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Results for “Integrated proteomics”

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PubMed2004

bFGF rescues 423-cells from serum starvation-induced apoptosis downstream of activated caspase-3.

Serum withdrawal rapidly induces apoptosis in rat 423-cells, while addition of bFGF results in cell survival. However, surviving cells initially display morphological changes characteristic for apoptotic cells and even process caspases. Active caspase-3 was detected at the single-cell level in those finally bFGF-rescued cells, while mitochondrial integrity was maintained. Generation of cleavage products of caspase targets was confirmed in surviving cells. Proteome analysis indicated multi-faceted survival activities of bFGF including upregulation of inhibitor-of-apoptosis and heat shock protein family members directly interfering with caspases. Our data suggest that the "point-of-no-return" in death-induced cells has to be moved downstream of activated caspase-3.

Animals↗

PubMed2026

Polystyrene microplastics induce auditory neurotoxicity in mammals: Integrated multi-omics profiling reveals oxidative damage and synaptic molecular dysregulation.

Microplastics (MPs) are ubiquitous environmental pollutants, yet their neurotoxic effects on the auditory system remain poorly understood. This study develops an integrated multi-level analytical framework combining auditory neurophysiology, behavioral assessment, tissue biochemistry, transcriptomics, and proteomics to investigate polystyrene (PS)-MPs-induced auditory neurotoxicity in rats. PS-MPs infiltrate the auditory system and significantly impair auditory processing, with central dysfunction emerging earlier and more prominently than peripheral alterations. Multi-omics analyses reveal coordinated suppression of glutamatergic synapse and Wnt signaling pathways in the cochlear nucleus. Mechanistically, PS-MPs perturb the crosstalk between glutamatergic synaptic and Wnt signaling, promoting AMPA receptor (AMPAR) internalization and potentially affecting synaptic plasticity-related processes and neuronal responsiveness. In parallel, PS-MPs trigger oxidative stress, apoptosis, and glial activation, reflecting pronounced neuroinflammatory and redox imbalance. In primary cochlear nucleus neurons (PCNNs), these mechanisms were further validated in vitro, where activation of Wnt signaling by Wnt3a significantly alleviated oxidative injury and reduced AMPAR internalization. Collectively, these findings provide comprehensive preclinical evidence for the neurotoxic potential of MPs and reveal a previously unrecognized PS-MPs-induced auditory neurotoxicity, although further studies are needed for human relevance. Results from the rat model further implicate Wnt-mediated signaling as a potential modulatory pathway underlying MPs-induced synaptic molecular alterations and redox dysfunction.

Animals↗

PubMed2001

Profiling the malaria genome: a gene survey of three species of malaria parasite with comparison to other apicomplexan species.

We have undertaken the first comparative pilot gene discovery analysis of approximately 25,000 random genomic and expressed sequence tags (ESTs) from three species of Plasmodium, the infectious agent that causes malaria. A total of 5482 genome survey sequences (GSSs) and 5582 ESTs were generated from mung bean nuclease (MBN) and cDNA libraries, respectively, of the ANKA line of the rodent malaria parasite Plasmodium berghei, and 10,874 GSSs generated from MBN libraries of the Salvador I and Belem lines of Plasmodium vivax, the most geographically wide-spread human malaria pathogen. These tags, together with 2438 Plasmodium falciparum sequences present in GenBank, were used to perform first-pass assembly and transcript reconstruction, and non-redundant consensus sequence datasets created. The datasets were compared against public protein databases and more than 1000 putative new Plasmodium proteins identified based on sequence similarity. Homologs of previously characterized Plasmodium genes were also identified, increasing the number of P. vivax and P. berghei sequences in public databases at least 10-fold. Comparative studies with other species of Apicomplexa identified interesting homologs of possible therapeutic or diagnostic value. A gene prediction program, Phat, was used to predict probable open reading frames for proteins in all three datasets. Predicted and non-redundant BLAST-matched proteins were submitted to InterPro, an integrated database of protein domains, signatures and families, for functional classification. Thus a partial predicted proteome was created for each species. This first comparative analysis of Plasmodium protein coding sequences represents a valuable resource for further studies on the biology of this important pathogen.

Animals↗

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↗

PubMed2003

Reaction of detoxification mechanisms in suspension cultured spruce cells (Picea abies L. Karst.) to heavy metals in pure mixture and in soil eluates.

UNLABELLED: INTENTION, GOAL, BACKGROUND: The widespread and unconcerned use of chemicals in the past has led to an accumulation of pollutants in our environment. Numerous sites are polluted with a mixture of organic chemicals and heavy metals. The future use of these sites and the safe consumption of groundwater from these areas depends on our ability to assess risk by determining the bioavailability of trace levels of pollutants in the respective soil solutions. Soil eluates containing heavy metals in mixture as well as pure heavy metals in aqueous solution were added to a spruce cell culture to set up such a test system. OBJECTIVE: The present study aims at evaluating the response of cultured spruce cells to heavy metals in aqueous solution, and at characterizing these basic cellular responses as potential biomarkers. METHODS: In order to characterize cell reactions toward heavy metals, spruce cell cultures were incubated with CdSO4 (50 to 500 microM), Na2HAsO4 (1.5 to 80 microM) or PbCl2 (10 to 150 microM). Alternatively, the cells were incubated with a standard heavy metal mixture containing 80 microM Na2HAsO4, 150 microM CdSO4 and 150 microM PbCl2 in medium and with aqueous original soil eluates. Measurement of oxidative stress, antioxidants and basic detoxification enzymes involved in plant defence reactions were performed with the treated cells. RESULTS AND DISCUSSION: After 5 hrs of incubation, the onset of a strong oxidative burst was observed. H2O2 concentrations exceeded 40 microM in the culture media after 20 hrs. Concomitantly, glutathione levels showed drastic changes indicating the influence of the metals and/or the H2O2 on antioxidative systems. Following cadmium treatment, GSH and GSSG were elevated by 50 and 200% above controls. Whereas arsenic doubled GSSG levels, treatment with lead did not cause significant changes. However, a mixture of the metals decreased both metabolites by 50%. The effect of the metals was concentration-dependent and disappeared at high concentrations. Furthermore, strong induction of glutathione S-transferase (GST) subunits was observed and, although no novel subunit was expressed, the rise of a new GST isoform occurred. The most potent inducer of plant defence reactions is cadmium, followed by arsenate and lead in descending order of effectiveness. Counter ions seem to play an important role, e.g. lead chloride influenced the investigated parameters much more than lead acetate. CONCLUSIONS: The investigated metals activate gene expression through signal transduction pathways previously not associated with these metals, which points to new end points for resistance and toxicity testing. Especially a monitoring of GST subunit behaviour together with quantifying the oxidative burst seem to be promising for a biomonitoring concept. The close regulation of plant answers observed may facilitate the setup of an integrated biotest for heavy metal pollution that could be based on enzymological as well as proteome data. RECOMMENDATIONS AND OUTLOOK: Heavy metals cause stress to plant cells and elicit a whole range of answers, although specific for individual metal species. The differences observed in plant answers are suitable to distinguish between metals bioavailable in soil eluates and water samples, however only at concentrations in the microM range. It will be necessary to evaluate the effects on the RNA and transcript level. We recommend that similar plant metabolic end points and enzyme reactions be screened for their suitability as biotest systems.

Biomarkers↗

PubMed2004

Multi-layered representation for cell signaling pathways.

To understand complex signaling pathways and networks, it is necessary to develop a formal and structured representation of the available information in a format suitable for analysis by software tools. Due to the complexity and incompleteness of the current biological knowledge about cell signaling, such a device must be able to represent cellular pathways at differing levels of details, one level of information abstract enough to convey an essential signaling flow while hiding its details and another level of information detailed enough to explain the underlying mechanisms that account for the signaling flow described at a more abstract level. We have defined a formal ontology for cell-signaling events that allows us to describe these cellular pathways at various levels of abstraction. Using this formal representation, ROSPath (reactive oxygen species-mediated signaling pathway) database system has been implemented and made available on the web (rospath.ewha.ac.kr). ROSPath is a database system for reactive oxygen species (ROS)-mediated cell signaling pathways and signaling processes in molecular detail, which facilitates a comprehensive understanding of the regulatory mechanisms in signaling pathways. ROSPath includes growth factor-, stress-, and cytokine-induced signaling pathways containing about 500 unique proteins (mostly mammalian) and their related protein states, protein complexes, protein complex states, signaling interactions, signaling steps, and pathways. It is a web-based structured repository of information on the signaling pathways of interest and provides a means for managing data produced by large-scale and high-throughput techniques such as proteomics. Also, software tools are provided for querying, displaying, and analyzing pathways, thus furnishing an integrated web environment for visualizing and manipulating ROS-mediated cell-signaling events.

Cell Physiological Phenomena↗

PubMed2005

Unsupervised pattern recognition: an introduction to the whys and wherefores of clustering microarray data.

Clustering has become an integral part of microarray data analysis and interpretation. The algorithmic basis of clustering -- the application of unsupervised machine-learning techniques to identify the patterns inherent in a data set -- is well established. This review discusses the biological motivations for and applications of these techniques to integrating gene expression data with other biological information, such as functional annotation, promoter data and proteomic data.

Algorithms↗

PubMed2004

Bayesian analysis of signaling networks governing embryonic stem cell fate decisions.

MOTIVATION: Signaling events that direct mouse embryonic stem (ES) cell self-renewal and differentiation are complex and accordingly difficult to understand in an integrated manner. We address this problem by adapting a Bayesian network learning algorithm to model proteomic signaling data for ES cell fate responses to external cues. Using this model we were able to characterize the signaling pathway influences as quantitative, logic-circuit type interactions. Our experimental dataset includes measurements for 28 signaling protein phosphorylation states across 16 different factorial combinations of cytokine and matrix stimuli as reported previously. RESULTS: The Bayesian network modeling approach allows us to uncover previously reported signaling activities related to mouse ES cell self-renewal, such as the roles of LIF and STAT3 in maintaining undifferentiated ES cell populations. Furthermore, the network predicts novel influences such as between ERK phosphorylation and differentiation, or RAF phosphorylation and differentiated cell proliferation. Visualization of the influences detected by the Bayesian network provides intuition about the underlying physiology of the signaling pathways. We demonstrate that the Bayesian networks can capture the linear, nonlinear and multistate logic interactions that connect extracellular cues, intracellular signals and consequent cell functional responses.

Algorithms↗

PubMed2006

Cluster analysis of networks generated through homology: automatic identification of important protein communities involved in cancer metastasis.

BACKGROUND: Protein-protein interactions have traditionally been studied on a small scale, using classical biochemical methods to investigate the proteins of interest. More recently large-scale methods, such as two-hybrid screens, have been utilised to survey extensive portions of genomes. Current high-throughput approaches have a relatively high rate of errors, whereas in-depth biochemical studies are too expensive and time-consuming to be practical for extensive studies. As a result, there are gaps in our knowledge of many key biological networks, for which computational approaches are particularly suitable. RESULTS: We constructed networks, or 'interactomes', of putative protein-protein interactions in the rat proteome--the rat being an organism extensively used for cancer studies. This was achieved by integrating experimental protein-protein interaction data from many species and translating this data into the reference frame of the rat. The putative rat protein interactions were given confidence scores based on their homology to proteins that have been experimentally observed to interact. The confidence score was furthermore weighted according to the extent of the experimental evidence, giving a higher weight to more frequently observed interactions. The scoring function was subsequently validated and networks constructed around key proteins, identified as being highly up- or down-regulated in rat cell lines of high metastatic potential. Using clustering methods on the networks, we have identified key protein communities involved in cancer metastasis. CONCLUSION: The protein network generation and subsequent network analysis used here, were shown to be useful for highlighting key proteins involved in metastasis. This approach, in conjunction with microarray expression data, can be extended to other species, thereby suggesting possible pathways around proteins of interest.

Algorithms↗

PubMed2000

Detection of Na(+) transporter proteins in urine.

Previous studies have established that the vasopressin-regulated water channel of the collecting duct, aquaporin-2, is excreted in the urine, providing a means for assessment of regulation and dysregulation of aquaporin-2 in humans. This article addresses the hypothesis that membrane transporters from upstream nephron segments are normally detectable in urine. The experiments employed rabbit polyclonal antibodies against the major Na transporters of the proximal tubule (the type 3 Na-H exchanger [NHE3]), the thick ascending limb of Henle's loop (the bumetanide-sensitive Na-K-2Cl cotransporter [NKCC2]), and the distal convoluted tubule (the thiazide-sensitive Na-Cl cotransporter [NCC]) in immunoblotting experiments. All three of these transporters were readily detectable as high molecular weight complexes present in lowdensity membrane fractions from urine of normal rats. Cross linking studies of NHE3, NKCC2, and NCC revealed that high molecular weight complexes are normally present in renal tissue. The molecular weights of the complexes in urine matched those of the cross-linked complexes in native kidney tissue. The presence in urine of integral membrane proteins representative of each nephron segment raises the possibility that limited or comprehensive proteomic analysis of urine samples may be useful in clinical settings.

Animals↗

PubMed2026

2025 Donald Seldin Lecture: Leveraging Diverse Population Genomics and Multiomics Integration for Gene Discovery of Cardiovascular and Kidney Diseases.

This review discusses the implications of frameworks leveraging genetic admixture and multiomics data for advancing gene discovery in cardiovascular and kidney disease research. By broadening gene discovery efforts to additional populations that have a disproportionately high risk of disease and leveraging genetic diversity in admixed populations, studies can identify population-enriched risk variants that traditionally have been missed in genome-wide association studies. The use of multiomics approaches, including the transcriptome, proteome, and metabolome, advances a mechanistic understanding of disease beyond associations. As single-cell omics technologies continue to improve, their integration into gene discovery may help uncover cell-type-specific regulatory pathways and more precise biological contexts. The full potential of these approaches depends on sustained investment in diverse, well-characterized omics data sets, methodological innovation in multiancestry statistical approaches, and interdisciplinary collaboration bridging genomics, epidemiology, and clinical medicine. These efforts will need to be translated into clinically actionable insights, including ancestry-informed risk stratification and targeted therapeutics, to improve outcomes for cardiovascular and kidney diseases.

Humans↗

PubMed2001

Functional proteomics to exploit genome sequences.

The sequencing of various genomes has inaugurated a new stage in the understanding of normal and pathological cell function through the analysis of the role of proteins. Proteins, after all, that intervene in the different molecular mechanisms of life, during growth, reproduction, and in the interaction between cells, thus making it possible to describe the biology of integrated systems. In this article, we briefly describe the various stages in the progression of our knowledge, from the genome to the "functional" proteome. Emphasis is placed on a global approach to the protein-protein interactions used to describe the cellular "interactome".

Biotechnology↗

PubMed2026

Proteins as Regulators of Metabolic Changes in Sepsis: Alterations in Body Fluids, Immune Cells, and Organs through the Eyes of Proteomics.

Sepsis is a life-threatening syndrome characterized by a dysregulated host response to infection and profound metabolic alterations that contribute to immune dysfunction and organ failure. This Review synthesizes proteomic evidence on sepsis-associated alterations in proteins involved in metabolic pathways across circulating biofluids, immune cells, and organs. Across plasma and urine, proteomic studies identify disturbances in lipoprotein-associated pathways, redox homeostasis, mitochondrial function, and substrate metabolism, indicating that protein signatures of metabolic dysregulation are systemic and detectable across biofluids. In immune cells, monocytes and neutrophils, proteomic analyses reveal a shift toward glycolysis with concurrent impairment of mitochondrial pathways alongside phenotype-dependent differences in lipid and redox-related programs. Organ-level studies further show that metabolic responses are heterogeneous, with distinct trajectories in the kidney, heart, liver, lung, skeletal muscle, and brain. These observations support the concept that sepsis involves compartment-specific remodeling of metabolism-associated protein networks rather than a single convergent metabolic state. Proteomics also highlights potential translational opportunities by identifying metabolism-associated proteins linked to disease severity, clinical phenotypes, and biologically distinct patient subgroups, although the current evidence remains largely exploratory and context-dependent. Overall, proteomics provides a complementary framework for understanding the molecular regulation of sepsis-associated metabolic dysfunction and may refine biological stratification and therapeutic targeting, particularly when integrated with longitudinal sampling and multiomic data.

Humans↗

PubMed2026

Multiomic Integration Reveals Novel miRNA-mRNA-Protein Expression Profile in the Aged Female Retina.

PURPOSE: Aging is a leading risk factor for retinal degeneration. MicroRNAs (miRNAs) regulate posttranscriptional gene suppressors and influence inflammation and oxidative stress, two processes disrupted during retinal aging. This study aimed to identify age-related miRNA-mRNA-protein associations between young and older retinas and uncover dysregulated pathways that may contribute to retinal degeneration. METHODS: Retinal function was assessed using electroretinography (ERG), and microgliosis was quantified by microglial immunohistochemistry (IHC). A multiomics approach was used to examine molecular changes in older (30-month-old) female C57BL/6J mouse retinas and compared with young female (3-month-old) controls. Illumina sequencing profiled short miRNAs (20 bp) and bulk mRNAs (150 bp), while total proteomics via mass spectrometry assessed protein expression. Bioinformatic analyses included targetome analysis (miRNet), pathway enrichment (Gene Ontology), and clustering to identify age-associated molecular targets and pathways. RESULTS: Retinas from older mice displayed neuronal dysfunction and increased microgliosis. Sequencing revealed significant dysregulation of miRNAs linked to immune and inflammatory pathways, supported by enrichment of their predicted mRNA targets. In the older mice, mRNA expression showed broad inflammatory activation, though only 14% of dysregulated mRNAs overlapped with predicted miRNA targets. Proteomic profiling revealed a disconnect between RNA and protein expression, yet all omics layers showed enrichment in inflammatory pathways. Integrated analysis identified associations involving several gene regulatory networks in the older retina. CONCLUSIONS: This study demonstrates that at an advanced age, miRNA expression and their predicted downstream regulatory networks are dysregulated, highlighting potential molecular mechanisms underlying age-related retinal degeneration.

Animals↗

PubMed2025

Multi-Omics insights into OsZFP252-OsGA20ox5 mediated drought tolerance in rice through stomatal and vascular regulation.

Rice growth is highly dependent on water availability, and drought stress significantly impacts its entire life cycle. However, previous studies lack systematic investigations into drought-responsive candidate genes across the full life cycle of rice. This study integrates transcriptomic and phenotypic data from two rice lines, IR64 (drought-sensitive) and DK151 (drought-tolerant), under varied environmental conditions at distinct growth stages. Using k-means clustering, 13 369 genes were categorized into 17 distinct expression patterns, revealing drought-responsive genes specifically upregulated or downregulated under drought stress. Weighted co-expression network analysis (WGCNA) further identified four gene modules strongly correlated with drought-related phenotypes, co-localizing 2859 drought-responsive genes through both approaches. Proteomics and metabolomics were supplemented at the booting stage, where phenotypic and transcriptomic differences under drought were most pronounced. Integrated omics results demonstrate gibberellin (GA) and abscisic acid (ABA) pathways play a key role during drought tolerance in rice, and 79 high-confidence drought-resistant candidate genes were prioritized from the 2859 drought-responsive genes. Among these, Gibberellin 20-oxidase 5 (OsGA20ox5) was identified as a key negative regulator of drought tolerance. Furthermore, the transcription factor zinc finger protein 252 (OsZFP252) directly binds to the OsGA20ox5 promoter, repressing its expression and enhancing ABA biosynthesis, thereby improving drought tolerance by increasing stomatal closure and expanding vascular bundle water transport capacity. Notably, the drought-tolerant haplotype 2-4 (Hap2-4) of OsGA20ox5 provides valuable insights for drought-resistant breeding.

Oryza↗

PubMed2005

Proteomic analysis of Rickettsia prowazekii.

Rickettsia prowazekii is an obligate intracellular gram-negative bacterium. Comparative proteomics study of a virulent strain (Breinl) versus an avirulent strain (Madrid E) was performed using an integrated liquid chromatography and mass spectrometer. About 30% of predicted proteins were detected and identified. Among the detected proteins, more than 30 proteins were of unknown function in both strains. Although several proteins were detected in only one strain, the overall distribution of detected proteins in different COGs (clusters of orthologs groups) was very similar between the two strains. Functional analysis of differentially expressed proteins, either qualitatively or quantitatively, may lead to the discovery of pathogenesis-related factors.

Bacterial Proteins↗

PubMedDate not supplied

Proteome analysis of tobacco bright yellow-2 (BY-2) cell culture plastids as a model for undifferentiated heterotrophic plastids.

We analyzed the proteome of undifferentiated plastids from a tobacco BY-2 cell culture by shotgun proteomics following multidimensional protein fractionation. The fractionation strategy initiated with the serial extraction of proteins from membranes which allowed us to distinguish soluble, peripheral, and integral membrane proteins. The majority of the identified proteins have a function in the cellular metabolism and most of them are active in amino acid synthesis pathways. A significant number of the identified proteins was not identified in chloroplast proteome analyses before. This suggests BY-2 plastid specific functions that differ from the major activities of chloroplasts. We have used the BY-2 plastid proteins reported here to assess the metabolic activities of undifferentiated heterotrophic plastids and compared the functional profile with that of differentiated heterotrophic amyloplasts. Comparative shotgun proteome analyses as reported here provide information about prevalent metabolic activities of different plastid types.

Cell Differentiation↗

PubMed2003

Drug resistance mechanisms in cancer cells: a proteomics perspective.

Chemotherapy forms a significant component of the treatment of many human cancers. The failure of tumor cells to respond to the action of cytotoxic drugs is referred to as drug resistance. Mechanisms mediating resistance are multifaceted and often not clearly defined. The challenge of elucidating the link between drug response and resistance, and then integrating the information for the purpose of therapeutic intervention, is a major task that awaits scientists in the post-genomic era. Rapid advances in proteome technologies have made it possible to simultaneously identify multiple proteins involved in drug refractory cancers. This methodology has the potential to isolate novel proteins, including those associated with resistance to specific drugs and those involved in conferring broad resistance to a range of compounds. The identification of key proteins will lead to the possibility of developing molecular, biological or pharmaceutical strategies to modify the action of such proteins when their inappropriate structure or expression is contributing to drug-resistant disease.

Antineoplastic Agents↗