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At least 1,315 records · Page 73Linked to original sources
PubMed2004

Global changes in gene expression observed at the transition from growth to stationary phase in Listeria monocytogenes ScottA batch culture.

Listeria monocytogenes is a food-borne Gram-positive bacterium that is responsible for a variety of infections (worldwide) annually. The organism is able to survive a variety of environmental conditions and stresses, however, the mechanisms by which L. monocytogenes adapts to environmental change are yet to be fully elucidated. An understanding of the mechanism(s) by which L. monocytogenes survives unfavourable environmental conditions will aid in developing new food processing methods to control the organism in foodstuffs. We have utilized a proteomic approach to investigate the response of L. monocytogenes batch cultures to the transition from exponential to stationary growth phase. Proteomic analysis showed that batch cultures of L. monocytogenes perceived stress and began preparations for stationary phase much earlier (approximately A(600) = 0.75, mid-exponential) than predicted by growth characteristics alone. Global analysis of the proteome revealed that the expression levels of more than 50% of all proteins observed changed significantly over a 7-9 h period during this transition phase. We have highlighted ten proteins in particular whose expression levels appear to be important in the early onset of the stationary phase. The significance of these findings in terms of functionality and the mechanistic picture are discussed.

Gene Expression↗
PubMed2000

Pharmaceutical proteomics.

Genomics and proteomics are today well established in drug discovery and, in combination with combinatorial chemistry and high-throughput screening, are helping to bring forward an unprecedented number of potential lead compounds. To avoid the generation of bottlenecks downstream in drug development, increasing pressure is arising to integrate these technologies into the development environment. Proteomics has demonstrated proof-of-concept in toxicology as shown by a number of successful applications in mechanistic toxicology and lead selection. The "technology wave" is now starting to impact the clinical phase of drug development. Expected benefits are optimized clinical trials based on the availability of biologically relevant markers of drug efficacy and safety.

Animals↗
PubMed2006

New perspectives on host-parasite interplay by comparative transcriptomic and proteomic analyses of Schistosoma japonicum.

Schistosomiasis remains a serious public health problem with an estimated 200 million people infected in 76 countries. Here we isolated ~ 8,400 potential protein-encoding cDNA contigs from Schistosoma japonicum after sequencing circa 84,000 expressed sequence tags. In tandem, we undertook a high-throughput proteomics approach to characterize the protein expression profiles of a number of developmental stages (cercariae, hepatic schistosomula, female and male adults, eggs, and miracidia) and tissues at the host-parasite interface (eggshell and tegument) by interrogating the protein database deduced from the contigs. Comparative analysis of these transcriptomic and proteomic data, the latter including 3,260 proteins with putative identities, revealed differential expression of genes among the various developmental stages and sexes of S. japonicum and localization of putative secretory and membrane antigens, enzymes, and other gene products on the adult tegument and eggshell, many of which displayed genetic polymorphisms. Numerous S. japonicum genes exhibited high levels of identity with those of their mammalian hosts, whereas many others appeared to be conserved only across the genus Schistosoma or Phylum Platyhelminthes. These findings are expected to provide new insights into the pathophysiology of schistosomiasis and for the development of improved interventions for disease control and will facilitate a more fundamental understanding of schistosome biology, evolution, and the host-parasite interplay.

Amino Acid Sequence↗
PubMed2005

Proteins and protein pattern differences between glioma cell lines and glioblastoma multiforme.

INTRODUCTION: Research into the pathogenesis, molecular signaling, and treatment of glioblastoma multiforme (GBM) has traditionally been conducted using cell lines derived from malignant gliomas. We compared protein expression patterns between solid primary GBMs and GBM cell lines to identify proteins whose expression may be altered in cell culture. METHODS: We cultured cell lines U87, U118, U251, and A172 and used tissue-selective microdissection of eight primary GBMs to obtain pure populations of tumor cells, which we studied using two-dimensional gel electrophoresis (2DGE) and examined using differential expression software. Select protein targets expressed differentially between GBM tumors and GBM cell lines were sequenced using tandem mass spectrometry. RESULTS: Analysis of the primary GBM tumor samples (n = 8) and the GBM cell lines revealed reproducibly similar proteomic patterns for each group, which distinguished tumors from the cell lines. Gels contained up to 500 proteins that were consistently identified in the pH 4 to 7 range. Comparison of proteins identified in the GBM tumors and in the cell lines showed approximately 160 proteins that were gained and 60 proteins that were lost on culture. Using normalized intensity patterns from the 2DGE images, ANOVA tests were done and statistically significant spots were identified. Seven proteins found in the cell lines were significantly increased when compared with the GBM tumors (P < 0.05), whereas 10 proteins were significantly decreased from cell lines compared with the GBM tumors. Proteins identified included transcription factors, tumor suppressor genes, cytoskeletal proteins, and cellular metabolic proteins. CONCLUSION: Global protein and proteomic differences were identified between primary GBM tumor samples and GBM cell lines. The proteins identified by 2DGE analysis elucidate some of the selection pressures of in vitro culture, help accentuate the advantages and limitations of cell culture, and may aid comprehension of gliomagenesis and enhance development of new therapeutics.

Brain Neoplasms↗
PubMed2026

DPAS-Graph: adaptive spatial-feature relation learning for spatial RNA-to-protein prediction and virtual protein profiling.

Paired spatial multi-omics provides a supervised basis for learning RNA-protein correspondence in situ, but predicting protein abundance from spatial transcriptomic data alone remains challenging across tissue contexts and protein panels. Here, we present DPAS-Graph, an adaptive relation-learning framework for spatial RNA-to-protein prediction. Rather than directly merging spatial proximity and transcriptomic similarity as fixed graph priors, DPAS-Graph represents them as two relation channels on a shared edge support and updates their contributions during representation learning for protein prediction. Its Niche-Coupled Field Encoder combines layer-wise edge-relation modeling, intra-branch relation refinement, and cross-branch residual correction to learn spot representations for protein abundance prediction. In a leave-one-dataset-out benchmark across seven paired spatial multi-omics datasets, DPAS-Graph achieved lower aggregate prediction errors and improved spot-level agreement of protein expression profiles, with gains mainly reflected in error-based metrics and PCC-Spot. Spatial autocorrelation and protein-derived domain agreement analyses were further used to characterize the spatial behavior of the predicted protein maps. When applied to external RNA-only spatial sections, DPAS-Graph generated qualitatively interpretable marker-level virtual protein maps, illustrating its use as a complementary tool for protein-level interpretation of transcriptomics-only spatial data.

RNA↗
PubMed2004

Serum protein profiles to identify head and neck cancer.

PURPOSE: New and more consistent biomarkers of head and neck squamous cell carcinoma (HNSCC) are needed to improve early detection of disease and to monitor successful patient management. The purpose of this study was to determine whether a new proteomic technology could correctly identify protein expression profiles for cancer in patient serum samples. EXPERIMENTAL DESIGN: Surface-enhanced laser desorption/ionization-time of flight-mass spectrometry ProteinChip system was used to screen for differentially expressed proteins in serum from 99 patients with HNSCC and 102 normal controls. Protein peak clustering and classification analyses of the surface-enhanced laser desorption/ionization spectral data were performed using the Biomarker Wizard and Biomarker Patterns software (version 3.0), respectively (Ciphergen Biosystems, Fremont, CA). RESULTS: Several proteins, with masses ranging from 2778 to 20800 Da, were differentially expressed between HNSCC and the healthy controls. The serum protein expression profiles were used to develop and train a classification and regression tree algorithm, which reliably achieved a sensitivity of 83.3% and a specificity of 100% in discriminating HNSCC from normal controls. CONCLUSIONS: We propose that this technique has potential for the development of a screening test for the detection of HNSCC.

Adult↗
PubMed2004

Molecular profiling approaches for identifying novel biomarkers.

An unprecedented interest in biomarker development has arisen from the increasing use of genomic information and high-throughput technologies in the field of drug development. Monitoring global cellular responses to perturbation due to disease, drug treatment or toxicity is achieved using molecular profiling methods such as DNA microarrays, proteomics and metabonomics. Unique fingerprints composed of molecular changes are captured and subjected to interpretation with the goal of class discovery, comparison or prediction. Each fingerprint reflects a cumulative response of complex molecular interactions, and if these interactions can be significantly correlated to an end point, the molecular fingerprint may be qualified as a predictive biomarker. Furthermore, in cases where the predictive power of any single response or set of responses is statistically significant, a molecular fingerprint can provide novel information related to the underlying disease biology or mechanism of toxicity. There is an acute need for effective biomarkers in every phase of drug development, from discovery, to preclinical studies, through to clinical trials. The context in which these molecular biomarkers are used will depend upon the nature of the biological problem being addressed. This review will summarise experimental and computational efforts in the field of molecular profiling and discuss the significant challenges in interpreting molecular profiling data and qualifying novel transcriptional biomarkers.

Biomarkers↗
PubMedDate not supplied

Reversed-phase HPLC separation of human serum employing a novel saw-tooth gradient: toward multidimensional proteome analysis.

A novel reversed-phase (RP-) HPLC gradient profile applicable to multidimensional separations of complex protein mixtures is reported. This gradient profile elutes small numbers of proteins from the RP-HPLC column in discrete intervals while minimizing the amount of band broadening between elution intervals and maintaining constant flow through the HPLC column. Eluting the proteins in discrete intervals eases the instrumental requirements necessary for performing multidimensional separations and can be used to aid in the collection of well-defined fractions. The saw-tooth gradient was applied to the successful isolation of albumin from less abundant proteins in whole human serum and provides adequate separation of proteins in a low-molecular weight (LMW) fraction of human serum with resolution comparable to that achieved using a typical linear gradient profile.

Blood Proteins↗
PubMed2026

Integrative Proteomics and Ubiquitomics Reveal on-Targets and off-Targets of PROTAC dBET1.

Proteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules that induce selective degradation of target proteins by hijacking the ubiquitin-proteasome system (UPS). Despite their transformative potential in eliminating disease-associated proteins, comprehensively identifying off-target degradation events remains technically challenging. Here, we employed an integrated proteomic and ubiquitinomic strategy to systematically profile the degradation landscape of the PROTAC molecule dBET1 in Jurkat T cells. By capturing the upstream ubiquitination events&#x2500;which serve as earlier and more sensitive indicators than total protein abundance&#x2500;our approach enabled the identification of previously overlooked off-target candidates. While dBET1 efficiently degraded its canonical BET family targets, our data also revealed the mitochondrial outer membrane protein VDAC1 as a putative off-target, evidenced by its depletion and increased multisite ubiquitination. Notably, our analysis framework enabled site-specific resolution of degradation events within BRD3, revealing preferential ubiquitination at functionally essential bromodomains, suggesting that degron-enriched regions may underlie domain-selective degradation. Additionally, dBET1 treatment was associated with mitochondrial depolarization and calcium homeostasis disruption, defects that we hypothesize may be functionally linked to the observed VDAC1 depletion. Together, this study demonstrates that integrating ubiquitomics provides a superior sensitivity layer for PROTAC safety assessment, capable of uncovering mechanism-based liabilities that escape conventional global proteomic screening.

Humans↗
PubMed2003

The German cDNA network: cDNAs, functional genomics and proteomics.

Among the greatest challenges facing biology today is the exploitation of huge amounts of genomic data, and their conversion into functional information about the proteins encoded. For example, the large-scale cDNA sequencing project of the German cDNA Consortium is providing vast numbers of open reading frames (ORFs) encoding novel proteins of completely unknown function. As a first step towards their characterization we have tagged over 500 of these with the green fluorescent protein (GFP), and examined the subcellular localizations of these fusion proteins in living cells. These data have allowed us to classify the proteins into subcellular groups which determines the next step towards a detailed functional characterization. To make further use of these GFP-tagged constructs, a series of functional assays have been designed and implemented to assess the effect of these novel proteins on processes such as cell growth, cell death, and protein transport. Functional assays with such a large set of molecules is only possible by automation. Therefore, we have developed, and adapted, functional assays for use by robotic liquid handling stations and reading stations. A transport assay allows to identify proteins which localize to distinct organelles of the secretory pathway and have the potential to be new regulators in protein transport, a proliferation assay helps identifying proteins that stimulate or repress mitosis. Further assays to monitor the effects of the proteins in apoptosis and signal transduction pathways are in progress. Integrating the functional information that is generated in the assays with data from expression profiling and further functional genomics and proteomics approaches, will ultimately allow us to identify functional networks of proteins in a morphological context, and will greatly contribute to our understanding of cell function.

Cloning, Molecular↗
PubMed2026

Next-generation brain proteomics: Integrating single-cell, spatial, and multi-omics for clinical biomarker discovery.

The mammalian brain's functional complexity arises from the sophisticated architecture of neurons and glia. This network is essentially defined by its dynamic proteome, which reveals the functional execution underlying neural computation and disease. This review integrates the technological leap in neuroproteomics. It has moved beyond bulk tissue proteome cataloguing to high-sensitivity single-cell and spatial resolution. We detail how next-generation platforms, such as TIMS-PASEF and Orbitrap-Astral, have enabled deeper and faster phenotypic profiling of limited brain samples. However, the proteome coverage remains constrained by dynamic range, sample loss, ionisation bias and incomplete detection of low-abundance regulatory proteins. We further examine how such studies have revealed the proteomic remodelling that drives lineage specification and synaptic plasticity by linking temporal protein expression waves to biological function. Crucially, we delineate the clinical translational trajectory, illustrating how aberrant signatures are verified in cerebrospinal fluid (CSF) and validated in plasma to support precision medicine. Finally, we argue for the necessity of "fused" multi-omics integration and Artificial Intelligence (AI) to decode the non-linear molecular logic of brain pathology.

Humans↗
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↗
PubMed2003

Comparative analysis of expressed sequence tags from Sesamum indicum and Arabidopsis thaliana developing seeds.

Sesame (Sesamum indicum) is an important oilseed crop which produces seeds with 50% oil that have a distinct flavor and contains antioxidant lignans. Because sesame lignans are known to have antioxidant and health-protecting properties, metabolic pathways for lignans have been of interest in developing sesame seeds. As an initial approach to identify genes involved in accumulation of storage products and in the biosynthesis of antioxidant lignans, 3328 expressed sequence tags (ESTs) were obtained from a cDNA library of immature seeds 5-25 days old. ESTs were clustered and analyzed by the BLASTX or FASTAX program against the GenBank NR and Arabidopsis proteome databases. To compare gene expression profiles during development of green and non-green seeds, a comparative analysis was carried out between developing sesame and Arabidopsis seed ESTs. Analyses of these two seed EST sets have helped to identify similar and different gene expression profiles during seed development, and to identify a large number of sesame seed-specific genes. In particular, we have identified EST candidates for genes possibly involved in biosynthesis of sesame lignans, sesamin and sesamolin, and also suggest a possible metabolic pathway for the generation of cofactors required for synthesis of storage lipid in non-green oilseeds. Seed-specific expression of several candidate genes has been confirmed by northern blot analysis.

Arabidopsis↗
PubMed2026

Targeting ALDH2 with Alda-1 to reverse cisplatin resistance in lung adenocarcinoma.

BACKGROUND: Cisplatin resistance remains a major obstacle in lung adenocarcinoma (LUAD) treatment. The role of Aldehyde dehydrogenase 2 (ALDH2), a detoxifying enzyme, in LUAD prognosis and chemoresistance is poorly understood. METHODS: We analyzed ALDH2's prognostic value using clinical cohorts, TCGA, and proteomic data. Cisplatin-resistant cell lines and xenograft models were used to assess the effect of the ALDH2 agonist Alda-1. Molecular mechanisms were investigated via gain/loss-of-function studies. RESULTS: High ALDH2 expression was significantly associated with improved survival in univariate analysis and correlated with a favorable genomic instability profile in LUAD. Pharmacological activation of ALDH2 with Alda-1 restored cisplatin sensitivity in resistant cells and potently enhanced cisplatin's efficacy in vivo. Mechanistically, ALDH2 activation upregulated PKC-&#x3b6;, leading to downregulation of the drug efflux pump MDR1. Proteomic analysis further linked low ALDH2 expression to a pro-chemoresistance signature. CONCLUSION: ALDH2 represents a potential prognostic biomarker associated with favorable outcomes in LUAD, particularly in patients receiving chemotherapy. Its activation via Alda-1 overcomes cisplatin resistance by targeting the PKC-&#x3b6;/MDR1 axis, presenting a novel therapeutic strategy.

Cisplatin↗
PubMed2007

Detection of down-regulated acetaldehyde dehydrogenase 1 in atopic dermatitis patients by two-dimensional electrophoresis.

We conducted the proteomic studies to detect the dysregulated proteins in the atopic dermatitis (AD) proteome obtained from the patient-derived primary cultured fibroblasts. Acetaldehyde dehydrogenase 1 (ALDH1) was detected as being significantly down-regulated at the pH ranges of 6-9 and 4-7. The transcriptional levels of ALDH1, as detected by RT-PCR and real-time PCR, further confirmed the down-regulated phenomena for all the AD-fibroblasts (n = 20). The expression levels of ALDH1 in the whole skin tissue samples were further supported by the results of the primary cultured samples. These findings clearly demonstrate that ALDH1 can be a dermal biomarker for AD disease.

Adult↗
PubMed2005

Proteomic characterization of harvested pseudopodia with differential gel electrophoresis and specific antibodies.

Malignant gliomas (astrocytomas) are lethal tumors that invade the brain. Invasive cell migration is initiated by extension of pseudopodia into interstitial spaces. In this study, U87 glioma cells formed pseudopodia in vitro as cells pushed through 3 microm pores of polycarbonate membranes. Harvesting pseudopodia in a novel two-step method provided material for proteomic analysis. Differences in the protein profiles of pseudopodia and whole cells were found using differential gel electrophoresis (DIGE) and immunoblotting. Proteins from two-dimensional (2D) gels with M(R)'s of 20-100 kDa and pI's of 3.0-10.0 were identified by peptide mass fingerprinting analysis using mass spectrometry. For DIGE, lysates of pseudopodia and whole cells were each labeled with electrophilic forms of fluorescent dyes, Cy3 or Cy5, and analyzed as mixtures. Analysis was repeated with reciprocal labeling. Differences in protein distributions were detected by manual inspection and computer analysis. Topographical digital maps of the scanned gels were used for algorithmic spot matching, normalization of background, quantifying spot differences, and elimination of artifacts. Pseudopodial proteins in Coomassie-stained 2D gels included isoforms of glycolytic enzymes as the largest group, seven of 24 proteins. Peptide mass fingerprint analysis of DIGE gels demonstrated increased isoforms of annexin (Anx) I, AnxII, enolase, pyruvate kinase, and aldolase, and decreased mitochondrial manganese superoxide dismutase and transketolase in pseudopodia. Specific antibodies showed restricted immunoreactivity of the hepatocyte growth factor (HGF) alpha chain to pseudopodia, indicating localization of its active form. Met (the HGF receptor), actin, and total AnxI were increased in pseudopodial lysates on immunoblots. Increased constituents of the pseudopodial proteome in glioma cells, identified in this study as actin, HGF, Met, and isoforms of AnxI, AnxII, and several glycolytic enzymes, represent therapeutic targets to consider for suppression of tumor invasion.

Annexin A1↗
PubMed2005

Combination of two-dimensional electrophoresis and shotgun peptide sequencing in comparative proteomics.

Two-dimensional electrophoresis (2-DE) and shotgun peptide sequencing are the two major technologies to compare the expression profile of proteins, which is also referred to as comparative proteomics or quantitative proteomics. Although the methodologies, such as difference gel electrophoresis for 2-DE and isotope-coded affinity tags for shotgun peptide sequencing, have made rapid progress, these two approaches have their own strengths and weaknesses. Therefore, the combination of the two methodologies is beneficial for the purpose of better comparative proteomics, especially in comprehensive coverage of the proteome and protein information such as post-translational modifications.

Animals↗
PubMed2024

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast.

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Saccharomyces cerevisiae↗