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PubMed2001

Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae.

Genomic and proteomic approaches can provide hypotheses concerning function for the large number of genes predicted from genome sequences. Because of the artificial nature of the assays, however, the information from these high-throughput approaches should be considered with caution. Although it is possible that more meaningful hypotheses could be formulated by integrating the data from various functional genomic and proteomic projects, it has yet to be seen to what extent the data can be correlated and how such integration can be achieved. We developed a 'transcriptome-interactome correlation mapping' strategy to compare the interactions between proteins encoded by genes that belong to common expression-profiling clusters with those between proteins encoded by genes that belong to different clusters. Using this strategy with currently available data sets for Saccharomyces cerevisiae, we provide the first global evidence that genes with similar expression profiles are more likely to encode interacting proteins. We show how this correlation between transcriptome and interactome data can be used to improve the quality of hypotheses based on the information from both approaches. The strategy described here may help to integrate other functional genomic and proteomic data, both in yeast and in higher organisms.

Fungal Proteins↗
PubMed2002

MAPPIT: a cytokine receptor-based two-hybrid method in mammalian cells.

Identifying novel targets for therapy in allergic disease: protein interactions inside the cell Therapy of allergic disease currently relies on pharmacological manipulation of mediators or immunotherapy. Drugs have been developed to target specific mediators and their receptors: for example antihistamines blocking the H1 receptor have been refined to maximize antagonism and reduce central side-effects or adverse effects of activity on other receptors such as muscarinic cholinergic receptors. Traditional pharmacological approaches identify new surface receptors against which chemists will then design or screen compounds for activity: examples are H3 or H4 histamine receptors. With the advent of the sequenced human genome we are faced with a vast array of genes and proteins that interact to define normal physiology or indeed pathology. A major challenge to biotechnology is to evolve novel techniques to understand the function and interaction of these myriad proteins. One particular area of current interest is the signalling cascades downstream of surface receptors. For many years pathways have appeared overlapping and to offer little chance of specific intervention. However, greater understanding of the complexity and integration of signalling, together with the possibility of directing drugs to specific cells has aroused considerable interest in this area for novel therapeutics. Indeed, targeting events within the cell has been done for many years with steroids. Here, Jan Tavernier and colleagues describe some signalling pathways relevant to allergic disease and potential methods for understanding protein interactions that allow mapping of the cascades. In particular they describe an elegant new system of analysis of protein-protein interactions in a mammalian system, which they have developed, termed MAPPIT. The basis of the system is an engineered receptor with JAK kinase but which lacks STAT activation sites. To the cytoplasmic end of the receptor is added a bait protein of interest, and the cell line can then be transduced with plasmid containing 'prey' cDNA from a library of interest linked to an active STAT binding site. If this cDNA encodes a protein which, upon expression, is activated and recruited to the membrane complex, it will bind to the receptor via the bait, then STAT activation will occur and activate a reporter gene system such as luciferase or puromycin resistance. This novel system allows study of known protein-protein interactions by targeted mutagenesis, or screening for novel interactions. It has the advantage over existing systems such as yeast 2 hybrid that it uses mammalian cells and thus can reproduce the physiological conditions for protein processing or activation. As new genes and proteins are linked to the atopic phenotypes, systems such as this hold promise of rapidly defining their function and interacting proteins and may be important in linking genomics and proteomics with function and pharmacology in the future.

Animals↗
PubMed2006

Differential proteomic analysis of nuclear extracts from thyroid cell lines.

Nuclear proteins play a major role in controlling cell functions. Differential proteomic analysis of nuclear proteins by combined 2D gel electrophoresis (2D-E) and mass spectrometry procedures can provide useful information to understand the control of cell proliferation and differentiation. To identify proteins involved in dedifferentiation, we used a differential proteomics approach by comparing nuclear extracts from the differentiated rat thyroid cell line FRTL-5 and the derived undifferentiated Ki-mol cell line, obtained by transformation with the Ki-ras oncogene. Thirteen proteins were identified as differently expressed in the nuclear compartment between the two cell lines. RT-PCR analysis performed on seven differently expressed genes showed that only in two cases the difference may be ascribable to a transcriptional mechanism. Since one of the identified proteins, namely apurinic apyrimidinic endonuclease/redox effector factor-1 (APE1/Ref-1), is suspected to play a role in thyroid tumorigenesis, we used a glutathione S-transferase (GST)-pulldown assay coupled to a 2D electrophoretic/matrix assisted laser desorption ionization-time of flight (MALDI-TOF)-mass spectrometry (MS) analysis to detect and identify its interacting partners. We show here that beta-actin directly interacted with APE1/Ref-1, as confirmed by co-immunoprecipitation assays and that this interaction was enhanced by oxidative stress on FRTL-5 cells.

Animals↗
PubMed1999

Proteome Analysis: A Pathway to the Functional Analysis of Proteins.

The protein equivalent of genomes, proteomes are quantitative protein patterns of an organism, a cell, or a body fluid, and are determined by the development state and environmental parameters. Changes in protein expression and their consequences can be investigated at the molecular level and provide biologically relevant information not obtainable from experiments with mRNA.

Journal Article↗
PubMed2006

Minimum reporting requirements for proteomics: a MIAPE primer.

Amongst other functions, the Human Proteome Organization's Proteomics Standards Initiative (HUPO PSI) facilitates the generation by the proteomics community of guidelines that specify the appropriate level of detail to provide when describing the various components of a proteomics experiment. These guidelines are codified as the MIAPE (Minimum Information About a Proteomics Experiment) specification, the first modules of which are now finalized. This primer describes the structure and scope of MIAPE, places it in context amongst reporting specifications for other domains, briefly discusses related informatics resources and closes by considering the ramifications for the proteomics community.

Databases, Protein↗
PubMed2026

ECLIPSE: exploring the dark proteome of ESKAPE pathogens through the sequence similarity network of the Protein Universe Atlas.

MOTIVATION: The accelerating crisis of antimicrobial resistance among the critical so-called ESKAPE pathogens demands the urgent identification of novel molecular targets. However, a substantial fraction of ESKAPE proteomes remains functionally uncharacterized, with many genes annotated as encoding hypothetical proteins. These protein sequences often lack significant similarity to known protein families when conventional homology-based annotation methods are used and thus remain "dark". This limits our ability to explore their roles in pathogenicity, and it is thus crucial to bridge this substantial gap in pathogen biology by developing new strategies to illuminate these "dark" regions of the ESKAPE pan-proteome. RESULTS: We introduce ECLIPSE (ESKAPE Connectome Linkage and Inference for Proteome Sequence Exploration), a network-based computational framework that systematically identifies and prioritizes functionally dark protein families in ESKAPE pan-proteomes. ECLIPSE embeds target ESKAPE pathogen proteomes within the global sequence similarity network of the Protein Universe Atlas. It detects connected components composed entirely of unannotated proteins, called the "dark proteome." As a case study, we applied ECLIPSE to a pan-proteome of 3 460 657 protein sequences from 635 strains of Pseudomonas aeruginosa (PA). ECLIPSE identified 120 985 proteins (4%) residing in completely dark connected components. Furthermore, we have performed a taxonomic diversity analysis using normalized Shannon indices to characterize each dark component by its enrichment in ESKAPE pathogens. The analysis utilized the evenness (E) value (see Methods 2.1), which distinguishes Pseudomonas-specific (target-specific) from ESKAPE-enriched dark components. We then developed the Dark Proteome Prioritization Score (DPPS), a composite multidimensional scoring framework (see Methods 2.5). It ranks these dark components by biological relevance across four orthogonal axes: (i) functional darkness, (ii) P. aeruginosa proportion in the Atlas, (iii) AMR-clade taxonomic restriction, and (iv) conservation across the 635 P. aeruginosa strains. This framework outputs a robust four-tier scoring system; the prioritized Tier I components were validated by weight sensitivity analysis and remained stable across 500 Monte Carlo weight perturbations. Structural characterization of one of the top-ranked ESKAPE-enriched dark components revealed that it belongs to the beta-barrel fold DUF1302 (PF06980) family, for which no experimentally solved three-dimensional structure exists in the PDB. The genomic context analysis indicates that it is co-localized with a LuxR-type transcriptional regulator. Collectively, ECLIPSE identifies evolutionarily conserved, structurally defined, and functionally dark proteins enriched across ESKAPE pathogens; these dark proteins can further be utilized as alternative antimicrobial targets for experimental characterization. AVAILABILITY AND IMPLEMENTATION: The source code and dataset are available for free at: Github: https://github.com/surabhilata/ECLIPSE.git, Zenodo: DOI: 10.5281/zenodo.21064323.

Proteome↗
PubMed2005

System, trends and perspectives of proteomics in dicot plants Part I: Technologies in proteome establishment.

The first 3 years of the 21st century have seen the impact of plant proteomics on functional genomics that has enhanced our understanding, not only on the plant genome(s), but also more importantly, on the functional aspect of proteins. This is mainly due to availability of the complete genome sequence of the Arabidopsis thaliana-a dicotyledoneous (dicot) model plant-and technological advancements in proteomics. Proteomic analyses of a variety of dicot plants, including both Arabidopsis and the model legume species, barrel medic (Medicago truncatula), have greatly helped in an efficient separation, identification and cataloguing of a large number of proteins, and thereby defining their proteomes. Therefore, we have composed an inclusive review on dicot plant materials, as of February 2004, that provides system, trends and perspectives of proteomics in growth and development and the environment. The review is summarized and discussed as three individual, but interlinked, entities: Part I, technologies in proteome establishment (this review), Part II, proteomes of the complex developmental stages [G.K. Agrawal, M. Yonekura, Y. Iwahashi, H. Iwahashi, R. Rakwal, J. Chromatogr. B (2004)], and Part III, unraveling the proteomes influenced by the environment, and at the levels of function and genetic relationships [G.K. Agrawal, M. Yonekura, Y. Iwahashi, H. Iwahashi, R. Rakwal, J. Chromatogr. B (2004)]. This review deals with the diverse proteomic technologies being used in proteome development of different dicot plants.

Arabidopsis↗
PubMed2006

Mild protease treatment as a small-scale biochemical method for mitochondria purification and proteomic mapping of cytoplasm-exposed mitochondrial proteins.

Because of its importance in basic biology and medicine, great efforts are being devoted to unraveling of the genuine mitochondrial proteome, which is the dynamic protein complement that the organelle uses to maintain its structure and functionality. Several proteomic investigations have now clearly shown that all the purification approaches we have at our disposal suffer from the problem of co-purification; therefore, it is very difficult to distinguish novel mitochondrial proteins from those that are just contaminants of the preparation. The question is further complicated by the fact that the mitochondrial proteome depends on the tissue source. Density gradient centrifugation is the most widespread purification method for obtaining highly pure mitochondrial fractions. The main disadvantage of these methods is the low yield of purified mitochondria that precludes their use in low-scale purifications. Here, we have treated small aliquots of crude mitochondria from mouse liver and from cultured hepatocytes (HEPA1-6) with trypsin under mild proteolysis conditions and have evaluated the suitability of this reaction as a small-scale purification approach. The protease removed several cytoplasmic and endoplasmic reticulum proteins, together with a fraction of mitochondrial proteins that we hypothesize to be associated with the cytosolic face of the outer mitochondrial membrane. The peculiar topology of these mitochondrial proteins could be indicative of their functional roles. Finally, our study represents an application of advanced mass spectrometry technology to the evaluation of biochemical approaches for the treatment of mitochondria.

Animals↗
PubMed2006

Glia maturation factor gamma (GMFG): a cytokine-responsive protein during hematopoietic lineage development and its functional genomics analysis.

Human hematopoiesis was evaluated using the techniques of controlled stem cell differentiation, two-dimensional gel electrophoresis-based proteomics, and functional genomics. We provide the first report that glia maturation factor gamma (GMFG) is a cytokine-responsive protein in erythropoietin-induced and granulocyte-colony stimulating factor-induced hematopoietic lineage development. Results from global functional genomics analysis indicate that GMFG possesses several other features: hematopoietic tissue-specific gene expression, a promoter concentrated with high-score hematopoiesis-specific transcription factors, and possible molecular coevolution with a rudimentary blood/immune system. On the basis of our findings, we hypothesize that GMFG is a hematopoietic-specific protein that may mediate the pluripotentiality and lineage commitment of human hematopoietic stem cells.

Amino Acid Sequence↗
PubMed2025

Proximity Proteomics to Profile Ebola Virus Protein Interactome in Its Functional Context.

Proximity labeling-based proteomics (proximity proteomics) has emerged as a popular and versatile approach to illuminate the molecular interactions between viruses and their hosts. In this approach, a proximity labeling enzyme tag is fused to a bait protein and labels neighboring proteins with a chemical handle such as biotin, allowing for downstream affinity purification. Compared to another widely used technique, affinity purification coupled mass spectrometry, proximity proteomics enables the detection of low affinity or transient interactors that might have important functions in the viral life cycle. Further, proximity proteomics can identify interactors of a labile bait protein, of which affinity purification is technically challenging. Here, we describe a proximity proteomic protocol to identify cellular interactors of the Ebola virus polymerase. A similar strategy is readily applicable to elucidate the virus-host interactions for Marburg virus.

Ebolavirus↗
PubMed2004

New functions of the thylakoid membrane proteome of Arabidopsis thaliana revealed by a simple, fast, and versatile fractionation strategy.

Identification of membrane proteomes remains challenging. Here, we present a simple, fast, and scalable off-line procedure based on three-phase partitioning with butanol to fractionate membrane proteomes in combination with both in-gel and in-solution digestions and mass spectrometry. This should help to further accelerate the field of membrane proteomics. Using this new strategy, we analyzed the salt-stripped thylakoid membrane of chloroplasts of Arabidopsis thaliana. 242 proteins were identified, at least 40% of which are integral membrane proteins. The functions of 86 proteins are unknown; these include proteins with TPR, PPR, rhodanese, and DnaJ domains. These proteins were combined with all known thylakoid proteins and chloroplast (associated) envelope proteins, collected from primary literature, resulting in 714 non-redundant proteins. They were assigned to functional categories using a classification developed for MapMan (Thimm, O., Blasing, O., Gibon, Y., Nagel, A., Meyer, S., Kruger, P., Selbig, J., Muller, L. A., Rhee, S. Y., and Stitt, M. (2004) Plant J. 37, 914-939), updated with information from primary literature. The analysis elucidated the likely location of many membrane proteins, including 190 proteins of unknown function, holding the key to better understanding the two membrane systems. The three-phase partitioning procedure added a new level of dynamic resolution to the known thylakoid proteome. An automated strategy was developed to track possible ambiguous identifications to more than one gene model or family member. Mass spectrometry search results, ambiguities, and functional classifications can be searched via the Plastid Proteome Database.

Amino Acid Sequence↗
PubMed2002

Functional genomics as applied to mapping transcription regulatory networks.

The sequencing of the human genome and the entire genomes of many model organisms has resulted in the identification of many genes. Many large-scale experiments for generating gene disruptions and analyzing the phenotypes are underway to ascertain gene function. A future challenge will be to determine interaction and regulation of all the genes of an organism. Recent advances in functional genomic technology have begun to shine light on such gene network problems at both transcriptomic and proteomic levels. Functional genomics will not only elucidate what the genes do, but will also help determine when, where and how they are expressed as an orchestrated system. In this review, we discuss the functional genomics approaches to extract knowledge about transcription regulatory mechanisms from combinations of sequence data, microarray data and ChIP data. We focus in particular on the budding yeast Saccharomyces cerevisiae.

Gene Expression Regulation, Fungal↗
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↗
PubMed1999

Applied proteomics--analyzing protein structure and function for drug discovery. 27-28 January 1999, London, UK.

This two-day meeting, attended by approximately 60 delegates, was aimed at researchers in the proteomics field. The proteome is defined as the entire protein content of the cell. Proteomics is the analysis of the end-product of gene expression and all regulations governing gene expression are taken into account, ie, transcriptional and translational. The three stages involved in proteomic analysis are: a separation phase, ie, two dimensional (2D) gel electrophoresis; a characterization phase, ie, mass spectrometry; and, a data analysis phase, ie, bioinformatics.

Journal Article↗
PubMed2005

Proteome analysis of the rice etioplast: metabolic and regulatory networks and novel protein functions.

We report an extensive proteome analysis of rice etioplasts, which were highly purified from dark-grown leaves by a novel protocol using Nycodenz density gradient centrifugation. Comparative protein profiling of different cell compartments from leaf tissue demonstrated the purity of the etioplast preparation by the absence of diagnostic marker proteins of other cell compartments. Systematic analysis of the etioplast proteome identified 240 unique proteins that provide new insights into heterotrophic plant metabolism and control of gene expression. They include several new proteins that were not previously known to localize to plastids. The etioplast proteins were compared with proteomes from Arabidopsis chloroplasts and plastid from tobacco Bright Yellow 2 cells. Together with computational structure analyses of proteins without functional annotations, this comparative proteome analysis revealed novel etioplast-specific proteins. These include components of the plastid gene expression machinery such as two RNA helicases, an RNase II-like hydrolytic exonuclease, and a site 2 protease-like metalloprotease all of which were not known previously to localize to the plastid and are indicative for so far unknown regulatory mechanisms of plastid gene expression. All etioplast protein identifications and related data were integrated into a data base that is freely available upon request.

Amino Acid Sequence↗
PubMed2006

A biological approach to computational models of proteomic networks.

Computational modeling is useful as a means to assemble and test what we know about proteins and networks. Models can help address key questions about the measurement, definition and function of proteomic networks. Here, we place these biological questions at the forefront in reviewing the computational strategies that are available to analyze proteomic networks. Recent examples illustrate how models can extract more information from proteomic data, test possible interactions between network proteins and link networks to cellular behavior. No single model can achieve all these goals, however, which is why it is critical to prioritize biological questions before specifying a particular modeling approach.

Computer Simulation↗
PubMedDate not supplied

Proteomic snapshot analyses of preribosomal ribonucleoprotein complexes formed at various stages of ribosome biogenesis in yeast and mammalian cells.

Proteomic technologies powered by advancements in mass spectrometry and bioinformatics and coupled with accumulated genome sequence data allow a comprehensive study of cell function through large-scale and systematic protein identifications of protein constituents of the cell and tissues, as well as of multi-protein complexes that carry out many cellular function in a higher-order network in the cell. One of the most extensively analyzed cellular functions by proteomics is the production of ribosome, the protein-synthesis machinery, in the nucle(ol)us--the main site of ribosome biogenesis. The use of tagged proteins as affinity bait, coupled with mass spectrometric identification, enabled us to isolate synthetic intermediates of ribosomes that might represent snapshots of nascent ribosomes at particular stages of ribosome biogenesis and to identify their constituents--some of which showed dynamic changes for association with the intermediates at various stages of ribosome biogenesis. In this review, in conjunction with the results from yeast cells, our proteomic approach to analyze ribosome biogenesis in mammalian cells is described.

Animals↗
PubMed2004

Proteomics.

The genome sequences of important model systems are available and the focus is now shifting to large-scale experiments enabled by this data. Following in the footsteps of genomics, we have functional genomics, proteomics, and even metabolomics, roughly paralleling the biological hierarchy of the transcription, translation, and production of small molecules. Proteomics is initially concerned with determining the structure, expression, localization, biochemical activity, interactions, and cellular roles of as many proteins as possible. There has been great progress owing to novel instrumentation, experimental strategies, and bioinformatics methods. The area of protein-protein interactions has been especially fruitful. First pass interaction maps of some model organisms exist, and the proteins in many important organelles are about to be determined. Researchers are also beginning to integrate large-scale data sets from various "omics" disciplines in targeted investigations of specific biomedical areas and in pursuit of a general framework for systems biology.

Genomics↗