adeC, ald) as well as spo0E. Furthermore, we recognized overlapping responses between ammonium and tryptophan starvation (e.g. dat, maeN) as well as the common induction of the CodY and sigma(H) general starvation regulons and the RelA-dependent stringent response. Many genes encoding proteins of so far unknown functions could be assigned to specifically or commonly induced genes.

Ammonium Sulfate↗
PubMed2003

Inhibitor affinity chromatography: profiling the specific reactivity of the proteome with immobilized molecules.

An inhibitor affinity chromatography (IAC) method has been developed for the analysis of inhibitor-protein interactions as a complementary approach to two-dimensional electrophoresis for functional proteomics studies. The procedure was developed utilizing a cyclin-dependent kinase 2 (Cdk2) inhibitor coupled to a polymeric resin and validated using a number of proteins interacting with the inhibitor with different specificities. Cdk2 and the other kinases bound and eluted from the resin in accordance with the relative in vitro potency of the inhibitor for each enzyme. Molecular interactions with the Cdk2 inhibitor were compared for HCT116 cancer cells versus rat pancreatic acinar cells. Proteins interacting with the ligand on the IAC matrix were identified by mass spectrometry. Isothermal calorimetry was used to confirm and quantitatively evaluate the binding affinity of some of the interacting proteins. Heat-shock protein (Hsp) 70 and Hsp27 were the strongest interactors with the inhibitor, displaying binding affinities comparable to those of Cdk2. These results support the use of IAC as a general method for the rapid identification and qualitative evaluation of the in vivo targets and potential side effects of a given drug.

Animals↗
PubMed2026

Polysomal Profiling Coupled to Allele-Specific Proteomics Reveals an EIF4H TranSNP Allele Possessing Higher mRNA Translation Potential.

To search for genetic sources of allele-specific mRNA translation, we leveraged heterozygous polymorphisms and variants present in the exome of HCT116 colorectal adenocarcinoma-derived cells, computing allelic fractions from both total and polysome-associated RNA from RNA-Seq data. Allelic imbalance in polysomal RNA led us to nominate 52 coding variants associated with allele-specific mRNA translation, of which 16 are nonsynonymous. To validate instances of allele-specific translation, a proteomics workflow was developed that combines label-free shotgun analysis, high-pH reversed-phase peptide fractionation, and targeted parallel reaction monitoring using isotope-labeled peptide standards. Using this approach, we provide proof-of-concept validation of the heterozygous G>A, R183H missense single-nucleotide variant rs1554710467 in the eukaryotic initiation factor 4H (EIF4H) gene. The variant is present in two EIF4H alternatively spliced variants, which showed equivalent translation efficiency in HCT116 cells but differ in abundance. The alternative peptide containing H183 was significantly more abundant than the corresponding reference peptide containing R183, consistent with the over-representation of the alternative allele in polysomal RNA in HCT116 cells. A dual-fluorescence ribosome-stalling assay confirmed the enhanced translation potential of the variant allele. The two EIF4H allelic proteins exhibited similar stability and subpolysomal localization. This study demonstrates the feasibility of using allele-specific proteomics at the endogenous protein levels by exploiting heterozygous coding variants. Overall, our approach extends the toolbox available to investigate allele-specific differences in mRNA translation potential, a relatively underexplored layer of gene expression regulation that could reveal interindividual differences in disease-relevant phenotypes.

Humans↗
PubMed2002

Enzyme activity profiles of the secreted and membrane proteome that depict cancer cell invasiveness.

By primarily measuring changes in transcript and protein abundance, conventional genomics and proteomics methods may fail to detect significant posttranslational events that regulate protein activity and, ultimately, cell behavior. To address these limitations, activity-based proteomic technologies that measure dynamics in protein function on a global scale would be of particular value. Here, we describe the application of a chemical proteomics strategy to quantitatively compare enzyme activities across a panel of human breast and melanoma cancer cell lines. A global analysis of the activity, subcellular distribution, and glycosylation state for the serine hydrolase superfamily resulted in the identification of a cluster of proteases, lipases, and esterases that distinguished cancer lines based on tissue of origin. Strikingly, nearly all of these enzyme activities were down-regulated in the most invasive cancer lines examined, which instead up-regulated a distinct set of secreted and membrane-associated enzyme activities. These invasiveness-associated enzymes included urokinase, a secreted serine protease with a recognized role in tumor progression, and a membrane-associated hydrolase KIAA1363, for which no previous link to cancer had been made. Collectively, these results suggest that invasive cancer cells share discrete proteomic signatures that are more reflective of their biological phenotype than cellular heritage, highlighting that a common set of enzymes may support the progression of tumors from a variety of origins and thus represent attractive targets for the diagnosis and treatment of cancer.

Biomarkers, Tumor↗
PubMed2005

The role of expression of the components of proteome in the formation of molecular profile of human ovarian carcinoma A2780 cells sensitive and resistant to cisplatin.

AIM: To study the expression of proteins that characterize drug resistance, proliferation and apoptosis of human ovarian carcinoma cells. METHODS: The study was carried out on human ovarian carcinoma A2780 cells and on the A2780/DDP8 subline resistant to cisplatin. Expression of the surface and intracellular antigens (p53, Bcl-2, CD95, antigen of proliferating cells, metallothioneins, drug resistance proteins (P-glycoprotein (P-gp), glutathione-S-transferase), molecules of adhesion (E-cadherin, alpha- and beta-catenins) was studied by immunocytochemical method. RESULTS: It has been shown that the formation of the resistance to cisplatin in A2780/DDP8 cells is accompanied by the increase of expression of glutathione-S-transferase and Bcl-2, by the decrease of expression of CD95-antigene and proliferation potential of the cells, by appearance of EGF receptors and elevation of expression level of E-cadherin, alpha- and beta-catenins, proving the enhancement of adhesive properties of tumor cells. CONCLUSION: Antiapoptotic program seems to be the leading mechanism of the development of the resistance to cisplatin in A2780/DDP8 cells and is realized via high expression of Bcl-2. During the development of drug resistance of A2780/DDP cells, the program of glutathione detoxification is functionally replacing the decrease of the content of metallothioneins.

Antineoplastic Agents↗
PubMed2005

Liver tumors in wild flatfish: a histopathological, proteomic, and metabolomic study.

Fish play host to viral, bacterial, and parasitic diseases in addition to non-infectious conditions such as cancer. The National Marine Monitoring Programme (NMMP) provides information to the U.K. Government on the health status of marine fish stocks. An aspect of this work relates to the presence of tumors and other pathologies in the liver of the offshore sentinel flatfish species, dab (Limanda limanda). Using internationally agreed quality assurance criteria, tumors and pre-tumors are diagnosed using histopathology. The current study has expanded upon this work by integrating these traditional diagnostic approaches with ones utilizing modern technologies for analysis of proteomic and metabolomic profiles of selected lesions. We have applied SELDI and FT-ICR technologies (for proteomic and metabolomic analyses, respectively) to tumor and non-tumor samples resected from the liver of dab. This combined approach has demonstrated how these technologies are able to identify protein and metabolite profiles that are specific to liver tumors. Using histopathology to classify "analysis groups" is key to the success of such an approach since it allows for elimination of spurious samples (e.g., those containing parasite infections) that may confuse interpretation of "omic" data. As such, the pathology laboratory plays a central role in collating information relating to particular specimens and in establishing sampling groups relative to specific diagnostic questions. In this study, we present pilot data, which illustrates that proteomics and metabolomics can be used to discriminate fish liver tumors and suggest future directions for work of this type.

Adenoma, Liver Cell↗
PubMed2005

Phosphoprotein profiling of erythropoietin receptor- dependent pathways using different proteomic strategies.

Proteomic techniques provide new tools for the global analysis of protein profiles but also for the investigation of specific protein functions. The analysis of signaling cascades has traditionally been performed by the determination of enzymatic or transcription factor activities representing a certain pathway. Functional proteomics now allows more comprehensive approaches to study cellular responses induced during ligand/receptor interactions. In this study we evaluated proteomic strategies for the investigation of structure-function relationships in the erythropoietin receptor signalling complex. After expression of epidermal growth factor/erythropoietin receptor mutant molecules in an identical cellular background we characterized their potential to induce cellular activities. Using this system we focused our efforts on post-translational modifications of signalling proteins reflecting a substantial part of receptor-dependent signaling events. Although tyrosine phosphorylated proteins were enriched by immunoprecipitation the analysis using the classical approach combining two-dimensional gel electrophoresis and identification by matrix assisted laser desorption/ionization-time of flight-mass spectrometry revealed that low expressed signaling proteins cannot be detected by this technique. An alternative strategy using one-dimensional gel separation of phosphoproteins and liquid chromatography-tandem mass spectrometry, however, allowed us to identify multiple proteins involved in intracellular signalling representing already established pathways but also proteins which have not been linked to EPO-induced signaling so far. This approach offers the potential to extend functional proteomic studies to complex signaling processes.

Animals↗
PubMed2002

Functional proteomics of breast cancer for signal pathway profiling and target discovery.

The near completion of human genome sequencing and the introduction of mass spectrometry combined with advanced bioinformatics for protein identification have led to the emergence of proteomics as a powerful tool for characterizing new markers and therapeutic targets. Breast cancer proteomics has already identified proteins of potential clinical interest, such as the molecular chaperone 14-3-3 sigma and the heat shock protein HSP90, and technological innovations such as large scale and high throughput analysis are now driving the field. Methods in functional proteomics have also been developed to study the intracellular signaling pathways that underlie the development of breast cancer cells. As illustrated by fibroblast growth factor-2 and the H19 noncoding oncogenic mRNA, proteomics is a pertinent approach to identify signaling proteins and to decipher the complex signaling circuitry involved in tumor growth and metastasis. Together with genomics, proteomics is now providing a way to define molecular processes involved in breast carcinogenesis and to identify new therapeutic targets. The next challenge will be the introduction of proteomics as a tool for the clinic, for the establishment of diagnosis, prognosis, and the monitoring of treatment; however, this ambitious goal still requires further technological progress in the field.

Breast Neoplasms↗
PubMed2005

A proteomics approach to identify changes in protein profiles in pre-cancerous colon.

The development of colon cancer is characterised by alterations in multiple genetic and epigenetic pathways in colon tissue leading ultimately to deregulation of colon epithelial cells. Early detection is an important factor in decreasing colon cancer deaths. Proteomic techniques were used to identify potential early markers in colon tissue exhibiting pre-cancerous activity that may characterise pathological changes in a chemically induced colon cancer rat model. Protein profiles were assessed in soluble and insoluble fractions prepared from distal colon of rats treated with the colonotropic carcinogen, dimethylhydrazine. Alterations in protein profiles were associated with the presence of aberrant crypt foci, hyperplasia and dysplasia, microanatomical changes, and metabolic changes in rat colon. These changes may have a potential role in the identification of pre-pathological features preceding colon tumorigenesis.

Animals↗
PubMed2004

Translational profiling: the genome-wide measure of the nascent proteome.

Translation in eukaryotic cells is both physically and temporally separated from transcription. This provides cells with extended options to alter their proteome: (1) directly, by synchronizing translation with an altering transcriptional profile; (2) by imposing a changed translational control over transcripts already present in the transcriptome; or (3) by a combination of (1) and (2). In this paper, recent findings in the controlled translation of the transcriptome using microarray analyses are reviewed. A guide to the current technologies and data analysis is also provided, and future directions in the study of translational control as the interface between the transcriptome and the proteome are outlined. This survey is focused on the yeast Saccharomyces cerevisiae, but the topics covered have universal relevance to the control of translation in eukaryotic cells.

Gene Expression Profiling↗
PubMed2002

DNA microarrays for functional plant genomics.

DNA microarray technology is a key element in today's functional genomics toolbox. The power of the method lies in miniaturization, automation and parallelism permitting large-scale and genome-wide acquisition of quantitative biological information from multiple samples. DNA microarrays are currently fabricated and assayed by two main approaches involving either in situ synthesis of oligonucleotides ('oligonucleotide microarrays') or deposition of pre-synthesized DNA fragments ('cDNA microarrays') on solid surfaces. To date, the main applications of microarrays are in comprehensive, simultaneous gene expression monitoring and in DNA variation analyses for the identification and genotyping of mutations and polymorphisms. Already at a relatively early stage of its application in plant science, microarrays are being utilized to examine a range of biological issues including the circadian clock, plant defence, environmental stress responses, fruit ripening, phytochrome A signalling, seed development and nitrate assimilation. Novel insights are obtained into the molecular mechanisms co-ordinating metabolic pathways, regulatory and signalling networks. Exciting new information will be gained in the years to come not only from genome-wide expression analyses on a few model plant species, but also from extensive studies of less thoroughly studied species on a more limited scale. The value of microarray technology to our understanding of living processes will depend both on the amount of data to be generated and on its clever exploration and integration with other biological knowledge arising from complementary functional genomics tools for 'profiling' the genome, proteome, metabolome and phenome.

Gene Expression Profiling↗
PubMed2026

The molecular similarity landscape of preclinical cancer models to patient tumors.

Selecting appropriate preclinical models is fundamental for translational oncology, yet a large-scale, multi-omic quantitative comparison of their similarity to primary human tumors is lacking. To address this, we integrated transcriptomic, proteomic, and genomic profiles from over 10,000 primary tumors from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), alongside 4,000 preclinical models. Using a robust computational framework, we revealed a clear hierarchy of transcriptomic and proteomic similarity to patient tumors: with patient-dervied xenografts (PDXs) having greater transcriptomic and proteomic similarity to patient tumors (>) compared with patient-derived organoids (PDOs), which are equal in hierarchy to that of PDX-dervied organoids (PDXOs) > cell lines. We also quantified high molecular conservation (Pearson correlation coefficient = 0.96) across paired in vitro to in vivo platform (organoids to PDX) transitions. Furthermore, genomic analysis demonstrated that whole-exome sequencing (WES) outperforms RNA-seq in detecting DNA variants, and it identified a clonal complexity hierarchy (cell lines > PDXOs > PDXs > PDOs) reflecting the effect of passaging history on intratumor heterogeneity. Ultimately, this study delivers a comprehensive quantitative benchmark, establishing a population-level hierarchy of molecular similarity between preclinical models and primary tumors and providing a data-driven reference for model selection. These findings offer a data-driven framework for selecting models that balance biological representativeness with experimental practicality.

Humans↗
PubMed2025

Spatiotemporally resolved GPCR interactome uncovers unique mediators of receptor agonism.

Cellular signaling by membrane G protein-coupled receptors (GPCRs) is governed by a complex and diverse array of mechanisms. The dynamics of a GPCR interactome, as it evolves over time and space in response to an agonist, provide a unique perspective on pleiotropic signaling decoding and functional selectivity at the cellular level. In this study, we utilized proximity-based APEX2 proteomics to investigate the interaction network of the luteinizing hormone receptor (LHR) on a minute-to-minute timescale. We developed an analytical approach that integrates quantitative multiplexed proteomics with temporal reference profiles, creating a platform to identify the proteomic environment of APEX2-tagged LHR at the nanometer scale. LHR activity is finely regulated spatially, leading to the identification of putative interactors, including the Ras-related GTPase RAP2B, which modulate both receptor signaling and post-endocytic trafficking. This work provides a valuable resource for spatiotemporal nanodomain mapping of LHR interactors across subcellular compartments.

Humans↗
PubMed2026

Multi-omic signatures of genetic mechanisms inform on type 2 diabetes biology and patient heterogeneity.

Type 2 diabetes (T2D) is a heterogeneous disease shaped by genetic pathways related to insulin resistance and β-cell dysfunction, but how this heterogeneity is reflected molecularly remains unclear. We integrated partitioned polygenic scores (pPS) with proteomic and metabolomic profiling to define molecular signatures of T2D and their clinical relevance. We analyzed UK Biobank participants with genomic, proteomic, and metabolomic data. In a disease-free training subset, we used LASSO regression to identify multi-omic signatures associated with each pPS by jointly modeling proteins and metabolites. In an independent testing set, we constructed multi-omic scores and examined their associations with clinical traits and diabetes-related outcomes. Mediation analyses were used to investigate putative causal pathways. Key findings were evaluated in the Multi-Ethnic Study of Atherosclerosis (MESA). We identified distinct multi-omic signatures that capture the molecular architecture of T2D genetic risk across physiological subtypes. Compared with genetic scores alone, multi-omic pPS showed larger effect sizes and better disease discrimination. These scores recapitulated subtype-specific physiology and were associated with T2D risk. The Beta-Cell 2 multi-omic score showed marked stratification for insulin use, which was replicated in MESA, where it also predicted future insulin use. Mediation analyses implicated lipoprotein remodeling and fatty acid metabolism in the Lipodystrophy 1 cluster, accounting for 30-45% of the total effect of pPS on T2D risk. Integrating process-specific genetic risk with circulating multi-omic profiles reveals biologically distinct endotypes of T2D and supports a framework for improved patient stratification and risk assessment.

Journal Article↗
PubMedDate not supplied

Urinary bladder tumor markers.

Bladder cancer is amenable to biomarker development because many tumor-associated molecules are secreted in urine. Tumor cells are shed in urine, and, therefore, tests that detect tumor cell-surface markers have also been developed to diagnose bladder cancer and monitor its recurrence. Several bladder tumor markers show higher sensitivity than cytology, but most have lower specificity. In addition to markers that use conventional technologies such as enzyme-linked immunosorbent assay, point-of-care devices, reverse transcriptase polymerase chain reaction, fluorescent in situ hybridization, and immunocytochemistry, proteomic and gene profiling approaches are being used to find new biomarkers to assist in the molecular profiling of bladder cancer. This review describes both new and well-studied bladder tumor markers.

Biomarkers, Tumor↗
PubMed2004

Global analysis of predicted proteomes: functional adaptation of physical properties.

The physical characteristics of proteins are fundamentally important in organismal function. We used the complete predicted proteomes of >100 organisms spanning the three domains of life to investigate the comparative biology and evolution of proteomes. Theoretical 2D gels were constructed with axes of protein mass and charge (pI) and converted to density estimates comparable across all types and sizes of proteome. We asked whether we could detect general patterns of proteome conservation and variation. The overall pattern of theoretical 2D gels was strongly conserved across all life forms. Nevertheless, coevolved replicons from the same organism (different chromosomes or plasmid and host chromosomes) encode proteomes more similar to each other than those from different organisms. Furthermore, there was disparity between the membrane and nonmembrane subproteomes within organisms (proteins of membrane proteomes are on the average more basic and heavier) and their variation across organisms, suggesting that membrane proteomes evolve most rapidly. Experimentally, a significant positive relationship independent of phylogeny was found between the predicted proteome and Biolog profile, a measure associated with the ecological niche. Finally, we show that, for the smallest and most alkaline proteomes, there is a negative relationship between proteome size and basicity. This relationship is not adequately explained by AT bias at the DNA sequence level. Together, these data provide evidence of functional adaptation in the properties of complete proteomes.

Animals↗
PubMed2026

Spatial multiomics in biomedical research: advances beyond transcriptomics.

Coordinated changes in gene expression, epigenetic regulation, protein and metabolic activities together drive disease progression and determine clinical outcomes. While spatially resolved transcriptomics has been widely adopted across biomedical fields, it offers an incomplete picture limited to transcriptomic levels. Here, we survey the latest developments in spatial multiomics technologies, with particular emphasis on platforms that extend beyond conventional transcriptomics and profile genomics, epigenomics, proteomics, or metabolomics within intact tissues. These approaches are rapidly becoming commercialized, and here we highlight major technical breakthroughs, enhanced sample compatibility, emerging applications, and computational tools for data analysis. This Review aims to equip researchers with a clear understanding of the current technological landscape and to accelerate the adoption of spatial multiomics methods in biomedical research.

Humans↗