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At least 1,369 records · Page 76Linked to original sources
PubMed2006

Salt stress in Desulfovibrio vulgaris Hildenborough: an integrated genomics approach.

The ability of Desulfovibrio vulgaris Hildenborough to reduce, and therefore contain, toxic and radioactive metal waste has made all factors that affect the physiology of this organism of great interest. Increased salinity is an important and frequent fluctuation faced by D. vulgaris in its natural habitat. In liquid culture, exposure to excess salt resulted in striking elongation of D. vulgaris cells. Using data from transcriptomics, proteomics, metabolite assays, phospholipid fatty acid profiling, and electron microscopy, we used a systems approach to explore the effects of excess NaCl on D. vulgaris. In this study we demonstrated that import of osmoprotectants, such as glycine betaine and ectoine, is the primary mechanism used by D. vulgaris to counter hyperionic stress. Several efflux systems were also highly up-regulated, as was the ATP synthesis pathway. Increases in the levels of both RNA and DNA helicases suggested that salt stress affected the stability of nucleic acid base pairing. An overall increase in the level of branched fatty acids indicated that there were changes in cell wall fluidity. The immediate response to salt stress included up-regulation of chemotaxis genes, although flagellar biosynthesis was down-regulated. Other down-regulated systems included lactate uptake permeases and ABC transport systems. The results of an extensive NaCl stress analysis were compared with microarray data from a KCl stress analysis, and unlike many other bacteria, D. vulgaris responded similarly to the two stresses. Integration of data from multiple methods allowed us to develop a conceptual model for the salt stress response in D. vulgaris that can be compared to those in other microorganisms.

Bacterial Proteins↗
PubMed2006

Inference of scale-free networks from gene expression time series.

Quantitative time-series observation of gene expression is becoming possible, for example by cell array technology. However, there are no practical methods with which to infer network structures using only observed time-series data. As most computational models of biological networks for continuous time-series data have a high degree of freedom, it is almost impossible to infer the correct structures. On the other hand, it has been reported that some kinds of biological networks, such as gene networks and metabolic pathways, may have scale-free properties. We hypothesize that the architecture of inferred biological network models can be restricted to scale-free networks. We developed an inference algorithm for biological networks using only time-series data by introducing such a restriction. We adopt the S-system as the network model, and a distributed genetic algorithm to optimize models to fit its simulated results to observed time series data. We have tested our algorithm on a case study (simulated data). We compared optimization under no restriction, which allows for a fully connected network, and under the restriction that the total number of links must equal that expected from a scale free network. The restriction reduced both false positive and false negative estimation of the links and also the differences between model simulation and the given time-series data.

Algorithms↗
PubMed2002

Novel approaches to identification of biomarkers for detection of early stage cancer.

Implementation of routine cancer screening accompanied by treatment of early stage disease is paramount to realizing reductions in cancer mortality rates. While morphologic assessment of relevant cells has traditionally been used to identify individuals with cancer, this approach is not feasible to identify cancers at inaccessible sites, such as the ovary or pancreas. For these and many other cancers, cancer mortality remains high, as sensitive and specific screening assays to detect in-situ or early stage disease are as yet unavailable. Identification of novel markers for early identification of cancer is an established priority of the National Cancer Institute. The rapid expansion of genomic-based technologies developed over the last decade, and the development of sensitive and specific blood-based assays for the detection of molecular changes associated with cancer, begin to offer the means for achieving this goal. Below, we review current approaches used in the effort to identify biomarkers appropriate for early cancer detection.

Antibodies, Neoplasm↗
PubMed2001

Chemical genomics: what will it take and who gets to play?

Chemical genomics requires continued advances in combinatorial chemistry, protein biochemistry, miniaturization, automation, and global profiling technology. Although innovation in each of these areas can come from individual academic labs, it will require large, well-funded centers to integrate these components and freely distribute both data and reagents.

Automation↗
PubMed2004

Biomarkers of Alzheimer disease in plasma.

Plasma and serum biochemical markers proposed for Alzheimer disease (AD) are based on pathophysiologic processes such as amyloid plaque formation [amyloid beta-protein (A beta), A beta autoantibodies, platelet amyloid precursor protein (APP) isoforms], inflammation (cytokines), oxidative stress (vitamin E, isoprostanes), lipid metabolism (apolipoprotein E, 24S-hydroxycholesterol), and vascular disease [homocysteine, lipoprotein (a)]. Most proteins or metabolites evaluated in plasma or serum thus far are, at best, biological correlates of AD: levels are statistically different in AD versus controls in some cohorts, but they lack sensitivity or specificity for diagnosis or for tracking response to therapy. Approaches combining panels of existing biomarkers or surveying the range of proteins in plasma (proteomics) show promise for discovering biomarker profiles that are characteristic of AD, yet distinct from nondemented patients or patients with other forms of dementia.

Alzheimer Disease↗
PubMed2026

PDZ-binding kinase promotes ovarian cancer cell proliferation and invasion via CCNB1 regulation.

BACKGROUND: Ovarian cancer is one of the most lethal gynecological malignancies, characterized by late diagnosis, frequent recurrence, and high mortality. PDZ-binding kinase (PBK), a serine/threonine kinase of the mitogen-activated protein kinase kinase (MAPKK) family, has been implicated in the tumorigenesis of multiple cancers, yet its role in ovarian cancer remains incompletely characterized. This study aimed to investigate the effect of PBK on the proliferation and invasion of ovarian cancer cells. METHODS: The expression of PBK and cyclin B1 (CCNB1) in normal ovarian tissues and ovarian cancer tissues was analyzed using online databases including Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Kaplan-Meier Plotter. Clinical tissue specimens were collected to detect the expression of PBK and CCNB1 by immunohistochemistry. Quantitative real-time polymerase chain reaction (PCR) was performed to detect PBK messenger RNA (mRNA) expression levels in clinical specimens and cell lines. Western blot was used to detect PBK protein expression in ovarian cancer cell lines. ES2 and A2780 cells with higher PBK expression were selected to construct PBK knockdown cell lines using lentiviral interference vectors. Cell Counting Kit-8 (CCK-8) assay, colony formation assay, and 5-ethynyl-2'-deoxyuridine (EdU) assay were performed to explore the effect of PBK knockdown on cell proliferation. Transwell assay was used to investigate the effect on cell invasion. The Cancer Genome Atlas (TCGA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were utilized to analyze PBK-related pathways and predict CCNB1 as the gene most closely related to PBK. RESULTS: PBK was significantly overexpressed in ovarian cancer tissues and cell lines compared with normal controls, and high PBK expression was associated with poor overall survival (OS) and progression-free survival (PFS). Knockdown of PBK expression inhibited the proliferation, colony formation, and invasion of ovarian cancer cells. Bioinformatics analysis revealed that CCNB1 was significantly overexpressed in ovarian cancer and high CCNB1 expression was associated with poor OS. CCNB1 was also significantly highly expressed in ovarian cancer tissues as validated by immunohistochemistry and was associated with lymph node metastasis. PBK and CCNB1 expression showed a significant positive correlation in TCGA ovarian cancer datasets. Knockdown of PBK inhibited CCNB1 expression in ovarian cancer cells. CONCLUSIONS: PBK promotes ovarian cancer cell proliferation and invasion. PBK knockdown leads to CCNB1 downregulation. These findings suggest that CCNB1 contributes to PBK-mediated oncogenic effects and identify the PBK-CCNB1 axis as a potential therapeutic target for ovarian cancer treatment.

PDZ-binding kinase (PBK)↗
PubMed2005

Getting sidetracked.

Explore the source record for details and available documents.

Gene Expression Profiling↗
PubMed2005

[Genomic analysis of serine carboxypeptidase-like protein family of Arabidopsis thaliana].

Based on hidden Markov models (HMM), the paper utilized reported SCP (Serine Carboxypeptidases) protein sequences as datasets to build HMM profile. To search Arabidopsis thaliana whole proteome,and identified 54 SCPL (Serine Carboxypeptidase-Like) proteins coding genes. The intron-exon structure, the chromosome mapping and the characteristic of coded protein sequences of those 54 putative genes were analyzed in details, revealing seven gene clusters probably resulted from recent gene duplication. This implied that a remarkable number of Arabidopsis thaliana SCPL genes are harboring alternative splice sites. Phylogenetics evolution analysis suggested 88.9% proteins encoded by Arabidopsis genes belong to two string subfamily of carboxypeptidase, I or II, while only 11.1% proteins fall into single string carboxypeptidase III subfamily. Our results indicated besides the facts that all enzymes of this family contained a central catalytic domain of unique topology and three dimensional structure designated as "alpha/beta hydrolase fold", the DNA and their encoded protein sequences also gave clues to phylogentics studies.

Amino Acid Sequence↗
PubMed2026

Chemogenetic placental activation and proteomic extracellular vesicle signatures predict functional roles across pregnancy and postpartum.

Mechanisms underlying homeostatic regulation of maternal health during pregnancy and the postpartum period are critical yet remain understudied. Extracellular vesicles (EVs) are vital sources of cell-to-cell communication that maintain homeostasis and are at their highest circulating concentration during pregnancy. Recent studies have implicated EVs and their cargo as facilitators in important physiological functions during pregnancy, including glucose and immune regulation, but precise mechanisms are not known. In this study, we aimed to compare changes in EVs and their protein cargo using unbiased proteomic analyses across pregnancy and postpartum periods to assert unique EV functions. As expected, we found significantly higher EV concentrations during pregnancy relative to nonpregnant and postpartum groups. We identified unique EV protein profiles across groups, suggesting EVs were highly responsive to their current environment and performing unique functions. Surprisingly, while postpartum mice had similar EV concentrations as nonpregnant mice, their EVs had the least overlap in protein composition between groups and the greatest number of proteins clustered in a biological function-a significant reduction around cell adhesion processes postpartum. Lastly, to examine a homeostatic role for maternal circulating EVs, we used a novel chemogenetic approach to control dynamic EV secretion and measured changes in maternal glucose regulation. We found that an acute increase in circulating EVs reduced maternal glucose sensitivity, keeping glucose levels elevated longer following a glucose challenge. In summary, these results demonstrate the unique EV protein cargo changes that occur in pregnancy and postpartum and their potential importance in maintenance of maternal health.NEW & NOTEWORTHY Extracellular vesicles in maternal circulation express unique proteomic cargo profiles across pregnancy and postpartum. Chemogenetic activation of the placental secretory pathway releases extracellular vesicles into maternal circulation that influence maternal glucose regulation.

Female↗
PubMed2003

Proteomics in the discovery of new therapeutic targets for psychiatric disease.

In terms of impact on and cost to society psychiatric disorders are among the most important health problems of today. Current estimates from the US suggest that the collective cost of psychiatric diseases could amount to one-third of the total health care budget with a cumulative lifetime prevalence of 30%. While undoubtedly improvements have been made in the diagnosis and treatment of at least the symptoms of mental illness, there has been frustratingly little progress in elucidating the molecular mechanisms. However, a fundamentally different approach to study molecular mechanisms of psychiatric diseases is emerging as a result of technological advances in expression profiling methods. This comprises the investigation of the expressed disease 'phenotypes', developing from the differential gene and protein expression in the central nervous system as a result of the complex interaction between genetic predisposition and environmental modulation. This paper will focus on proteomics, expression profiling at the protein level, reviewing some of the available tools and their application in the molecular analysis of psychiatric disease.

Antipsychotic Agents↗
PubMed2026

Transcriptomic and Proteomic Insights into Mucosal Immune Responses of Asian Seabass (Lates calcarifer) After Sequential Mucosal Vaccination Against Bacterial Pathogens.

Bacterial diseases caused by Flavobacterium covae (Fc), Vibrio harveyi (Vh), Vibrio vulnificus (Vv) and Photobacterium damselae (Pd) seriously constrain Asian seabass aquaculture. Here we dissect the mucosal immune mechanisms engaged by a five-month sequential vaccination strategy that combines nanoemulsion immersion priming with multivalent oral hydrogel boosting. Juvenile seabass were vaccinated, then challenged with F. covae by freshwater immersion and with a Vibrio-Photobacterium (Vh/Vv/Pd) mix by immersion or intraperitoneal injection. Gills were sampled after immersion challenges and intestine after injection, and profiled by RNA sequencing and label-free quantitative proteomics, with selected genes validated by RT-qPCR. Principal component analysis showed clear separation of vaccinated and control fish in all tissues and challenges, indicating a strong and coherent transcriptional reprogramming. Vaccination markedly increased the number of upregulated genes, with Gene Ontology enrichment revealing dominant signatures of ribosome biogenesis, RNA processing, lysosomal organization and immune response. KEGG analysis highlighted cytokine receptor interaction; NOD and Toll-like receptor signaling; oxidative phosphorylation; and phagosome, lysosome and cell adhesion molecule pathways, consistent with heightened antimicrobial readiness. Volcano plots and focused heatmaps showed strong induction of interferon-stimulated genes, cytokines and chemokine receptors, complement components, macrophage mannose receptor, epithelial barrier mediators and numerous immunoglobulin transcripts, with tissue- and challenge-specific patterns. Proteomics corroborated these trends, demonstrating a higher abundance of immunoglobulin heavy chains, complement proteins, cathepsins, heat shock and redox chaperones, ribosomal proteins and cytoskeletal and adhesion regulators in vaccinated mucosae. Integrated pathway mapping linked endothelial adhesion molecules and leukocyte integrins with T cell costimulation networks and an intestinal immune network for immunoglobulin production, including enhanced pIgR-mediated transcytosis. Overall, the sequential vaccination regimen was associated with coordinated transcriptomic and proteomic signatures related to epithelial responses, innate immunity, and humoral immune functions across gill and intestinal tissues. These molecular patterns were accompanied by improved survival following bacterial challenge; however, the present data do not directly demonstrate the functional activity of the inferred immune mechanisms in Asian seabass.

Animals↗
PubMed2000

Relationship between whole proteome aminoacid composition and static DNA curvature.

To study possible relationships between an organism's genomic DNA curvature and the aminoacid composition of its proteome, every peptidic sequence from fully determined genomes was retrotranslated using the E. coli codon preferences, and the curvature profiles of the resulting DNA sequences were calculated and compared. A clear interdependence between these two variables was observed, as each retrotranslated proteome presented a distinctive, statistically significant DNA curvature profile biased toward its natural DNA curvature profile. In addition, by comparing the profiles arising from real and randomly permuted proteomes, we also found a position-dependent contribution of the peptidic sequence to DNA curvature. The implications of these results support the idea of a possible selection toward a specific global curvature of genomes.

Amino Acids↗
PubMed2004

Biological rhythmicity in expressed proteins of the marine dinoflagellate Lingulodinium polyedrum demonstrated by chronological proteomics.

The dinoflagellate Lingulodinium polyedrum shows circadian expression of proteins. Analysis of the expression profile of ca. 900 proteins (pI range 5-8; MW 22,000-120,000) by chronological proteomics in 12:12h light-dark ('day-night') cycles revealed 28 with quantitative circadian changes. The patterns were classified into three types: Phase 1 ('evening'), Phase 2 ('night'), and Phase 3 ('midnight'). Peptide mass fingerprinting identified luciferin-binding protein in Phase 2 and two components of the tricarboxylic acid cycle in Phases 1 and 2. Thus, rhythmicity appears to be related to physiological states and to control the metabolic pathway in L. polyedrum.

Animals↗
PubMed2005

Chronically inflamed synovium from spondyloarthropathy and rheumatoid arthritis investigated by protein expression profiling followed by tandem mass spectrometry.

We investigated the cytosolic proteome of inflamed synovial tissue by hierarchical clustering analysis and validated the feasibility of this proteome analysis by identifying proteins that were differentially expressed between rheumatoid arthritis (RA), spondyloarthropathy (SpA), and osteoarthritis (OA). Synovial biopsy samples were obtained from 18 patients undergoing needle arthroscopy for knee synovitis associated with RA (n = 6) and SpA (n = 6), and for joint effusion of the knee associated with OA (n = 6). Cytosolic proteins were extracted from the tissue and subjected to two-dimensional gel electrophoresis. Protein expression patterns were statistically analyzed and used for hierarchical cluster analysis. Proteins of interest were independently identified by matrix-assisted laser desorption/ionization- and electrospray ionization-mass spectrometry. Hierarchical cluster analysis of the complete match set, containing 640 spots, remarkably segregated SpA from RA and OA. Next, we used a subset of spots that was statistically, differentially expressed (P < 0.01), between RA and SpA, SpA and OA, or RA and OA, in both Student's t-test and Mann-Whitney U-test. The dendrograms revealed distinct clustering of RA versus SpA and RA versus OA. Spots that were differentially expressed between the groups were identified by tandem mass spectrometry. Fructose bisphosphate aldolase A and alpha-enolase showed higher expression levels in SpA than in OA (P < 0.01). Calgranulin A myeloid related protein-8 (MRP-8) was markedly up-regulated in RA and SpA patients in comparison to OA patients where this spot was below detection limit. The analysis of the cytosolic proteome of synovial tissue is a useful approach to identify disease-associated proteins in chronic inflammatory arthritis.

Adult↗
PubMed2005

The molecular make-up of a tumour: proteomics in cancer research.

The enormous progress in proteomics, enabled by recent advances in MS (mass spectrometry), has brought protein analysis back into the limelight of cancer research, reviving old areas as well as opening new fields of study. In this review, we discuss the basic features of proteomic technologies, including the basics of MS, and we consider the main current applications and challenges of proteomics in cancer research, including (i) protein expression profiling of tumours, tumour fluids and tumour cells; (ii) protein microarrays; (iii) mapping of cancer signalling pathways; (iv) pharmacoproteomics; (v) biomarkers for diagnosis, staging and monitoring of the disease and therapeutic response; and (vi) the immune response to cancer. All these applications continue to benefit from further technological advances, such as the development of quantitative proteomics methods, high-resolution, high-speed and high-sensitivity MS, functional protein assays, and advanced bioinformatics for data handling and interpretation. A major challenge will be the integration of proteomics with genomics and metabolomics data and their functional interpretation in conjunction with clinical results and epidemiology.

Biomarkers, Tumor↗