Protein interaction methods--toward an endgame

Dodecenylsuccinic anhydride-modified oxalate decarboxylase loaded with magnetic nano-Fe3O4@SiO2 for demulsification of oil-in-water emulsions

The inability to demulsify oil-in-water emulsions via green and efficient processes is a challenging problem in many industrial processes. As a novel biodemulsifier, protein demulsifiers display excellent dispersibility and stability, but their demulsification mechanisms are not clear, which severely restricts their large-scale production and application. In this study, the demulsification mechanism of the high-efficiency protein biodemulsifier oxalate decarboxylase (Bacm OxdC), which is secreted by the Bacillus mojavensis XH1 strain, for an oil-in-water emulsion was analyzed. The results showed that Bacm OxdC was spontaneously adsorbed at the oil-water interface and turned its hydrophobic amino acids outward to increase its hydrophobicity and break the emulsified system. Furthermore, it effectively reduced the oil-water interfacial tension and interfacial film strength, thereby reducing the oil-water interfacial energy and finally enabling demulsification. To further improve the demulsification efficiency and reusability, Fe₃O₄@SiO₂@OxdC-DDSA was prepared. This method provided a magnetic response for Bacm OxdC and enabled efficient demulsification. The demulsification rate of Fe₃O₄@SiO₂@OxdC-DDSA reached 98.1% at 24 h, which was 30.7% higher than that of the original Bacm OxdC. After three cycles, the demulsification rate still reached 89.3%, proving it has excellent recyclability. This work is the first study on the demulsification mechanism of protein biodemulsifiers and provides useful insights into the demulsification mechanism of biodemulsifiers for oil-in-water emulsions. In addition, a promising high-efficiency modification technique for protein biodemulsifiers was proposed, which provided information for the development of biodemulsifiers for oil-water separation.

Bioluminescence Assays for Monitoring Chondrogenic Differentiation and Cartilage Regeneration

Since articular cartilage has a limited regeneration potential, for developing biological therapies for cartilage regeneration it is important to study the mechanisms underlying chondrogenesis of stem cells. Bioluminescence assays can visualize a wide range of biological phenomena such as gene expression, signaling, metabolism, development, cellular movements, and molecular interactions by using visible light and thus contribute substantially to elucidation of their biological functions. This article gives a concise review to introduce basic principles of bioluminescence assays and applications of the technology to visualize the processes of chondrogenesis and cartilage regeneration. Applications of bioluminescence assays have been highlighted in the methods of real-time monitoring of gene expression and intracellular levels of biomolecules and noninvasive cell tracking within animal models. This review suggests that bioluminescence assays can be applied towards a visual understanding of chondrogenesis and cartilage regeneration.

Next-Generation Sequencing for Binary Protein-Protein Interactions

The yeast two-hybrid (Y2H) system exploits host cell genetics in order to display binary protein-protein interactions (PPIs) via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS), and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.

The Prion Protein Controls Polysialylation of Neural Cell Adhesion Molecule 1 during Cellular Morphogenesis

Despite its multi-faceted role in neurodegenerative diseases, the physiological function of the prion protein (PrP) has remained elusive. On the basis of its evolutionary relationship to ZIP metal ion transporters, we considered that PrP may contribute to the morphogenetic reprogramming of cells underlying epithelial-to-mesenchymal transitions (EMT). Consistent with this hypothesis, PrP transcription increased more than tenfold during EMT, and stable PrP-deficient cells failed to complete EMT in a mammalian cell model. A global comparative proteomics analysis identified the neural cell adhesion molecule 1 (NCAM1) as a candidate mediator of this impairment, which led to the observation that PrP-deficient cells fail to undergo NCAM1 polysialylation during EMT. Surprisingly, this defect was caused by a perturbed transcription of the polysialyltransferase ST8SIA2 gene. Proteomics data pointed toward β-catenin as a transcriptional regulator affected in PrP-deficient cells. Indeed, pharmacological blockade or siRNA-based knockdown of β-catenin mimicked PrP-deficiency in regards to NCAM1 polysialylation. Our data established the existence of a PrP-ST8SIA2-NCAM signaling loop, merged two mature fields of investigation and offer a simple model for explaining phenotypes linked to PrP.

Synaptotagmin 1 and Ca2+ drive trans SNARE zippering

Synaptotagmin 1 (Syt1) is a major Ca²⁺-sensor that evokes neurotransmitter release. Here we used site-specific fluorescence resonance energy transfer (FRET) assay to investigate the effects of Syt1 on SNAREpin assembly. C2AB, a soluble version of Syt1, had virtually no stimulatory effect on the rate of the FRET at N-terminus of SNARE complex both with and without Ca²⁺, indicating C2AB does not interfere with the initial nucleation of SNARE assembly. However, C2AB-Ca²⁺ accelerated the FRET rate significantly at membrane proximal region, indicating C2AB-Ca²⁺ promotes the transition from a partially assembled SNARE complex to the fusion-competent SNAREpin. Similar enhancement was also observed at the end of the transmembrane domain of SNARE proteins. The stimulatory effect disappeared if there was no membrane or only neutral membrane present.

Analyzing protein-protein interactions in the post-interactomic era. Are we ready for the endgame?

Mapping protein-protein interactions in genome-wide scales revealed thousands of novel binding partners in each of the explored model organisms. Organizing these hits in comprehensive ways is becoming increasingly important for systems biology approaches to understand complex cellular processes and diseases. However, proteome wide interaction techniques and their resulting global networks are not revealing the topologies of networks that are truly operating in the cell. In this short review I will discuss which prerequisites have to be fulfilled and which experimental methods might be practicable to translate primary protein interaction data into network presentations that help in understanding cellular processes.

The role of electrostatic energy in prediction of obligate protein-protein interactions

BACKGROUND

Prediction and analysis of protein-protein interactions (PPI) and specifically types of PPIs is an important problem in life science research because of the fundamental roles of PPIs in many biological processes in living cells. In addition, electrostatic interactions are important in understanding inter-molecular interactions, since they are long-range, and because of their influence in charged molecules. This is the main motivation for using electrostatic energy for prediction of PPI types.

RESULTS

We propose a prediction model to analyze protein interaction types, namely obligate and non-obligate, using electrostatic energy values as properties. The prediction approach uses electrostatic energy values for pairs of atoms and amino acids present in interfaces where the interaction occurs. The main features of the complexes are found and then the prediction is performed via several state-of-the-art classification techniques, including linear dimensionality reduction (LDR), support vector machine (SVM), naive Bayes (NB) and k-nearest neighbor (k-NN). For an in-depth analysis of classification results, some other experiments were performed by varying the distance cutoffs between atom pairs of interacting chains, ranging from 5Å to 13Å. Moreover, several feature selection algorithms including gain ratio (GR), information gain (IG), chi-square (Chi2) and minimum redundancy maximum relevance (mRMR) are applied on the available datasets to obtain more discriminative pairs of atom types and amino acid types as features for prediction.

CONCLUSIONS

Our results on two well-known datasets of obligate and non-obligate complexes confirm that electrostatic energy is an important property to predict obligate and non-obligate protein interaction types on the basis of all the experimental results, achieving accuracies of over 98%. Furthermore, a comparison performed by changing the distance cutoff demonstrates that the best values for prediction of PPI types using electrostatic energy range from 9Å to 12Å, which show that electrostatic interactions are long-range and cover a broader area in the interface. In addition, the results on using feature selection before prediction confirm that (a) a few pairs of atoms and amino acids are appropriate for prediction, and (b) prediction performance can be improved by eliminating irrelevant and noisy features and selecting the most discriminative ones.

On employing a translationally controlled tumor protein-derived protein transduction domain analog for transmucosal delivery of drugs

Protein transduction domains (PTDs) are recognized as promising vehicles for the delivery of macromolecular drugs. We have previously shown that a region in the N-terminus (residues 1-10) of translationally controlled tumor protein (TCTP) contains a PTD (TCTP-PTD), MIIYRDLISH, which can serve as a vehicle for the delivery of macromolecules into the cells and tissues. In the current study, we evaluated the potential and safety of TCTP-PTD and its three mutant analogs as nasal absorption enhancers for delivery of drugs. We conducted this evaluation employing insulin as test drug. We examined the degree to which insulin was absorbed in nasal mucosa and also if any mucosal damage occurs following such nasal delivery of insulin using TCTP-PTDs as a vehicle. The systemic delivery of insulin was assessed by measuring the changes in blood glucose levels after nasal coadministration insulin and four PTDs. Of the three TCTP-PTD analogs examined, one, TCTP-PTD analog (MIIFRALISHKK) significantly enhanced the nasal absorption of insulin in both normal and streptozotocin-induced diabetic mice. The relative pharmacological bioavailability of insulin nasally coadministered with the TCTP-PTD analog was 21.3% relative to the subcutaneous route. Molecular association between insulin and the TCTP-PTD analog was observed by fluorescence resonance energy transfer measurements. The binding between the TCTP-PTD analog and insulin may enable the penetration of insulin through the nasal mucosa. Histological examination of mice nasal mucosa 7 days after repeated nasal administration showed no evidence of toxicity at the site of nasal administration. In this study using insulin as a test system we demonstrate that the TCTP-PTD analog offers a promising approach for nasal peptides and protein-drugs delivery.

Quantification of the ionization probability during desorption/ionization of oligopeptides induced by neutral cluster impact

RATIONALE

Desorption-and-ionization induced by neutral cluster impact is a soft and matrix-free method, which leads to the formation of free ions of oligopeptides and smaller proteins without fragmentation. As a prerequisite for its successful application in bioanalytics, especially with respect to sensitivity, the ionization efficiency, i.e., the ion-to-neutral ratio of the desorbing molecules, was determined.

METHODS

Neutral SO2 clusters of 10(3) to 10(4) molecules in size were seeded in a pulsed He beam and used to desorb and ionize oligopeptides by means of cluster surface impact. The samples were prepared by drop casting a well-defined amount of substance on the substrate surface; the desorbing ions were identified by means of time-of-flight mass spectrometry. Furthermore, the ion current leaving the surface was determined for positive ions, which predominate in the investigated oligopeptides.

RESULTS

For angiotensin II, bradykinin (1-7), and adrenocorticotropic hormone (34-39), the number of ions desorbed from the respective samples was compared with the amount of substance applied on the substrate. Assuming that all biomolecules were desorbed during the experiment, the ion-to-neutral ratio or ionization efficiency η was determined. For the tested molecules, values of η between 0.5% and 3% were observed; the substrate material and the total amount of substance applied were shown to have a minor effect on the results.

CONCLUSIONS

The ion-to-neutral ratio in desorption/ionization of oligopeptides induced by neutral cluster impact was determined to be of the order of 10(-3) to 10(-2). The soft and matrix-free nature of the method in combination with this value of η might be interesting for applications in bioanalytics.

An improved bimolecular fluorescence complementation tool based on superfolder green fluorescent protein

Bimolecular fluorescence complementation (BiFC) has been widely used in the analysis of protein-protein interactions (PPIs) in recent years. There are many notable advantages of BiFC such as convenience and direct visualization of PPI in cells. However, BiFC has one common limitation: the separated non-fluorescent fragments can be spontaneously self-assembled into an intact protein, which leads to false-positive results. In this study, a pair of complementary fragments (sfGFPN and sfGFPC) was constructed by splitting superfolder GFP (sfGFP) between the 214 and 215 amino acid residue, and sfGFPC was mutated by site-directed gene mutagenesis to decrease the signal of negative control. Our results showed that mutations in sfGFPC (sfGFPC(m12)) can effectively decrease the signal of negative control. Thus, we provide an improved BiFC tool for the analysis of PPI. Further, since the self-assembly problem is a common shortcoming for application of BiFC, our research provides a feasible strategy for other BiFC candidate proteins with the same problem.

Bioluminescence resonance energy transfer (BRET) imaging in plant seedlings and mammalian cells

Bioluminescence resonance energy transfer (BRET) has become a widely used technique to monitor protein-protein interactions. It involves resonance energy transfer between a bioluminescent donor and a fluorescent acceptor. Because the donor emits photons intrinsically, fluorescence excitation is unnecessary. Therefore, BRET avoids some of the problems inherent in fluorescence resonance energy transfer (FRET) approaches, such as photobleaching, autofluorescence, and undesirable stimulation of photobiological processes. In the past, BRET signals have generally been too dim to be effectively imaged. Newly available cameras that are more sensitive coupled to image splitter now enable BRET imaging in plant and mammalian cells and tissues. In addition, new substrates and enhanced luciferases enable brighter signals that allow even subcellular BRET imaging. Here, we report methods for BRET imaging of (1) localization of COP1 dimerization in plant cells and tissues and (2) subcellular distributions of interactions of the CCAAT/Enhancer Binding Protein α (C/EBPα) in single mammalian cells. We also discuss methods for the correction of BRET images for tissues that absorb light of different spectra. This progress should catalyze further applications of BRET for imaging and high-throughput assays.

Identification of genes expressed during the self-incompatibility response in perennial ryegrass (Lolium perenne L.)

Self-incompatibility (SI) in Lolium perenne is controlled gametophytically by the S-Z two-locus system. S and Z loci mapped to L. perenne linkage groups 1 and 2, respectively, with their corresponding putative-syntenic regions on rice chromosome 5 (R5) and R4. None of the gene products of S and Z have yet been identified. SI cDNA libraries were developed to enrich for SI expressed genes in L. perenne. Transcripts were identified from the SI libraries that were orthologous to sequences on rice R4 and R5. These represent potential SI candidate genes. Altogether ten expressed SI candidate genes were identified. A rapid increase in gene expression within two minutes after pollen-stigma contact was revealed, reaching a maximum between 2 and 10 min. The potential involvement of these genes in the SI reactions is discussed.

Protein networks markedly improve prediction of subcellular localization in multiple eukaryotic species

The function of a protein is intimately tied to its subcellular localization. Although localizations have been measured for many yeast proteins through systematic GFP fusions, similar studies in other branches of life are still forthcoming. In the interim, various machine-learning methods have been proposed to predict localization using physical characteristics of a protein, such as amino acid content, hydrophobicity, side-chain mass and domain composition. However, there has been comparatively little work on predicting localization using protein networks. Here, we predict protein localizations by integrating an extensive set of protein physical characteristics over a protein's extended protein–protein interaction neighborhood, using a classification framework called ‘Divide and Conquer k-Nearest Neighbors’ (DC-kNN). These predictions achieve significantly higher accuracy than two well-known methods for predicting protein localization in yeast. Using new GFP imaging experiments, we show that the network-based approach can extend and revise previous annotations made from high-throughput studies. Finally, we show that our approach remains highly predictive in higher eukaryotes such as fly and human, in which most localizations are unknown and the protein network coverage is less substantial.

Exploiting likely-positive and unlabeled data to improve the identification of protein-protein interaction articles

Background

Experimentally verified protein-protein interactions (PPI) cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such databases can be made faster by ranking newly-published articles' relevance to PPI, a task which we approach here by designing a machine-learning-based PPI classifier. All classifiers require labeled data, and the more labeled data available, the more reliable they become. Although many PPI databases with large numbers of labeled articles are available, incorporating these databases into the base training data may actually reduce classification performance since the supplementary databases may not annotate exactly the same PPI types as the base training data. Our first goal in this paper is to find a method of selecting likely positive data from such supplementary databases. Only extracting likely positive data, however, will bias the classification model unless sufficient negative data is also added. Unfortunately, negative data is very hard to obtain because there are no resources that compile such information. Therefore, our second aim is to select such negative data from unlabeled PubMed data. Thirdly, we explore how to exploit these likely positive and negative data. And lastly, we look at the somewhat unrelated question of which term-weighting scheme is most effective for identifying PPI-related articles.

Results

To evaluate the performance of our PPI text classifier, we conducted experiments based on the BioCreAtIvE-II IAS dataset. Our results show that adding likely-labeled data generally increases AUC by 3~6%, indicating better ranking ability. Our experiments also show that our newly-proposed term-weighting scheme has the highest AUC among all common weighting schemes. Our final model achieves an F-measure and AUC 2.9% and 5.0% higher than those of the top-ranking system in the IAS challenge.

Conclusion

Our experiments demonstrate the effectiveness of integrating unlabeled and likely labeled data to augment a PPI text classification system. Our mixed model is suitable for ranking purposes whereas our hierarchical model is better for filtering. In addition, our results indicate that supervised weighting schemes outperform unsupervised ones. Our newly-proposed weighting scheme, TFBRF, which considers documents that do not contain the target word, avoids some of the biases found in traditional weighting schemes. Our experiment results show TFBRF to be the most effective among several other top weighting schemes.

Network-based classification of breast cancer metastasis

Mapping the pathways that give rise to metastasis is one of the key challenges of breast cancer research. Recently, several large-scale studies have shed light on this problem through analysis of gene expression profiles to identify markers correlated with metastasis. Here, we apply a protein-network-based approach that identifies markers not as individual genes but as subnetworks extracted from protein interaction databases. The resulting subnetworks provide novel hypotheses for pathways involved in tumor progression. Although genes with known breast cancer mutations are typically not detected through analysis of differential expression, they play a central role in the protein network by interconnecting many differentially expressed genes. We find that the subnetwork markers are more reproducible than individual marker genes selected without network information, and that they achieve higher accuracy in the classification of metastatic versus non-metastatic tumors.

Computational prediction of protein-protein interactions

Recently a number of computational approaches have been developed for the prediction of protein-protein interactions. Complete genome sequencing projects have provided the vast amount of information needed for these analyses. These methods utilize the structural, genomic, and biological context of proteins and genes in complete genomes to predict protein interaction networks and functional linkages between proteins. Given that experimental techniques remain expensive, time-consuming, and labor-intensive, these methods represent an important advance in proteomics. Some of these approaches utilize sequence data alone to predict interactions, while others combine multiple computational and experimental datasets to accurately build protein interaction maps for complete genomes. These methods represent a complementary approach to current high-throughput projects whose aim is to delineate protein interaction maps in complete genomes. We will describe a number of computational protocols for protein interaction prediction based on the structural, genomic, and biological context of proteins in complete genomes, and detail methods for protein interaction network visualization and analysis.

Activation of Glycogen Synthase Kinase 3β Promotes the Intermolecular Association of Tau

Tau is hyperphosphorylated and undergoes proteolysis in Alzheimer disease brain. Caspase-cleaved tau efficiently forms fibrillary structures in vitro and in situ. Glycogen synthase kinase 3beta (GSK3beta) phosphorylates tau and induces the aggregation of caspase-cleaved tau in situ. Given the hypothesis that increased association of tau precedes the formation of fibrillar structures, we generated a cell model to quantitate the extent of tau association in situ using fluorescence resonance energy transfer (FRET) microscopy. The cyan and yellow fluorescent proteins were attached to full-length (T4) and caspase-cleaved (T4C3) tau at either the N or C termini, and a pair of cyan and yellow fluorescent protein-tagged tau were co-transfected into human embryonic kidney cells. The FRET efficiency was examined in the presence of a constitutively active or a kinase-dead GSK3beta. Active GSK3beta significantly increased FRET efficiency with both T4 and T4C3, indicating that GSK3beta activation resulted in an increase in the self-association of both T4 and T4C3, but interestingly only T4 is efficiently phosphorylated by GSK3beta. There was no significant difference in FRET efficiency between T4 and T4C3, although only T4C3 in the presence of active GSK3beta leads to the formation of Sarkosyl-insoluble inclusions. These FRET studies demonstrate that GSK3beta facilitates the association of T4 and T4C3, and the presence of caspase-cleaved tau is necessary for the evolution of tau oligomers into Sarkosyl-insoluble inclusions even though it is not extensively phosphorylated. These data imply that increased association of tau should not be regarded as a direct indicator of the formation of insoluble tau aggregates.

Imaging protein interactions with bioluminescence resonance energy transfer (BRET) in plant and mammalian cells and tissues

FRET is a well established method for cellular and subcellular imaging of protein interactions. However, FRET obligatorily necessitates fluorescence excitation with its concomitant problems of photobleaching, autofluorescence, phototoxicity, and undesirable stimulation of photobiological processes. A sister technique, bioluminescence resonance energy transfer (BRET), avoids these problems because it uses enzyme-catalyzed luminescence; however, BRET signals usually have been too dim to image effectively in the past. Using a new generation electron bombardment-charge-coupled device camera coupled to an image splitter, we demonstrate that BRET can be used to image protein interactions in plant and animal cells and in tissues; even subcellular imaging is possible. We have applied this technology to image two different protein interactions: (i) dimerization of the developmental regulator, COP1, in plant seedlings; and (ii) CCAAT/enhancer binding protein alpha (C/EBPalpha) in the mammalian nucleus. This advance heralds a host of applications for imaging without fluorescent excitation and its consequent limitations.

Functional selection of a type IV pili-binding peptide that specifically inhibits Salmonella Typhi adhesion to/invasion of human monocytic cells

Salmonella enterica serovar Typhi (S. Typhi) is an important pathogen which infects humans exclusively and causes typhoid or enteric fever. Recently it has been discovered that type IVB pili, encoded by the S. Typhi pil operon located in the major pathogenicity island, may be important in the pathogenesis of epidemic enteric fever. To further investigate the roles of type IVB pili of S. Typhi, a 12-mer peptide (RQERSSLSKPVV), binding to the structural protein PilS of the type IVB pili of S. Typhi, was isolated with a ribosome display system. This peptide was designated as peptide R. We found that peptide R inhibited adhesion to/invasion of human monocytic THP-1 cells by piliated S. Typhi bacteria, but had no effects on nonpiliated S. Typhi bacteria. A random 12-mer peptide, of size and solubility equal to peptide R, served as a control on the specificity of peptide R. The specific interaction and binding equilibrium between the 12-mer peptide R and PilS protein was determined by isothermal titration calorimetry (ITC) and a binding constant Ka determined to be between 0.4 x 10(5) and 2.2 x 10(5)L mol(-1). Our findings suggest that the type IV pili-binding peptide R holds potential as an antibacterial peptide effective against S. Typhi infections, both in terms of prevention and therapeutic treatment. The data further provide insights into the understanding of the pathogenic roles of the type IVB pili of S. Typhi.

Interactome-transcriptome analysis reveals the high centrality of genes differentially expressed in lung cancer tissues

Motivation

Global protein interaction network (interactome) analysis provides an effective way to understand the relationships between genes. Through this approach, it was demonstrated that the essential genes in yeast tend to be highly connected as well as connected to other highly connected genes. This is in contrast to the genes that are not essential, which share neither of these properties. Using a similar interactome-transcriptome approach, the topological features in the interactome of differentially expressed genes in lung squamous cancer tissues are assessed.

Results

This analysis reveals that the genes that are differentially elevated, as obtained from the microarray gene profiling data, in cancer are well connected, whereas the suppressed genes and randomly selected ones are less so. These results support the notion that a topological analysis of cancer genes using protein interaction data will allow the placement of the list of genes, often of the disparate nature, into the global, systematic context of the cell. The result of this type of analysis may provide the rationale for therapeutic targets in cancer treatment.

Chiral recognition of dextran sulfate with d- and l-cystine studied by multiwavelength surface plasmon resonance

A multiwavelength surface plasmon resonance (mwSPR) approach has been developed to study the chiral discrimination between D- and L-cystine (Cys). A monolayer of the two enantiomers was separately assembled on a pair of gold films of about 50 nm in thickness and their resonance wavelength shifts, Deltalambda, were measured under a continuous flow of an identical chiral probe solution. Dextran sulfate (DS) was found to be an excellent chiral probe because it has rich chiral centers and is large enough to produce sensitive mwSPR response. The chiral discrimination was investigated either by Deltalambda(max), the maximum resonance wavelength shift in recognition equilibrium, or by recognition kinetics (Deltalambda vs time). The equilibrium data showed that D-Cys yielded always the smaller Deltalambda(max) as compared to L-Cys at pH 5.0 or above. This differentiation was enlarged by raising the probe content and became naught at pH <4.5. The kinetic results showed that, as pH increased from 5.0 to 7.5, the non-equilibrium Deltalambda for D-Cys rose above the level for L-Cys at the first 30s of recognition but came back gradually to its equilibrium position after about 150 s, with crossing at 50--150 s depending on DS concentration. This phenomenon was thought to be the result of molecular orientation adjustment after DS binding to D-Cys. Both kinetic and thermodynamic mechanisms were thus considered to be deeply involved in the investigated chiral recognition system.

Protein synthesis by pure translation systems

We have developed a partially recombinant, cell-free, protein-synthesis system reconstituted solely from those essential elements of the Escherichia coli translation system, termed protein synthesis using recombinant elements (PURE). It provides higher reaction controllability in comparison to crude cell-free protein-synthesis systems for translation studies and biotechnology applications. The PURE system stands out among translation methods in that it provides not only a simple and unique "reverse" purification method of separating the synthesized protein from reaction mixture, but also that the system can be tailor-made according to individual protein requirements. In this paper, two new approaches to obtaining active proteins are described: the use of molecular chaperones, and modification of the reaction conditions. Several possible applications of the PURE system are also discussed.

Molecular recognition by mass spectrometry

A recent major advance in the field of mass spectrometry in the biomolecular sciences is represented by the study of the supramolecular interactions among two or more partners in the gas phase. A great deal of chemistry and most of biochemistry concerns molecular interactions taking place in solution. The electrospray technique, which allows direct sampling from solution, and soft ionization of the solute without deposition into the analyte of large amounts of energy, guarantees in many cases the survival of noncovalent bondings and, hence, the direct analysis of the supramolecular complexes present in the condensed phase. The proper preparation of the solution to be studied and also the expert and accurate setting and use of the instrumental parameters are the prerequisites for gaining results as to the specific interactions between, for instance, a protein conformationally modified by its specific metal ion, eventually, and a ligand molecule. The analysis of the charge state of the protein itself and of the modifications of the complex integrity by activating collisions are also methods for studying the biomolecule-molecule interactions. Accordingly, this new mass spectrometric approach to the supramolecular chemistry, which could be also defined as 'supramolecular mass spectrometry', allows the study of ion-protein, protein-protein, protein-ligand and DNA-drug interactions. Chiral recognition can also be performed in the gas phase, studying by electrospray mass spectrometry the fragmentation of diastereomeric complex ions. Not the least, a deep insight can also be obtained into the formation and nature of inclusion complexes like those formed with crown ethers, cyclodextrins and calixarenes as host molecules. All these topics are treated to a certain extent in this special feature article.

Development of an Autofluorescent Translocation Biosensor System To Investigate Protein−Protein Interactions in Living Cells

Protein-protein interactions are crucial for all cellular events. To analyze protein-protein interactions in live mammalian cells, we developed novel protein translocation biosensors composed of glutathione S-transferase, mutants of GFP, and a rational combination of nuclear import and export signals. Nuclear accumulation of the cytoplasmic biosensors served as the reliable indicator, which was induced by the formation of protein complexes and could easily be detected by fluorescence microscopy. The efficacy of the system was systematically investigated by mapping the p53/mdm2 protein interaction interface. Specificity and general applicability of the biosensors were confirmed by studying additional classes of protein interaction domains (IDs), e.g., the leucine zipper IDs of Jun/Fos and the coiled-coil ID of Bcr-Abl in different cell lines. Importantly, we found that, in comparison to protein complementation assays, our system proved highly efficient and reversible and thus suited for the identification of molecular decoys to prevent specific protein-protein interactions in living cells. Reversibility was demonstrated in competition experiments by overexpressing the specific IDs or by the application of a p53/mdm2 protein interaction inhibitor. Thus, besides the convenient mapping of protein IDs in living cells, the modular translocation system has great potential to be employed in numerous cell-based assays for the identification of small-molecule protein interaction inhibitors as potential novel therapeutics.

Cellulose membrane supported peptide arrays for deciphering protein-protein interaction sites: the case of PIN, a protein with multiple natural partners

Cellulose membrane supported peptide arrays, prepared according to the Spot method, allow the rapid identification and characterization of protein-protein interaction sites. Here, the method was used to screen reactive peptides from different proteins that bind to a single molecule, the PIN protein. PIN possesses two binding grooves, that have been shown to interact with several targets, including neuronal NO synthase, dynein intermediate chain, myosin V, the proapoptotic protein Bim, the scaffolding proteins DAP1alpha and gephyrin, and the transcription factor NRF-1. Arrays of peptides representing sequences of these targets were probed for reactivity with GST-tagged PIN, enabling the precise identification of binding motifs. Binding motifs were then minimized to seven or eight amino acid long peptides: YSKETQT for dynein IC, CDKSTQT for Bim, KDTGIQVD for nNOS, QSVGVQV for DAP1alpha and EDKNTMTD for myosin V. Alascan and substitution analysis provided proof that the Gln residue is critical for the interaction and cannot be easily replaced. Positions -1 and +1, just flanking the pivotal Gln, are also important; they consist of hydrophobic residues (Thr, Val) that could only be replaced by hydrophobic or aromatic amino acids. Position -4 is also critical for binding, with its Asp or Ser being replaceable to some extent. Alignment of sequences of proteins known to bind PIN shows that the most frequent amino acids in the motif are DKGTQT, consistent with the Spot results. We postulate that the degenerate character of binding to PIN is based on the propensity of several sequences to adopt a beta-strand conformation that allows the Gln residue to position itself in the PIN channel and on the conformational breathing of the PIN binding groove.

Protein-protein interaction between monomers of coliphage HK022 excisionase

Excisionase (Xis) is an accessory protein that is required for the site-specific excision reaction of the coliphages HK022 and lambda. Xis binds in a strong cooperative manner to two tandem binding sites (X1 and X2) located on the P arm of the attachment (att) sites on the phage genome. As a result of crosslinking experiments in vivo and in vitro of Xis-overexpressing cells, by gel filtration of purified Xis and by FRET analyses we show that Xis monomers of HK022 interact and form dimers that are not dependent on the single Cys residue of the protein and on the presence of DNA. The formation of the dimers may explain the strong binding cooperativity of Xis to its sites on DNA.

Single-molecule imaging of cooperative assembly of gamma-hemolysin on erythrocyte membranes

Single-molecule fluorescence imaging was used to investigate assembly of Staphylococcus aureus LukF and HS monomers into pore-forming oligomers (gamma-hemolysin) on erythrocyte membranes. We distinguished the hetero-oligomers from the monomers, as indicated by fluorescence resonance energy transfer between different dyes attached to monomeric subunits. The stoichiometry of LukF (donor) and HS (acceptor) subunits in oligomers was deduced from the acceptor emission intensities during energy transfer and by direct acceptor excitation, respectively. Based on populations of monomeric and oligomeric intermediates, we estimated 11 sequential equilibrium constants for the assembly pathway, beginning with membrane binding of monomers, proceeding through single pore oligomerization, and culminating in the formation of clusters of pores. Several stages are highly cooperative, critically enhancing the efficiency of assembly.

Locating a Protein−Protein Interaction in Living Cells via SplitRenillaLuciferase Complementation

For spatial and quantitative kinetic analysis of protein-protein interactions (PPIs) in living mammalian cells, a method was developed in which PPI-induced complementation of split Renilla luciferase triggers spontaneous emission of luminescence using a cell membrane permeable substrate, coelenterazine. This split Renilla luciferase complementation readout was shown to work for locating a PPI between the tyrosine-phosphorylated peptide (Y941) of IRS-1 and the SH2 domain of PI3K among insulin signaling pathways in living Chinese hamster ovary cells overexpressing human insulin receptors (CHO-HIR). It was thereby found that the insulin-stimulated interaction occurred near the plasma membrane in the cytosol.

Activity of coliphage HK022 excisionase (Xis) in the absence of DNA binding

A mutated excisionase (Xis) protein of coliphage HK022 whose single Cys residue was replaced by Ser does not bind to its two tandem binding sites (X1, X2) on the P arm of attR. Despite its DNA-binding inability the protein showed 30% excision activity of the wild type Xis both in vitro and in vivo. This partial activity is attributed to the interaction of Xis with integrase that is retained in the mutant protein. This protein-protein interaction occurs in the absence of DNA binding.

Visualization of Na,K-ATPase interacting proteins using FRET technique

Signaling transduction mediated by protein aggregates within specific microdomains has been receiving increased attention. We previously showed that Na,K-ATPase, partially inhibited by ouabain, induces intracellular calcium (Ca(2+)) oscillations which involve Ca(2+) release from the endoplasmic reticulum (ER). Plasma membrane bound Na,K-ATPase and proteins in the ER are in close proximity to each other, and signal transduction may occur via a physical interaction or a microdomain. To study these signaling pathways and intricate microenvironments, sophisticated methods are required. One way to detect molecular interactions in the nanometer scale (1-10 nm) is fluorescence resonance energy transfer (FRET). Thus, FRET provides vital insight into the action of Na,K-ATPase to trigger intracellular signaling events.

Using the Ras Recruitment System to Identify PP2A–B55-Interacting Proteins

The RRS system facilitated the discovery of hitherto unknown interactions with the PP2A-B55 subunit. The advantages of the system lie in its ability to identify interactions that may not be detected by traditional yeast two-hybrid systems. The RRS can thus provide a complementary genetic approach to the identification of protein-protein interactions.

Co-evolutionary analysis reveals insights into protein-protein interactions

Protein-protein interactions play crucial roles in biological processes. Experimental methods have been developed to survey the proteome for interacting partners and some computational approaches have been developed to extend the impact of these experimental methods. Computational methods are routinely applied to newly discovered genes to infer protein function and plausible protein-protein interactions. Here, we develop and extend a quantitative method that identifies interacting proteins based upon the correlated behavior of the evolutionary histories of protein ligands and their receptors. We have studied six families of ligand-receptor pairs including: the syntaxin/Unc-18 family, the GPCR/G-alpha's, the TGF-beta/TGF-beta receptor system, the immunity/colicin domain collection from bacteria, the chemokine/chemokine receptors, and the VEGF/VEGF receptor family. For correlation scores above a defined threshold, we were able to find an average of 79% of all known binding partners. We then applied this method to find plausible binding partners for proteins with uncharacterized binding specificities in the syntaxin/Unc-18 protein and TGF-beta/TGF-beta receptor families. Analysis of the results shows that co-evolutionary analysis of interacting protein families can reduce the search space for identifying binding partners by not only finding binding partners for uncharacterized proteins but also recognizing potentially new binding partners for previously characterized proteins. We believe that correlated evolutionary histories provide a route to exploit the wealth of whole genome sequences and recent systematic proteomic results to extend the impact of these studies and focus experimental efforts to categorize physiologically or pathologically relevant protein-protein interactions.

Quantitative proteomics: the copy number of pyruvate dehydrogenase is more than 10(2)-fold lower than that of complex III in human mitochondria

Pyruvate dehydrogenase (PDH) and complex III are two key protein complexes in mitochondrial metabolic activity. Using a novel quantitative Western blotting method, we find that PDH and complex III exist at a steady-state ratio of 1:100, 1:128 and 1:202 in HeLa cell extracts, fibroblast mitochondria and heart tissue mitochondria, respectively. This difference in stoichiometry is reflected in the immunogold labeling intensities of the two complexes and by the much more sparse distribution of PDH in fluorescence microscopy. In Rho0 fibroblasts there is a 64% reduction of complex III but the concentration of PDH remains the same as wild-type.

In vitro selection for catalytic activity with ribosome display

We report what is, to our knowledge, the first in vitro selection for catalytic activity based on catalytic turnover by using ribosome display, a method which does not involve living cells at any step. RTEM-beta-lactamase was functionally displayed on ribosomes as a complex with its encoding mRNA. We designed and synthesized a mechanism-based inhibitor of beta-lactamase, biotinylated ampicillin sulfone, appropriate for selection of catalytic activity of the ribosome-displayed beta-lactamase. This derivative of ampicillin inactivated beta-lactamase in a specific and irreversible manner. Under appropriate selection conditions, active RTEM-beta-lactamase was enriched relative to an inactive point mutant over 100-fold per ribosome display selection cycle. Selection for binding, carried out with beta-lactamase inhibitory protein (BLIP), gave results similar to selection with the suicide inhibitor, indicating that ribosome display is similarly efficient in catalytic activity and affinity selections. In the future, the capacity to select directly for enzymatic activity using an entirely in vitro process may allow for a significant increase in the explorable sequence space relative to existing strategies.

Biotin-tagged cDNA expression libraries displayed on lambda phage: a new tool for the selection of natural protein ligands

cDNA expression libraries displayed on lambda phage have been successfully employed to identify partners involved in antibody-antigen, protein- protein and DNA-protein interactions and represent a novel approach to functional genomics. However, as in all other cDNA expression libraries based on fusion to a carrier polypeptide, a major issue of this system is the absence of control over the translation frame of the cDNA. As a consequence, a large number of clones will contain lambda D/cDNA fusions, resulting in the foreign sequence being translated on alternative reading frames. Thus, many phage will not display natural proteins, but could be selected, as they mimic the binding properties of the real ligand, and will hence interfere with the selection outcome. Here we describe a novel lambda vector for display of exogenous peptides at the C-terminus of the capsid D protein. In this vector, translation of fusion peptides in the correct reading frame allows efficient in vivo biotinylation of the chimeric phage during amplification. Using this vector system we constructed three libraries from human hepatoma cells, mouse hepatocytic MMH cells and from human brain. Clones containing open reading frames (ORFs) were rapidly selected by streptavidin affinity chromatography, leading to biological repertoires highly enriched in natural polypeptides. We compared the selection outcome of two independent experiments performed using an anti-GAP-43 monoclonal antibody on the human brain cDNA library before and after ORF enrichment. A significant increase in the efficiency of identification of natural target peptides with very little background of false-positive clones was observed in the latter case.

Aib-based peptide backbone as scaffolds for helical peptide mimics

Helical peptides that can intervene and disrupt therapeutically important protein-protein interactions are attractive drug targets. In order to develop a general strategy for developing such helical peptide mimics, we have studied the effect of incorporating alpha-amino isobutyric acid (Aib), an amino acid with strong preference for helical backbone, as the sole helix promoter in designed peptides. Specifically, we focus on the hdm2-p53 interaction, which is central to development of many types of cancer. The peptide corresponding to the hdm2 interacting part of p53, helical in bound state but devoid of structure in solution, served as the starting point for peptide design that involved replacement of noninteracting residues by Aib. Incorporation of Aib, while preserving the interacting residues, led to significant increase in helical structure, particularly at the C-terminal region as judged by nuclear magnetic resonance and circular dichroism. The interaction with hdm2 was also found to be enhanced. Most interestingly, trypsin cleavage was found to be retarded by several orders of magnitude. We conclude that incorporation of Aib is a feasible strategy to create peptide helical mimics with enhanced receptor binding and lower protease cleavage rate.

Protein-dependent ribozymes report molecular interactions in real time

Most approaches to monitoring interactions between biological macromolecules require large amounts of material, rely upon the covalent modification of an interaction partner, or are not amenable to real-time detection. We have developed a generalizable assay system based on interactions between proteins and reporter ribozymes. The assay can be configured in a modular fashion to monitor the presence and concentration of a protein or of molecules that modulate protein function. We report two applications of the assay: screening for a small molecule that disrupts protein binding to its nucleic acid target and screening for protein protein interactions. We screened a structurally diverse library of antibiotics for small molecules that modulate the activity of HIV-1 Rev-responsive ribozymes by binding to Rev. We identified an inhibitor that subsequently inhibited HIV-1 replication in cells. A simple format switch allowed reliable monitoring of domain-specific interactions between the blood-clotting factor thrombin and its protein partners. The rapid identification of interactions between proteins or of compounds that disrupt such interactions should have substantial utility for the drug-discovery process.

In silico two-hybrid system for the selection of physically interacting protein pairs

Deciphering the interaction links between proteins has become one of the main tasks of experimental and bioinformatic methodologies. Reconstruction of complex networks of interactions in simple cellular systems by integrating predicted interaction networks with available experimental data is becoming one of the most demanding needs in the postgenomic era. On the basis of the study of correlated mutations in multiple sequence alignments, we propose a new method (in silico two-hybrid, i2h) that directly addresses the detection of physically interacting protein pairs and identifies the most likely sequence regions involved in the interactions. We have applied the system to several test sets, showing that it can discriminate between true and false interactions in a significant number of cases. We have also analyzed a large collection of E. coli protein pairs as a first step toward the virtual reconstruction of its complete interaction network.

Theoretical and computational advances in biomolecular NMR spectroscopy

Recent developments in experimental and computational aspects of NMR spectroscopy have had a significant impact on the accuracy and speed of macromolecular structure determination in solution, particularly with regard to systems of high complexity (such as protein complexes). These include experiments designed to provide long-range orientational and translational restraints, improvements in internal coordinate dynamics used for simulated annealing, and the development of database potentials of mean force to improve the description of the non-bonded contacts.

Software for signaling networks, electronic and cellular

Cellular signaling networks have many similarities with electronic circuits. Therefore, the tools used to test and analyze electronic circuits can be adapted to analyze cellular signaling processes. Lok describes some of these signaling network analysis tools, their underlying principles, and their limitations.