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PubMed2001

Towards an understanding of complex protein networks.

Large-scale two-hybrid screens have generated a wealth of information describing potential protein--protein interactions. When compiled with data from systematic localizations of proteins, mutant screens and other functional tests, a network of interactions among proteins and between proteins and other components of eukaryotic cells can be deduced. These networks can be viewed as maps of the cell, depicting potential signaling pathways and interactive complexes. Most importantly, they provide potential clues to the function of previously uncharacterized proteins. Focusing on recent experiments, we explore these protein-interaction studies and the maps derived from such efforts.

Cell Cycle↗
PubMed2003

Iterative data analysis is the key for exhaustive analysis of peptide mass fingerprints from proteins separated by two-dimensional electrophoresis.

Peptide mass fingerprinting (PMF) is a powerful tool for identification of proteins separated by two-dimensional electrophoresis (2-DE). With the increase in sensitivity of peptide mass determination it becomes obvious that even spots looking well separated on a 2-DE gel may consist of several proteins. As a result the number of mass peaks in PMFs increased dramatically leaving many unassigned after a first database search. A number of these are caused by experiment-specific contaminants or by neighbor spots, as well as by additional proteins or post-translational modifications. To understand the complete protein composition of a spot we suggest an iterative procedure based on large numbers of PMFs, exemplified by PMFs of 480 Helicobacter pylori protein spots. Three key iterations were applied: (1) Elimination of contaminant mass peaks determined by MS-Screener (a software developed for this purpose) followed by reanalysis; (2) neighbor spot mass peak determination by cluster analysis, elimination from the peak list and repeated search; (3) re-evaluation of contaminant peaks. The quality of the identification was improved and spots previously unidentified were assigned to proteins. Eight additional spots were identified with this procedure, increasing the total number of identified spots to 455.

Cluster Analysis↗
PubMed2006

Efficient and specific trypsin digestion of microgram to nanogram quantities of proteins in organic-aqueous solvent systems.

Mass spectrometry-based identification of the components of multiprotein complexes often involves solution-phase proteolytic digestion of the complex. The affinity purification of individual protein complexes often yields nanogram to low-microgram amounts of protein, which poses several challenges for enzymatic digestion and protein identification. We tested different solvent systems to optimize trypsin digestions of samples containing limited amounts of protein for subsequent analysis by LC-MS-MS. Data collected from digestion of 10-, 2-, 1-, and 0.2-microg portions of a protein standard mixture indicated that an organic-aqueous solvent system containing 80% acetonitrile consistently provided the most complete digestion, producing more peptide identifications than the other solvent systems tested. For example, a 1-h digestion in 80% acetonitrile yielded over 52% more peptides than the overnight digestion of 1 microg of a protein mixture in purely aqueous buffer. This trend was also observed for peptides from digested ribosomal proteins isolated from Rhodopseudomonas palustris. In addition to improved digestion efficiency, the shorter digestion times possible with the organic solvent also improved trypsin specificity, resulting in smaller numbers of semitryptic peptides than an overnight digestion protocol using an aqueous solvent. The technique was also demonstrated for an affinity-isolated protein complex, GroEL. To our knowledge, this report is the first using mass spectrometry data to show a linkage between digestion solvent and trypsin specificity.

Acetonitriles↗
PubMedDate not supplied

"Top Down" characterization is a complementary technique to peptide sequencing for identifying protein species in complex mixtures.

At present, mass spectrometry provides a rapid and sensitive means for making conclusive protein identifications from complex mixtures. Sequencing tryptic peptides derived from proteolyzed protein samples, also known as the "Bottom Up" approach, is the mass spectrometric gold standard for identifying unknowns. An alternative technology, "Top Down" characterization, is emerging as a viable option for protein identifications, which involves analyzing the intact unknowns for accurate mass and amino acid sequence tags. In this paper, both characterization methods were employed to more comprehensively differentiate two early-eluting peaks in a process-scale size-exclusion chromatography (SEC) step for a recombinant, immunoglobulin gamma-1 (IgG-1) fusion protein. The contents of each SEC peak were enzymatically digested, and the resulting peptides were mapped using reversed-phase (RP) HPLC-ion trap MS. Many low-level UV signals were observed among the fusion protein-related peptide peaks. These unknowns were collected, concentrated, and analyzed using nanoelectrospray (nanoES) collision-induced dissociation (CID) tandem (MS/MS) mass spectrometry for identification. The peptide sequencing experiments resulted in the identification of twenty host cell-related proteins. Following peptide mapping, the contents of the two SEC peaks were protein mass profiled using on-line RP HPLC coupled to a high-resolution, quadrupole time-of-flight (Qq/TOF) MS. Unknown proteins were also collected, concentrated, and dissociated using nanoES CID MS/MS. Intact protein CID experiments and accurate molecular weight information allowed for the identification of three full length host cell-derived proteins and numerous clips from these and additional proteins. The accurate molecular weight values allowed for the assignment of N- and C-terminal processing, which is difficult to conclusively access from peptide mapping data. The peptide-mapping experiments proved to be far more effective for making protein identifications from complex mixtures, whereas the protein mass profiling was useful for assessing modifications and distinguishing protein clips from full length species.

Alkylation↗
PubMedDate not supplied

Analysis of murine natural killer cell microsomal proteins using two-dimensional liquid chromatography coupled to tandem electrospray ionization mass spectrometry.

This study describes the application of a single tube sample preparation technique coupled with multidimensional fractionation for the analysis of a complex membrane protein sample from murine natural killer (NK) cells. A solution-based method that facilitates the solubilization and tryptic digestion of integral membrane proteins is conjoined with strong cation exchange (SCX) liquid chromatography (LC) fractionation followed by microcapillary reversed-phase (microRP) LC tandem mass spectrometric analysis of each SCXLC fraction in second dimension. Sonication in buffered methanol solution was employed to solubilize, and tryptically digest murine NK cell microsomal proteins, allowing for the large-scale identification of integral membrane proteins, including the mapping of the membrane-spanning peptides. Bioinformatic analysis of the acquired tandem mass spectra versus the murine genome database resulted in 11,967 matching tryptic peptide sequences, corresponding to 5782 unique peptide identifications. These peptides resulted in identification of 2563 proteins of which 876 (34%) are classified as membrane proteins.

Amino Acid Sequence↗
PubMedDate not supplied

Differential expression of proteins in response to ceramide-mediated stress signal in colon cancer cells by 2-D gel electrophoresis and MALDI-TOF-MS.

Comparative cancer cell proteome analysis is a strategy to study the implication of ceramides in the transmission of stress signals. To better understand the mechanisms by which ceramide regulate some physiological or pathological events and the response to the pharmacological treatment of cancer, we performed a differential analysis of the proteome of HCT-116 (human colon carcinoma) cells in response to these substances. We first established the first 2-dimensional map of the HCT-116 proteome. Then, HCT116 cell proteome treated or not with C6-ceramide have been compared using two-dimensional electrophoresis, matrix-assisted laser desorption/ionization-mass spectrometry and bioinformatic (genomic databases). 2-DE gel analysis revealed more than fourty proteins that were differentially expressed in control cells and cells treated with ceramide. Among them, we confirmed the differential expression of proteins involved in apoptosis and cell adhesion.

Apoptosis↗
PubMed2003

Computational approaches to protein-protein interaction.

The interactions between proteins allow the cell's life. A number of experimental, genome-wide, high-throughput studies have been devoted to the determination of protein-protein interactions and the consequent interaction networks. Here, the bioinformatics methods dealing with protein-protein interactions and interaction network are overviewed. 1. Interaction databases developed to collect and annotate this immense amount of data; 2. Automated data mining techniques developed to extract information about interactions from the published literature; 3. Computational methods to assess the experimental results developed as a consequence of the finding that the results of high-throughput methods are rather inaccurate; 4. Exploitation of the information provided by protein interaction networks in order to predict functional features of the proteins; and 5. Prediction of protein-protein interactions.

Algorithms↗
PubMed2006

Peptidomic analysis of breast cancer reveals a putative surrogate marker for estrogen receptor-negative carcinomas.

Estrogen-receptor status provides a major biomarker in breast cancer classification and has an important impact on prognosis and treatment options. The aim of this study was to investigate peptide profiles of invasive breast cancer with positive (n=39) and negative receptor status (n=41). Peptide profiles were generated by 'Differential Peptide Display', which is an offline-coupled combination of reversed-phase-HPLC and MALDI mass spectrometry. Mass spectrometric data were correlated with the immunohistochemically determined receptor state. Identification of peptides of interest was carried out by additional mass spectrometric methods (eg MALDI-TOF-TOF-MS-MS). Approximately 3000-7000 signals were detected per sample and thymosin alpha-1, an asparaginyl endopeptidase generated cleavage product of the ubiquitous acidic protein prothymosin-alpha, was found to differentiate the tumor samples according to their receptor status with the highest specificity. The concentration of Thymosin alpha-1 was found to be upregulated (n=37) in estrogen-negative cancer samples and downregulated (n=32) in estrogen-positive breast cancer samples. The expression of the precursor protein (Prothymosin-alpha) has been discussed previously as a prognostic factor in breast cancer. It is involved in the ER signal transduction pathway as an anti-coactivator-inhibitor. From our findings we conclude that Thymosin alpha-1 could serve as a surrogate marker in breast cancers and may indicate ER functionality.

Biomarkers, Tumor↗
PubMed2004

Ten thousand interactions for the molecular biologist.

Previous studies have suggested that nature is restricted to about 1,000 protein folds to perform a great diversity of functions. Here, we use protein interaction data from different sources and three-dimensional structures to suggest that the total number of interaction types is also limited, and estimate that most interactions in nature will conform to one of about 10,000 types. We currently know fewer than 2,000, and at the present rate of structure determination, it will be more than 20 years before we know a full representative set.

Cell Physiological Phenomena↗
PubMed2005

Effect of sampling on topology predictions of protein-protein interaction networks.

Currently available protein-protein interaction (PPI) network or 'interactome' maps, obtained with the yeast two-hybrid (Y2H) assay or by co-affinity purification followed by mass spectrometry (co-AP/MS), only cover a fraction of the complete PPI networks. These partial networks display scale-free topologies--most proteins participate in only a few interactions whereas a few proteins have many interaction partners. Here we analyze whether the scale-free topologies of the partial networks obtained from Y2H assays can be used to accurately infer the topology of complete interactomes. We generated four theoretical interaction networks of different topologies (random, exponential, power law, truncated normal). Partial sampling of these networks resulted in sub-networks with topological characteristics that were virtually indistinguishable from those of currently available Y2H-derived partial interactome maps. We conclude that given the current limited coverage levels, the observed scale-free topology of existing interactome maps cannot be confidently extrapolated to complete interactomes.

Animals↗
PubMed2003

Regulation of Salmonella typhimurium virulence gene expression by cationic antimicrobial peptides.

Cationic antimicrobial peptides (CAMP) represent a conserved and highly effective component of innate immunity. During infection, the Gram-negative pathogen Salmonella typhimurium induces different mechanisms of CAMP resistance that promote pathogenesis in animals. This study shows that exposure of S. typhimurium to sublethal concentrations of CAMP activates the PhoP/PhoQ and RpoS virulence regulons, while repressing the transcription of genes required for flagella synthesis and the invasion-associated type III secretion system. We further demonstrate that growth of S. typhimurium in low doses of the alpha-helical peptide C18G induces resistance to CAMP of different structural classes. Inducible resistance depends on the presence of PhoP, indicating that the PhoP/PhoQ system can sense sublethal concentrations of cationic antimicrobial peptides. Growth of S. typhimurium in the presence of CAMP also leads to RpoS-dependent protection against hydrogen peroxide. Because bacterial resistance to oxidative stress and CAMP are induced during infection of animals, CAMP may be an important signal recognized by bacteria on colonization of animal tissues.

Alkaline Phosphatase↗
PubMed2004

Global network analysis of phenotypic effects: protein networks and toxicity modulation in Saccharomyces cerevisiae.

Using genome-wide information to understand holistically how cells function is a major challenge of the postgenomic era. Recent efforts to understand molecular pathway operation from a global perspective have lacked experimental data on phenotypic context, so insights concerning biologically relevant network characteristics of key genes or proteins have remained largely speculative. Here, we present a global network investigation of the genotype/phenotype data set we developed for the recovery of the yeast Saccharomyces cerevisiae from exposure to DNA-damaging agents, enabling explicit study of how protein-protein interaction network characteristics may be associated with phenotypic functional effects. We show that toxicity-modulating proteins have similar topological properties as essential proteins, suggesting that cells initiate highly coordinated responses to damage similar to those needed for vital cellular functions. We also identify toxicologically important protein complexes, pathways, and modules. These results have potential implications for understanding toxicity-modulating processes relevant to a number of human diseases, including cancer and aging.

Cluster Analysis↗
PubMed2003

A fast layout algorithm for protein interaction networks.

MOTIVATION: Graph drawing algorithms are often used for visualizing relational information, but a naive implementation of a graph drawing algorithm encounters real difficulties when drawing large-scale graphs such as protein interaction networks. RESULTS: We have developed a new, extremely fast layout algorithm for visualizing large-scale protein interaction networks in the three-dimensional space. The algorithm (1) first finds a layout of connected components of an entire network, (2) finds a global layout of nodes with respect to pivot nodes within a connected component and (3) refines the local layout of each connected component by first relocating midnodes with respect to their cutvertices and direct neighbors of the cutvertices and then by relocating all nodes with respect to their neighbors within distance 2. Advantages of this algorithm over classical graph drawing methods include: (1) it is an order of magnitude faster, (2) it can directly visualize data from protein interaction databases and (3) it provides several abstraction and comparison operations for effectively analyzing large-scale protein interaction networks. AVAILABILITY: http://wilab.inha.ac.kr/interviewer/

Algorithms↗
PubMed2006

Predicting protein interaction sites: binding hot-spots in protein-protein and protein-ligand interfaces.

MOTIVATION: Protein assemblies are currently poorly represented in structural databases and their structural elucidation is a key goal in biology. Here we analyse clefts in protein surfaces, likely to correspond to binding 'hot-spots', and rank them according to sequence conservation and simple measures of physical properties including hydrophobicity, desolvation, electrostatic and van der Waals potentials, to predict which are involved in binding in the native complex. RESULTS: The resulting differences between predicting binding-sites at protein-protein and protein-ligand interfaces are striking. There is a high level of prediction accuracy (< or =93%) for protein-ligand interactions, based on the following attributes: van der Waals potential, electrostatic potential, desolvation and surface conservation. Generally, the prediction accuracy for protein-protein interactions is lower, with the exception of enzymes. Our results show that the ease of cleft desolvation is strongly predictive of interfaces and strongly maintained across all classes of protein-binding interface.

Binding Sites↗
PubMed2005

The European Bioinformatics Institute's data resources: towards systems biology.

Genomic and post-genomic biological research has provided fine-grain insights into the molecular processes of life, but also threatens to drown biomedical researchers in data. Moreover, as new high-throughput technologies are developed, the types of data that are gathered en masse are diversifying. The need to collect, store and curate all this information in ways that allow its efficient retrieval and exploitation is greater than ever. The European Bioinformatics Institute's (EBI's) databases and tools have evolved to meet the changing needs of molecular biologists: since we last wrote about our services in the 2003 issue of Nucleic Acids Research, we have launched new databases covering protein-protein interactions (IntAct), pathways (Reactome) and small molecules (ChEBI). Our existing core databases have continued to evolve to meet the changing needs of biomedical researchers, and we have developed new data-access tools that help biologists to move intuitively through the different data types, thereby helping them to put the parts together to understand biology at the systems level. The EBI's data resources are all available on our website at http://www.ebi.ac.uk.

Computational Biology↗
PubMed2006

Macromolecular recognition in the Protein Data Bank.

Crystal structures deposited in the Protein Data Bank illustrate the diversity of biological macromolecular recognition: transient interactions in protein-protein and protein-DNA complexes and permanent assemblies in homodimeric proteins. The geometric and physical chemical properties of the macromolecular interfaces that may govern the stability and specificity of recognition are explored in complexes and homodimers compared with crystal-packing interactions. It is found that crystal-packing interfaces are usually much smaller; they bury fewer atoms and are less tightly packed than in specific assemblies. Standard-size interfaces burying 1200-2000 A2 of protein surface occur in protease-inhibitor and antigen-antibody complexes that assemble with little or no conformation changes. Short-lived electron-transfer complexes have small interfaces; the larger size of the interfaces observed in complexes involved in signal transduction and homodimers correlates with the presence of conformation changes, often implicated in biological function. Results of the CAPRI (critical assessment of predicted interactions) blind prediction experiment show that docking algorithms efficiently and accurately predict the mode of assembly of proteins that do not change conformation when they associate. They perform less well in the presence of large conformation changes and the experiment stimulates the development of novel procedures that can handle such changes.

Algorithms↗