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PubMed2003

Identification of the p16-Arc subunit of the Arp 2/3 complex as a substrate of MAPK-activated protein kinase 2 by proteomic analysis.

The p38 MAPK pathway regulates multiple neutrophil functional responses via activation of the serine-threonine kinase MAPK-activated protein kinase 2 (MAPKAPK2). To identify substrates of MAPKAPK2 that mediate these responses, a proteomic approach was used in which in vitro phosphorylation of neutrophil lysates by exogenously added active recombinant MAPKAPK2 was followed by protein separation using two-dimensional electrophoresis. Peptide mass fingerprinting of peptides defined by MALDI-MS was then utilized to identify phosphorylated proteins detected by autoradiography. Six candidate substrates were identified, including the p16 subunit of the seven-member Arp2/3 complex (p16-Arc). In vitro studies confirmed that MAPKAPK2 interacts with and phosphorylates the A isoform, but not the B isoform, of p16-Arc with a stoichiometry of 0.6 to 0.7. MAPKAPK2 also phosphorylated p16-Arc in intact Arp2/3 complexes precipitated from neutrophil lysates. Mutation of serine-77 to alanine on the A isoform prevented phosphorylation by MAPKAPK2. The ability of MAPKAPK2 to phosphorylate one isoform of p16-Arc suggests a possible mechanism by which the p38 MAPK cascade regulates remodeling of the actin cytoskeleton.

Actin-Related Protein 2↗

PubMed2006

Genomics and the irreducible nature of eukaryote cells.

Large-scale comparative genomics in harness with proteomics has substantiated fundamental features of eukaryote cellular evolution. The evolutionary trajectory of modern eukaryotes is distinct from that of prokaryotes. Data from many sources give no direct evidence that eukaryotes evolved by genome fusion between archaea and bacteria. Comparative genomics shows that, under certain ecological settings, sequence loss and cellular simplification are common modes of evolution. Subcellular architecture of eukaryote cells is in part a physical-chemical consequence of molecular crowding; subcellular compartmentation with specialized proteomes is required for the efficient functioning of proteins.

Biological Evolution↗

PubMed2006

[Proteomics and breast cancer: new perspectives and limitations].

From differential analysis for the identification of biomarkers, to functional analysis for the evidencing of new therapeutic targets, proteomics brings new comprehensive information for a better understanding of the molecular basis of oncology and new perspectives for the clinic. However the major limitation of proteomic investigations and more generally of post-genomic approaches remains the molecular and cellular complexity of biological systems. This will be illustrated with the case of breast cancer.

Antineoplastic Agents↗

PubMed2006

Analysis of outer membrane proteome of Escherichia coli related to resistance to ampicillin and tetracycline.

The elucidation of the molecular details of antibiotic resistance will lead to improvements in extending the efficacy of current antimicrobials. In the current study, proteomic methodologies were applied to characterize functional outer membrane proteins (Omps) of E. coli K-12 responded to tetracycline and ampicillin resistance for understanding of universal pathways that form barriers for antimicrobial agents. For this purpose, E. coli K-12 expressional outer membrane proteome was characterized and identified with the use of 2-DE and MALDI-TOF/MS methods. Then, differential Omps due to tetracycline or ampcilin resistance were determined by comparison between tetracycline minimum inhibitory concentration (MIC)10, ampicillin MIC10, control0 and control10, showing 9 proteins with 11 spots for tetracycline and 8 protein with 9 spots for ampicillin, showing a difference in only 1 protein (decreased LamB in tetracyclin) between the two antibiotics. Among the proteins, 3 were known as antibiotic-resistant proteins, including TolC, OmpC and YhiU, while FimD precursor, LamB, Tsx, YfiO, OmpW, NlpB were first reported here to be antibiotic-resistance-related proteins. Our findings will be helpful for further understanding of antibiotic-resistant mechanism(s). This study also shows that the combination of Omp purification methods certainly contributes the sensitivity of Omp detection.

Ampicillin↗

PubMed2004

[Proteomic approach in gastrointestinal and liver research].

In the post-genomic era, the focus of research is now moving to functional genomics employing the information on predicted gene products provided by genome sequencing. Proteomics, the global analysis of structures, functions, and interactions of whole cellular proteins, draws the special attention as a tool for documenting the disease pathogenesis or progression. The high-throughput technology has become feasible by considerable improvement of two dimensional electrophoresis and mass fingerprinting. Thus proteome techniques can be used as tools to study the disease processes, develop new biomakers for diagnosis and early detection of diseases, and accelerate drug development. In this review, we discuss the background and techniques of proteomics, and potential applications to the research of gastrointestinal diseases.

Gastrointestinal Diseases↗

PubMed2005

Organotypic cultures as tools for functional screening in the CNS.

A major challenge for the pharmaceutical industry is the development of relevant model systems in which knowledge gained from high-throughput, genomic and proteomic approaches can be integrated to study function. Animal models are still the main choice for such studies but over the past few years powerful new in vitro systems have begun to emerge as useful tools to study function. Organotypic cultures made from slices of explanted tissue represent a complex multi-cellular in vitro environment with the potential to assess biological function and are uniquely placed to act as an important link between high-throughput approaches and animal models.

Animals↗

PubMed2005

Renal and urinary proteomics: current applications and challenges.

During the past few years, proteomics has been extensively applied to various fields of medicine including nephrology. Current applications of renal and urinary proteomics are to better understand renal physiology, to explore the complexity of disease mechanisms, and to identify novel biomarkers and new therapeutic targets. This review provides some examples and perspectives of how proteomics can be applied to nephrology and how experimental data can be linked to physiology, functional significance and clinical applications. In some instances, proteomic analysis can be utilized to generate a new hypothesis from a set of candidates that are obtained from expression studies. The new hypothesis can then be addressed rapidly by conventional molecular biology methods, as demonstrated by identification of an altered renal elastin-elastase system in diabetic nephropathy and alterations in the renal kallikrein-kallistatin pathway in hypoxia-induced hypertension. The strengths and limitations of proteomics in renal research are summarized. Optimization of analytical protocols is required to overcome current limitations. Applications of proteomics to nephrology will then be more fruitful and successful.

Animals↗

PubMed2006

Counting the zinc-proteins encoded in the human genome.

Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, or for regulation of their activities or for structural purposes. Genome sequencing projects have provided a huge number of protein primary sequences, but, even though several different elaborate analyses and annotations have been enabled by a rich and ever-increasing portfolio of bioinformatic tools, metal-binding properties remain difficult to predict as well as to investigate experimentally. Consequently, the present knowledge about metalloproteins is only partial. The present bioinformatic research proposes a strategy to answer the question of how many and which proteins encoded in the human genome may require zinc for their physiological function. This is achieved by a combination of approaches, which include: (i) searching in the proteome for the zinc-binding patterns that, on their turn, are obtained from all available X-ray data; (ii) using libraries of metal-binding protein domains based on multiple sequence alignments of known metalloproteins obtained from the Pfam database; and (iii) mining the annotations of human gene sequences, which are based on any type of information available. It is found that 1684 proteins in the human proteome are independently identified by all three approaches as zinc-proteins, 746 are identified by two, and 777 are identified by only one method. By assuming that all proteins identified by at least two approaches are truly zinc-binding and inspecting the proteins identified by a single method, it can be proposed that ca. 2800 human proteins are potentially zinc-binding in vivo, corresponding to 10% of the human proteome, with an uncertainty of 400 sequences. Available functional information suggests that the large majority of human zinc-binding proteins are involved in the regulation of gene expression. The most abundant class of zinc-binding proteins in humans is that of zinc-fingers, with Cys4 and Cys2His2 being the most common types of coordination environment.

Computational Biology↗

PubMed2007

Molecular portrait of high productivity in recombinant NS0 cells.

Many important therapeutic proteins are produced in recombinant mammalian cells. Upon the introduction of the product gene, the isolated clones typically exhibit a wide range of productivity and high producers are subsequently selected for use in production. Using DNA microarray, two-dimensional gel electrophoresis (2DE), and iTRAQ as global surveying tools, we examined the transcriptome and proteome profiles of 11 lines of NS0 cells producing the same antibody molecule. Genes that are significantly differentially expressed between high and low producer groups statistically fall into a number of functional classes. Their distribution among the functional classes differs somewhat between transcriptomic and proteomic results. Overall, a high degree of consistency between transcriptome and proteome analysis are seen, although some genes exhibiting inconsistent trends between transcript and protein levels were observed as expected. In a novel approach, functional gene networks were retrieved using computational pathway analysis tools and their association with productivity was tested by physiological comprehension of the possible pathways involved in high recombinant protein production. Network analysis indicates that protein synthesis pathways were altered in high producers at both transcriptome and proteome levels, whereas the effect on cell growth/death pathways was more prominent only at the transcript level. The results suggest a common mechanism entailing the alteration of protein synthesis and cell growth control networks leading to high productivity. However, alternate routes with different sets of genes may be invoked to give rise to the same mechanistic outcomes. Such systematic approaches, combining transcriptomic and proteomic tools to examine high and low producers of recombinant mammalian cells will greatly enhance our capability to rationally design high producer cells. This work is a first step towards shedding a new light on the global physiological landscape of hyper productivity of recombinant cells.

Animals↗

PubMed2006

Inner ear proteomics: a fad or hear to stay.

Proteomics, the large-scale analysis of the structure and function of proteins, as well as of protein-protein interactions, has evolved into a major component of 'systems analysis'. This requires the integration of information from different sources and at multiple levels, and involves two distinct parameters, (1) high-throughput protein separation, identification, and characterization, and (2) the extension of the obtained analytical data for the determination of the physiological function. The inner ear poses exceptional challenges to the study of proteomics because of its minute size, poor accessibility, association with complex fluid spaces, and diversity of cell types. Various approaches to the study of proteomics of the inner ear are presented, and success stories, noteworthy failures and what lies ahead, will be discussed.

Animals↗

PubMed2004

Decoupling dynamical systems for pathway identification from metabolic profiles.

RATIONALE: Modern molecular biology is generating data of unprecedented quantity and quality. Particularly exciting for biochemical pathway modeling and proteomics are comprehensive, time-dense profiles of metabolites or proteins that are measurable, for instance, with mass spectrometry, nuclear magnetic resonance or protein kinase phosphorylation. These profiles contain a wealth of information about the structure and dynamics of the pathway or network from which the data were obtained. The retrieval of this information requires a combination of computational methods and mathematical models, which are typically represented as systems of ordinary differential equations. RESULTS: We show that, for the purpose of structure identification, the substitution of differentials with estimated slopes in non-linear network models reduces the coupled system of differential equations to several sets of decoupled algebraic equations, which can be processed efficiently in parallel or sequentially. The estimation of slopes for each time series of the metabolic or proteomic profile is accomplished with a 'universal function' that is computed directly from the data by cross-validated training of an artificial neural network (ANN). CONCLUSIONS: Without preprocessing, the inverse problem of determining structure from metabolic or proteomic profile data is challenging and computationally expensive. The combination of system decoupling and data fitting with universal functions simplifies this inverse problem very significantly. Examples show successful estimations and current limitations of the method. AVAILABILITY: A preliminary Web-based application for ANN smoothing is accessible at http://bioinformatics.musc.edu/webmetabol/. S-systems can be interactively analyzed with the user-friendly freeware PLAS (http://correio.cc.fc.ul.pt/~aenf/plas.html) or with the MATLAB module BSTLab (http://bioinformatics.musc.edu/bstlab/), which is currently being beta-tested.

Algorithms↗

PubMed2005

Plant membrane proteomics.

Plant membrane proteins are involved in many different functions according to their location in the cell. For instance, the chloroplast has two membrane systems, thylakoids and envelope, with specialized membrane proteins for photosynthesis and metabolite and ion transporters, respectively. Although recent advances in sample preparation and analytical techniques have been achieved for the study of membrane proteins, the characterization of these proteins, especially the hydrophobic ones, is still challenging. The present review highlights recent advances in methodologies for identification of plant membrane proteins from purified subcellular structures. The interest of combining several complementary extraction procedures to take into account specific features of membrane proteins is discussed in the light of recent proteomics data, notably for chloroplast envelope, mitochondrial membranes and plasma membrane from Arabidopsis. These examples also illustrate how, on one hand, proteomics can feed bioinformatics for a better definition of prediction tools and, on the other hand, although prediction tools are not 100% reliable, they can give valuable information for biological investigations. In particular, membrane proteomics brings new insights over plant membrane systems, on both the membrane compartment where proteins are working and their putative cellular function.

Arabidopsis↗

PubMed2004

Shaping the mitochondrial proteome.

Mitochondria are eukaryotic organelles that originated from a single bacterial endosymbiosis some 2 billion years ago. The transition from the ancestral endosymbiont to the modern mitochondrion has been accompanied by major changes in its protein content, the so-called proteome. These changes included complete loss of some bacterial pathways, amelioration of others and gain of completely new complexes of eukaryotic origin such as the ATP/ADP translocase and most of the mitochondrial protein import machinery. This renewal of proteins has been so extensive that only 14-16% of modern mitochondrial proteome has an origin that can be traced back to the bacterial endosymbiont. The rest consists of proteins of diverse origin that were eventually recruited to function in the organelle. This shaping of the proteome content reflects the transformation of mitochondria into a highly specialized organelle that, besides ATP production, comprises a variety of functions within the eukaryotic metabolism. Here we review recent advances in the fields of comparative genomics and proteomics that are throwing light on the origin and evolution of the mitochondrial proteome.

Animals↗

PubMed2025

Unraveling Plant Nuclear Envelope Composition Using Proximity Labeling Proteomics.

The nuclear envelope (NE) defines the eukaryotic cell and functions in a myriad of fundamental cellular processes including but not limited to signal transduction, lipid metabolism, chromatin organization, and nucleocytoplasmic transportation. Although the general structure of the NE is well-conserved across eukaryotic kingdoms, its composition and functions vary substantially between species and remain largely unknown in plants. In this chapter, we describe a proximity-labeling-based proteomic approach to profile novel NE components in the model organism Arabidopsis. This method is generally suitable for the identification of protein components in subcellular compartments or protein complexes that are poorly accessible to traditional mass spectrometry approaches and can be easily applied to other plant species. In addition to giving a step-by-step detailed description of the proximity labeling proteomics procedure in plant samples, we also provide guidelines on the appropriate use of controls and statistical analysis to achieve a highly specific selection of probed candidates.

Proteomics↗

PubMed2001

Profiling the specific reactivity of the proteome with non-directed activity-based probes.

BACKGROUND: The field of proteomics aims to characterize dynamics in protein function on a global level. However, several classes of proteins, in particular low abundance proteins, remain difficult to characterize using standard proteomics technologies. Recently, chemical strategies have emerged that profile classes of proteins based on activity rather than quantity, thereby greatly facilitating the analysis of low abundance constituents of the proteome. RESULTS: In order to expand the classes of proteins susceptible to analysis by activity-based methods, we have synthesized a library of biotinylated sulfonate esters and applied its members to complex proteomes under conditions that distinguish patterns of specific protein reactivity. Individual sulfonates exhibited unique profiles of proteome reactivity that in extreme cases appeared nearly orthogonal to one another. A robustly labeled protein was identified as a class I aldehyde dehydrogenase and shown to be irreversibly inhibited by members of the sulfonate library. CONCLUSIONS: Through screening the proteome with a non-directed library of chemical probes, diverse patterns of protein reactivity were uncovered. These probes labeled protein targets based on properties other than abundance, circumventing one of the major challenges facing contemporary proteomics research. Considering further that the probes were found to inhibit a target enzyme's catalytic activity, the methods described herein should facilitate the identification of compounds possessing both selective proteome reactivities and novel bioactivities.

Aldehyde Dehydrogenase↗

PubMed2002

Finding genes for bipolar disorder in the functional genomics era: from convergent functional genomics to phenomics and back.

Psychiatric genetics, while promising to unravel the mechanisms of psychiatric disorders, has proven to be a challenging field. Psychiatric disorders, like other common genetic traits, are complex and heterogeneous. Psychiatric genetics has also suffered from a lack of quantifiable, biology-based phenotypes. However, the field is currently at an opportune moment. The work of various investigators is on the verge of paying rich dividends. Efforts at positional cloning are being greatly accelerated by the fruits of the Human Genome Project. New tools of functional genomics, such as expression profiling and proteomics, are being applied to animal models. These two methods can complement each other in an approach we have termed convergent functional genomics. Lastly, improvements in the measurement of biologically distinct endophenotypes--or phenomic--will lead to a better understanding of the mapping of genes to phenotypes in both animal and human systems.

Journal Article↗

PubMed2002

Metabolic control analysis in drug discovery and disease.

Metabolic control analysis (MCA) provides a quantitative description of substrate flux in response to changes in system parameters of complex enzyme systems. Medical applications of the approach include the following: understanding the threshold effect in the manifestation of metabolic diseases; investigating the gene dose effect of aneuploidy in inducing phenotypic transformation in cancer; correlating the contributions of individual genes and phenotypic characteristics in metabolic disease (e.g., diabetes); identifying candidate enzymes in pathways suitable as targets for cancer therapy; and elucidating the function of "silent" genes by identifying metabolic features shared with genes of known pathways. MCA complements current studies of genomics and proteomics, providing a link between biochemistry and functional genomics that relates the expression of genes and gene products to cellular biochemical and physiological events. Thus, it is an important tool for the study of genotype-phenotype correlations. It allows genes to be ranked according to their importance in controlling and regulating cellular metabolic networks. We can expect that MCA will have an increasing impact on the choice of targets for intervention in drug discovery.

Aneuploidy↗

PubMed2006

The synapse proteome and phosphoproteome: a new paradigm for synapse biology.

Synapse proteomics has recently resulted in a quantum leap in knowledge of the protein composition of brain synapses and its phosphorylation. We now have the first draft picture of the synapse, comprising approximately 1000 proteins. This is not matched by available methods of functional analysis either in reduced systems or in whole animals. Fewer than 20% of synapse proteome proteins have a known function in the nervous system. A concerted effort is required to establish new technical approaches before we can understand the diversity of functions conferred by the synapse proteome on the synapse, the neuron and the animal. This review will highlight this change in knowledge and discuss current technical and interpretative limitations challenged by synapse proteomics.

Animals↗