Showing papers on "Proteomics published in 2010"
TL;DR: The analysis here suggests that state stem cell funding programs are sufficiently large and established that simply ending the programs, at least in the absence of substantial investment in the field by other funding sources, could have deleterious effects.
Abstract: 1. Anonymous. Nat. Biotechnol. 28, 987 (2010). 2. Plosila, W.H. Econ. Dev. Q. 18, 113–126 (2004). 3. Stayn, S. BNA Med. Law Pol. Rep. 5, 718–725 (2006). 4. Lomax, G. & Stayn, S. BNA Med. Law Pol. Rep. 7, 695–698 (2008). 5. Levine, A.D. Public Adm. Rev. 68, 681–694 (2008). 6. Levine, A.D. Nat. Biotechnol. 24, 865–866 (2006). 7. McCormick, J.B., Owen-Smith, J. & Scott, C.T. Cell Stem Cell 4, 107–110 (2009). 8. Fossett, J.W., Ouellette, A.R., Philpott, S., Magnus, D. & Mcgee, G. Hastings Cent. Rep. 37, 24–35 (2007). 9. Mintrom, M. Publius 39, 606–631 (2009). 10. Scott, C.T., McCormick, J.B. & Owen-Smith, J. Nat. Biotechnol. 27, 696–697 (2009). 11. Takahashi, K. & Yamanaka, S. Cell 126, 663–676 (2006). Foundation and the Georgia Research Alliance, and Georgia Tech. They thank J. Walsh at Georgia Tech for helpful comments on an earlier version of this manuscript. They also appreciate the assistance they received with data collection from officials in various state stem cell agencies. A.D.L. would also like to thank A. Jakimo, whose comment at a meeting of the Interstate Alliance on Stem Cell Research inspired collection of these data. stem cell programs, as well as similar state programs supporting other areas of science, is uncertain. The analysis here suggests that state stem cell funding programs are sufficiently large and established that simply ending the programs, at least in the absence of substantial investment in the field by other funding sources, could have deleterious effects. Such action would fail to capitalize on the initial efforts of scientists who have been drawn to the field of stem cell research by state programs and leave many stem cell scientists suddenly searching for funding to continue their research. Large-scale state funding for basic research is a relatively new phenomenon, and many questions remain about the impact of these programs on the development of scientific fields and the careers of scientists. The influence of state funding programs on the distribution of research publications, the acquisition of future external funding, the creation of new companies and the translation of basic research into medical practice, for instance, are important unanswered questions. Similarly, comparing state funding programs with federal funding programs as well as foundations could offer new insight into the relative priorities of different funding bodies and the extent to which their funding portfolios overlap or are distinct. We hope the analysis presented here and the public release of the underlying database will inspire additional analysis of state science funding programs generally and state-funded stem cell science in particular.
2,509 citations
TL;DR: The data suggest that the "typical" phosphoprotein is widely expressed yet displays variable, often tissue-specific phosphorylation that tunes protein activity to the specific needs of each tissue, and is offered as an online resource for the biological research community.
1,797 citations
TL;DR: High-resolution mass spectrometry–based proteomics was applied to investigate the proteome and phosphoproteome of the human cell cycle on a global scale and quantified 6027 proteins and 20,443 unique phosphorylation sites and their dynamics, finding that nuclear proteins and proteins involved in regulating metabolic processes have high phosphorylated site occupancy in mitosis, suggesting that these proteins may be inactivated by phosphorylate in mitotic cells.
Abstract: Eukaryotic cells replicate by a complex series of evolutionarily conserved events that are tightly regulated at defined stages of the cell division cycle. Progression through this cycle involves a large number of dedicated protein complexes and signaling pathways, and deregulation of this process is implicated in tumorigenesis. We applied high-resolution mass spectrometry-based proteomics to investigate the proteome and phosphoproteome of the human cell cycle on a global scale and quantified 6027 proteins and 20,443 unique phosphorylation sites and their dynamics. Co-regulated proteins and phosphorylation sites were grouped according to their cell cycle kinetics and compared to publicly available messenger RNA microarray data. Most detected phosphorylation sites and more than 20% of all quantified proteins showed substantial regulation, mainly in mitotic cells. Kinase-motif analysis revealed global activation during S phase of the DNA damage response network, which was mediated by phosphorylation by ATM or ATR or DNA-dependent protein kinases. We determined site-specific stoichiometry of more than 5000 sites and found that most of the up-regulated sites phosphorylated by cyclin-dependent kinase 1 (CDK1) or CDK2 were almost fully phosphorylated in mitotic cells. In particular, nuclear proteins and proteins involved in regulating metabolic processes have high phosphorylation site occupancy in mitosis. This suggests that these proteins may be inactivated by phosphorylation in mitotic cells.
1,581 citations
TL;DR: The authors' data reveal a highly adapted interplay between chromatin marks and their associated protein complexes, and reading specific trimethyl-lysine sites by specialized complexes appears to be a widespread mechanism to mediate gene expression.
837 citations
TL;DR: The technologies of these label-free quantitative methods, statistics, available computational software, and their applications in complex proteomics studies are discussed.
Abstract: In order to study the differential protein expression in complex biological samples, strategies for rapid, highly reproducible and accurate quantification are necessary. Isotope labeling and fluorescent labeling techniques have been widely used in quantitative proteomics research. However, researchers are increasingly turning to label-free shotgun proteomics techniques for faster, cleaner, and simpler results. Mass spectrometry-based label-free quantitative proteomics falls into two general categories. In the first are the measurements of changes in chromatographic ion intensity such as peptide peak areas or peak heights. The second is based on the spectral counting of identified proteins. In this paper, we will discuss the technologies of these label-free quantitative methods, statistics, available computational software, and their applications in complex proteomics studies.
717 citations
TL;DR: This review concludes that single cell analysis is the new frontier in omics, and single cell omics has the potential to transform systems biology through new discoveries derived from cellular heterogeneity.
688 citations
TL;DR: Several hundred proteins become insoluble and aggregation-prone as a consequence of aging in Caenorhabditis elegans and indicate that these proteins influence disease-related protein aggregation and toxicity.
Abstract: Aberrant protein aggregation is a hallmark of many age-related diseases, yet little is known about whether proteins aggregate with age in a non-disease setting. Using a systematic proteomics approach, we identified several hundred proteins that become more insoluble with age in the multicellular organism Caenorhabditis elegans. These proteins are predicted to be significantly enriched in beta-sheets, which promote disease protein aggregation. Strikingly, these insoluble proteins are highly over-represented in aggregates found in human neurodegeneration. We examined several of these proteins in vivo and confirmed their propensity to aggregate with age. Different proteins aggregated in different tissues and cellular compartments. Protein insolubility and aggregation were significantly delayed or even halted by reduced insulin/IGF-1-signaling, which also slows aging. We found a significant overlap between proteins that become insoluble and proteins that influence lifespan and/or polyglutamine-repeat aggregation. Moreover, overexpressing one aggregating protein enhanced polyglutamine-repeat pathology. Together our findings indicate that widespread protein insolubility and aggregation is an inherent part of aging and that it may influence both lifespan and neurodegenerative disease.
655 citations
TL;DR: Current studies focus on phosphorylation, but acetylation, methylation, glycosylation and ubiquitylation are also becoming amenable to investigation and will fundamentally change the understanding of signalling networks.
Abstract: Signalling networks regulate essentially all of the biology of cells and organisms in normal and disease states. Signalling is often studied using antibody-based techniques such as western blots. Large-scale 'precision proteomics' based on mass spectrometry now enables the system-wide characterization of signalling events at the levels of post-translational modifications, protein-protein interactions and changes in protein expression. This technology delivers accurate and unbiased information about the quantitative changes of thousands of proteins and their modifications in response to any perturbation. Current studies focus on phosphorylation, but acetylation, methylation, glycosylation and ubiquitylation are also becoming amenable to investigation. Large-scale proteomics-based signalling research will fundamentally change our understanding of signalling networks.
623 citations
Journal Article•
TL;DR: Wang et al. as discussed by the authors described the single cell analysis as the new frontier in Omics, and single cell Omics has the potential to transform systems biology through new discoveries derived from cellular heterogeneity.
Abstract: Single cell analysis: the new frontier in ‘Omics’ Daojing Wang 1 and Steven Bodovitz 2 1. Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 2. BioPerspectives, San Francisco, CA Corresponding author: Wang, D. (djwang@lbl.gov) Cellular heterogeneity arising from stochastic expression of genes, proteins, and metabolites is a fundamental principle of cell biology, but single cell analysis has been beyond the capabilities of ‘Omics’ technologies. This is rapidly changing with the recent examples of single cell genomics, transcriptomics, proteomics, and metabolomics. The rate of change is expected to accelerate owing to emerging technologies that range from micro/nanofluidics to microfabricated interfaces for mass spectrometry to third- and fourth-generation automated DNA sequencers. As described in this review, single cell analysis is the new frontier in Omics, and single cell Omics has the potential to transform systems biology through new discoveries derived from cellular heterogeneity. Single cell analysis: needs and applications Cellular heterogeneity Cellular heterogeneity within an isogenic cell population is a widespread event [1, 2]. Stochastic gene and protein expression at the single cell level has been clearly demonstrated in different systems using a variety of techniques [3-5]. Therefore, analyzing cell ensembles individually with high spatiotemporal resolutions will lead to a
526 citations
TL;DR: QUBIC, a specific and highly sensitive method for detection of protein–protein interactions, is used to identify new partners for the mitotic spindle components pericentrin and TACC3.
Abstract: Protein interactions are involved in all cellular processes. Their efficient and reliable characterization is therefore essential for understanding biological mechanisms. In this study, we show that combining bacterial artificial chromosome (BAC) TransgeneOmics with quantitative interaction proteomics, which we call quantitative BAC–green fluorescent protein interactomics (QUBIC), allows specific and highly sensitive detection of interactions using rapid, generic, and quantitative procedures with minimal material. We applied this approach to identify known and novel components of well-studied complexes such as the anaphase-promoting complex. Furthermore, we demonstrate second generation interaction proteomics by incorporating directed mutational transgene modification and drug perturbation into QUBIC. These methods identified domain/isoform-specific interactors of pericentrin- and phosphorylation-specific interactors of TACC3, which are necessary for its recruitment to mitotic spindles. The scalability, simplicity, cost effectiveness, and sensitivity of this method provide a basis for its general use in small-scale experiments and in mapping the human protein interactome.
506 citations
TL;DR: A unique knowledge base containing extensive information on the proteins identified in envelope fractions was obtained, allowing new insights into this membrane system to be revealed, and the data obtained provide unexpected information about plastidial or subplastidials localization of some proteins that were not suspected to be associated to this membranes system.
TL;DR: It is demonstrated that large portions of the proteome are simply inaccessible following digestion with a single protease and that multiple proteases, rather than technical replicates, provide a direct route to increase both protein identifications and proteome sequence coverage.
Abstract: Large-scale protein sequencing methods rely on enzymatic digestion of complex protein mixtures to generate a collection of peptides for mass spectrometric analysis. Here we examine the use of multiple proteases (trypsin, LysC, ArgC, AspN, and GluC) to improve both protein identification and characterization in the model organism Saccharomyces cerevisiae. Using a data-dependent, decision tree-based algorithm to tailor MS(2) fragmentation method to peptide precursor, we identified 92 095 unique peptides (609 665 total) mapping to 3908 proteins at a 1% false discovery rate (FDR). These results were a significant improvement upon data from a single protease digest (trypsin) - 27 822 unique peptides corresponding to 3313 proteins. The additional 595 protein identifications were mainly from those at low abundances (i.e., < 1000 copies/cell); sequence coverage for these proteins was likewise improved nearly 3-fold. We demonstrate that large portions of the proteome are simply inaccessible following digestion with a single protease and that multiple proteases, rather than technical replicates, provide a direct route to increase both protein identifications and proteome sequence coverage.
TL;DR: Rapid advances in all areas of the proteomic workflow, including sample preparation, MS, and computational analysis, should make the technology more easily available to a broad community and turn it into a staple methodology for cell biologists.
Abstract: The global analysis of protein composition, modifications, and dynamics are important goals in cell biology. Mass spectrometry (MS)–based proteomics has matured into an attractive technology for this purpose. Particularly, high resolution MS methods have been extremely successful for quantitative analysis of cellular and organellar proteomes. Rapid advances in all areas of the proteomic workflow, including sample preparation, MS, and computational analysis, should make the technology more easily available to a broad community and turn it into a staple methodology for cell biologists.
TL;DR: A versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations and will enable the discovery of novel biomarkers in a manner that is unencumbered by the incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.
Abstract: Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.
TL;DR: Seven membrane protein topology prediction methods based on different underlying algorithms, such as hidden Markov models, neural networks and support vector machines, have been used for analysis of the protein sequences from the 21 416 annotated genes in the human genome.
Abstract: Membrane proteins are key molecules in the cell, and are important targets for pharmaceutical drugs. Few three-dimensional structures of membrane proteins have been obtained, which makes computatio ...
TL;DR: Compared with the existing methods for predicting eukaryotic protein subcellular localization, the new predictor is much more powerful and flexible, particularly in dealing with proteins with multiple locations and proteins without available accession numbers.
Abstract: Information of subcellular locations of proteins is important for in-depth studies of cell biology. It is very useful for proteomics, system biology and drug development as well. However, most existing methods for predicting protein subcellular location can only cover 5 to 12 location sites. Also, they are limited to deal with single-location proteins and hence failed to work for multiplex proteins, which can simultaneously exist at, or move between, two or more location sites. Actually, multiplex proteins of this kind usually posses some important biological functions worthy of our special notice. A new predictor called “Euk-mPLoc 2.0” is developed by hybridizing the gene ontology information, functional domain information, and sequential evolutionary information through three different modes of pseudo amino acid composition. It can be used to identify eukaryotic proteins among the following 22 locations: (1) acrosome, (2) cell wall, (3) centriole, (4) chloroplast, (5) cyanelle, (6) cytoplasm, (7) cytoskeleton, (8) endoplasmic reticulum, (9) endosome, (10) extracell, (11) Golgi apparatus, (12) hydrogenosome, (13) lysosome, (14) melanosome, (15) microsome (16) mitochondria, (17) nucleus, (18) peroxisome, (19) plasma membrane, (20) plastid, (21) spindle pole body, and (22) vacuole. Compared with the existing methods for predicting eukaryotic protein subcellular localization, the new predictor is much more powerful and flexible, particularly in dealing with proteins with multiple locations and proteins without available accession numbers. For a newly-constructed stringent benchmark dataset which contains both single- and multiple-location proteins and in which none of proteins has pairwise sequence identity to any other in a same location, the overall jackknife success rate achieved by Euk-mPLoc 2.0 is more than 24% higher than those by any of the existing predictors. As a user-friendly web-server, Euk-mPLoc 2.0 is freely accessible at http://www.csbio.sjtu.edu.cn/bioinf/euk-multi-2/. For a query protein sequence of 400 amino acids, it will take about 15 seconds for the web-server to yield the predicted result; the longer the sequence is, the more time it may usually need. It is anticipated that the novel approach and the powerful predictor as presented in this paper will have a significant impact to Molecular Cell Biology, System Biology, Proteomics, Bioinformatics, and Drug Development.
TL;DR: Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells and can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment.
Abstract: Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment.
TL;DR: This work reviews activity-based protein profiling and its implementation to annotate the enzymatic proteome, with particular attention given to probes that target serine hydrolases, a diverse superfamily of enzymes replete with many uncharacterized members.
TL;DR: In this article, the authors integrated quantitative proteomics with bioinformatic analysis to generate a series of independent classifiers that describe the approximately 4,000 proteins identified in isolated mitotic chromosomes.
TL;DR: This is the first report that uses the proteomic approach to thoroughly study trypsin-induced cell physiological changes and provides researchers in carrying out their experimental design.
Abstract: It is essential to subculture the cells once cultured cells reach confluence. For this, trypsin is frequently applied to dissociate adhesive cells from the substratum. However, due to the proteolytic activity of trypsin, cell surface proteins are often cleaved, which leads to dysregulation of the cell functions. In this study, a triplicate 2D-DIGE strategy has been performed to monitor trypsin-induced proteome alterations. The differentially expressed spots were identified by MALDI-TOF MS and validated by immunoblotting. 36 proteins are found to be differentially expressed in cells treated with trypsin, and proteins that are known to regulate cell metabolism, growth regulation, mitochondrial electron transportation and cell adhesion are down-regulated and proteins that regulate cell apoptosis are up-regulated after trypsin treatment. Further study shows that bcl-2 is down-regulated, p53 and p21 are both up-regulated after trypsinization. In summary, this is the first report that uses the proteomic approach to thoroughly study trypsin-induced cell physiological changes and provides researchers in carrying out their experimental design.
TL;DR: The secretome definition, the applied approaches for unlocking secrets of the secreted proteins in the extracellular fluid, the possible functional significance and secretory mechanisms of LSPs, as well as glycosylation ofsecreted proteins and challenges involved ahead are discussed.
Abstract: Plant secretomics is a newly emerging area of the plant proteomics field. It basically describes the global study of secreted proteins into the extracellular space of plant cell or tissue at any given time and under certain conditions through various secretory mechanisms. A combination of biochemical, proteomics and bioinformatics approaches has been developed to isolate, identify and profile secreted proteins using complementary in vitro suspension-cultured cells and in planta systems. Developed inventories of secreted proteins under normal, biotic and abiotic conditions revealed several different types of novel secreted proteins, including the leaderless secretory proteins (LSPs). On average, LSPs can account for more than 50% of the total identified secretome, supporting, as in other eukaryotes, the existence of novel secretory mechanisms independent of the classical endoplasmic reticulum-Golgi secretory pathway, and suggesting that this non-classical mechanism of protein expression is, for as yet unknown reasons, more massively used than in other eukaryotic systems. Plants LSPs, which seem to be potentially involved in the defense/stress responses, might have dual (extracellular and/or intracellular) roles as most of them have established intracellular functions, yet presently unknown extracellular functions. Evidence is emerging on the role of glycosylation in the apical sorting and trafficking of secretory proteins. These initial secretome studies in plants have considerably advanced our understanding on secretion of different types of proteins and their underlying mechanisms, and opened a door for comparative analyses of plant secretomes with those of other organisms. In this first review on plant secretomics, we summarize and discuss the secretome definition, the applied approaches for unlocking secrets of the secreted proteins in the extracellular fluid, the possible functional significance and secretory mechanisms of LSPs, as well as glycosylation of secreted proteins and challenges involved ahead. Further improvements in existing and developing strategies and techniques will continue to drive forward plant secretomics research to building comprehensive and confident data sets of secreted proteins. This will lead to an increased understanding on how cells couple the concerted action of secreted protein networks to their internal and external environments.
TL;DR: This work indicates that protein export profoundly marks early sexual differentiation in P. falciparum, probably contributing to host cell remodeling in this phase of the life cycle, and that gametocyte-enriched molecules are recruited to modulate this process in gametocytogenesis.
TL;DR: In this article, the authors describe a methodology for the extraction of extracellular proteins from human aortas and their identification by proteomics, which is based on effective decellularization to enrich for scarce ECM proteins, successful solubilization and deglycosylation of ECM protein and relative estimation of protein abundance using spectral counting.
TL;DR: N-terminomics analyses using iTRAQ-TAILS links gelatinases with new mechanisms of action in angiogenesis and reveals unpredicted restrictions in substrate repertoires for these two very similar proteases.
Journal Article•
TL;DR: An unbiased analysis of the whole chromosome proteome from genetic knockouts of kinetochore protein Ska3/Rama1 revealed that the APC/C and RanBP2/RanGAP1 complexes depend on the Ska complex for stable association with chromosomes.
Abstract: Summary Despite many decades of study, mitotic chromosome structure and composition remain poorly characterized. Here, we have integrated quantitative proteomics with bioinformatic analysis to generate a series of independent classifiers that describe the ∼4,000 proteins identified in isolated mitotic chromosomes. Integrating these classifiers by machine learning uncovers functional relationships between protein complexes in the context of intact chromosomes and reveals which of the ∼560 uncharacterized proteins identified here merits further study. Indeed, of 34 GFP-tagged predicted chromosomal proteins, 30 were chromosomal, including 13 with centromere-association. Of 16 GFP-tagged predicted nonchromosomal proteins, 14 were confirmed to be nonchromosomal. An unbiased analysis of the whole chromosome proteome from genetic knockouts of kinetochore protein Ska3/Rama1 revealed that the APC/C and RanBP2/RanGAP1 complexes depend on the Ska complex for stable association with chromosomes. Our integrated analysis predicts that up to 97 new centromere-associated proteins remain to be discovered in our data set.
TL;DR: The focus of this review is on the use of proteomics tools and methods to identify oxidized proteins along with specific sites of oxidative damage and the consequences of protein oxidation.
Abstract: Excessive oxidative stress leaves a protein carbonylation fingerprint in biological systems. Carbonylation is an irreversible post-translational modification (PTM) that often leads to the loss of protein function and can be a component of multiple diseases. Protein carbonyl groups can be generated directly (by amino acids oxidation and the α-amidation pathway) or indirectly by forming adducts with lipid peroxidation products or glycation and advanced glycation end-products. Studies of oxidative stress are complicated by the low concentration of oxidation products and a wide array of routes by which proteins are carbonylated. The development of new selection and enrichment techniques coupled with advances in mass spectrometry are allowing the identification of hundreds of new carbonylated protein products from a broad range of proteins located at many sites in biological systems. The focus of this review is on the use of proteomics tools and methods to identify oxidized proteins along with specific sites o...
Journal Article•
Abstract: Two-dimensional gel electrophoresis has been instrumental in the birth and developments of proteomics, although it is no longer the exclusive separation tool used in the field of proteomics. In this review, a historical perspective is made, starting from the days where two-dimensional gels were used and the word proteomics did not even exist. The events that have led to the birth of proteomics are also recalled, ending with a description of the now well-known limitations of two-dimensional gels in proteomics. However, the often-underestimated advantages of two-dimensional gels are also underlined, leading to a description of how and when to use two-dimensional gels for the best in a proteomics approach. Taking support of these advantages (robustness, resolution, and ability to separate entire, intact proteins), possible future applications of this technique in proteomics are also mentioned.
TL;DR: This overview describes variables at each stage of a protein expression experiment that can influence solubility and offers a summary of strategies used to optimize soluble expression in E. coli.
Abstract: Recombinant protein expression in Escherichia coli (E. coli) is simple, fast, inexpensive, and robust, with the expressed protein comprising up to 50 percent of the total cellular protein. However, it also has disadvantages. For example, the rapidity of bacterial protein expression often results in unfolded/misfolded proteins, especially for heterologous proteins that require longer times and/or molecular chaperones to fold correctly. In addition, the highly reductive environment of the bacterial cytosol and the inability of E. coli to perform several eukaryotic post-translational modifications results in the insoluble expression of proteins that require these modifications for folding and activity. Fortunately, multiple, novel reagents and techniques have been developed that allow for the efficient, soluble production of a diverse range of heterologous proteins in E. coli. This overview describes variables at each stage of a protein expression experiment that can influence solubility and offers a summary of strategies used to optimize soluble expression in E. coli.
TL;DR: This study uncovered the Na-H exchanger NHE1 as a potential MAPK scaffold, found links between HSP90 chaperones and MAPK pathways and identified MUC12 as the human analog to the yeast signaling mucin Msb2.
Abstract: Mitogen-activated protein kinase (MAPK) pathways form the backbone of signal transduction in the mammalian cell. Here we applied a systematic experimental and computational approach to map 2,269 interactions between human MAPK-related proteins and other cellular machinery and to assemble these data into functional modules. Multiple lines of evidence including conservation with yeast supported a core network of 641 interactions. Using small interfering RNA knockdowns, we observed that approximately one-third of MAPK-interacting proteins modulated MAPK-mediated signaling. We uncovered the Na-H exchanger NHE1 as a potential MAPK scaffold, found links between HSP90 chaperones and MAPK pathways and identified MUC12 as the human analog to the yeast signaling mucin Msb2. This study makes available a large resource of MAPK interactions and clone libraries, and it illustrates a methodology for probing signaling networks based on functional refinement of experimentally derived protein-interaction maps.
TL;DR: Recent proteomics results that have elucidated new aspects of the roles and regulation of signal transduction pathways in cancer using the epidermal growth factor receptor, ERK and breakpoint cluster region (BCR)–ABL1 networks as examples are reviewed.
Abstract: Advances in the generation and interpretation of proteomics data have spurred a transition from focusing on protein identification to functional analysis. Here we review recent proteomics results that have elucidated new aspects of the roles and regulation of signal transduction pathways in cancer using the epidermal growth factor receptor (EGFR), ERK and breakpoint cluster region (BCR)-ABL1 networks as examples. The emerging theme is to understand cancer signalling as networks of multiprotein machines which process information in a highly dynamic environment that is shaped by changing protein interactions and post-translational modifications (PTMs). Cancerous genetic mutations derange these protein networks in complex ways that are tractable by proteomics.