Protein complementation assays: Approaches for the in vivo analysis of protein interactions

The in vivo identification and characterization of protein-protein interactions (PPIs) are essential to understand cellular events in living organisms. In this review, we focus on protein complementation assays (PCAs) that have been developed to detect in vivo protein interactions as well as their modulation or spatial and temporal changes. The uses of PCAs are increasing, spanning different areas such as the study of biochemical networks, screening for protein inhibitors and determination of drug effects. Emphasis is given to approaches that rely on signals of spectroscopic nature (i.e. fluorescence or luminescence), the ones that are more directly related to bioimaging.     

Fluorescent protein recruitment assay for demonstration and analysis of in vivo protein interactions in plant cells and its application to Tobacco mosaic virus movement protein

We describe a simple fluorescent protein‐based method to investigate interactions with a viral movement protein in living cells that relies on the in vivo re‐localization of proteins in the presence of their interaction partners. We apply this method in combination with fluorescence lifetime imaging microscopy (FLIM) to demonstrate that a domain of the Tobacco mosaic virus (TMV) movement protein (MP) previously predicted to mediate protein:protein interactions is dispensable for these contacts. We suggest that this method can be generalized for analysis of other protein interactions in planta.     

Computational prediction for the protein interactions of tyrosinase: Protein experimental interactome MAP

Tyrosinase (EC 1.14.18.1) is a diversely distributed enzyme in various organisms with physiological roles related to pigment production. Tyrosinase has gained the attention of researchers due to its biological functions and potential applications. In this regard, studies on the partner proteins of tyrosinase are important. In this study, we predicted the 3D structure of human tyrosinase and simulated the protein–protein interactions between tyrosinase and binding partners by using the PEIMAP algorithm. As a result, we found that tyrosinase is predicted to bind with G protein-related proteins, potassium voltage-gated channel-related proteins, and vesicle/sorting-related proteins. In particular, GIPC1, GIPC2, GIPC3, TYRP1, and DCT were predicted to primarily bind with tyrosinase. Interacting proteins (103) were secondarily bound to these 5 interacting proteins in the PEIMAP network of tyrosinase. An involvement in melanogenesis was also newly predicted by associating the predicted binding proteins. We simulated the protein–protein bindings by probing the residues of each complex facing toward the predicted site of interaction with tyrosinase. Among the interacting residues, some were predicted to dock to the active site of tyrosinase, which could affect its activity directly. Our computational predictions will be useful for elucidating the protein–protein interactions of tyrosinase and for studying its binding mechanisms and the melanin biosynthesis pathway.     

NMR analysis of protein interactions

Recent technological advances in NMR spectroscopy have alleviated the size limitations for the determination of biomolecular structures in solution. At the same time, novel NMR parameters such as residual dipolar couplings are providing greater accuracy. As this review shows, the structures of protein-protein and protein-nucleic acid complexes up to 50 kDa can now be accurately determined. Although de novo structure determination still requires considerable effort, information on interaction surfaces from chemical shift perturbations is much easier to obtain. Advances in modelling and data-driven docking procedures allow this information to be used for determining approximate structures of biomolecular complexes. As a result, a wealth of information has become available on the way in which proteins interact with other biomolecules. Of particular interest is the fact that these NMR-based methods can be applied to weak and transient protein-protein complexes that are difficult to study by other structural methods.     

Structural systems biology: modelling protein interactions

Much of systems biology aims to predict the behaviour of biological systems on the basis of the set of molecules involved. Understanding the interactions between these molecules is therefore crucial to such efforts. Although many thousands of interactions are known, precise molecular details are available for only a tiny fraction of them. The difficulties that are involved in experimentally determining atomic structures for interacting proteins make predictive methods essential for progress. Structural details can ultimately turn abstract system representations into models that more accurately reflect biological reality.     

Protein composition of human mRNPs spliced in vitro and differential requirements for mRNP protein recruitment

The deposition of proteins onto newly spliced mRNAs has far reaching consequences for their subsequent metabolism. We affinity-purified spliced human mRNPs under physiological conditions from HeLa nuclear extract and present the first comprehensive inventory of their protein composition as determined by mass spectrometry. Several proteins previously not known to be mRNP-associated were detected, including the DEAD-box helicases DDX3, DDX5, and DDX9, and the ELG, hNHN1, BCLAF1, and TRAP150 proteins. The association of some of the newly identified mRNP proteins was shown to be splicing-dependent, but not to require EJC formation. Initial recruitment of EJC proteins to the spliceosome did not require an EJC binding platform at the -20/24 region of the 5' exon. Finally, while recruitment of EJC proteins and stable EJC formation were not dependent on the cap binding complex, several of the newly identified mRNP proteins required the latter for their association with mRNPs. These results provide novel insights into the composition of spliced mRNPs and the requirements for the association of mRNP proteins with the newly spliced mRNA.     

Mass spectrometric analysis of protein interactions

Mass spectrometry is a powerful tool for identification of interaction partners and structural characterization of protein interactions because of its high sensitivity, mass accuracy and tolerance towards sample heterogeneity. Several tools that allow studies of protein interaction are now available and recent developments that increase the confidence of studies of protein interaction by mass spectrometry include quantification of affinity-purified proteins by stable isotope labeling and reagents for surface topology studies that can be identified by mass-contributing reporters (e.g. isotope labels, cleavable cross-linkers or fragment ions. The use of mass spectrometers to study protein interactions using deuterium exchange and for analysis of intact protein complexes recently has progressed considerably.     

Visualization and analysis of protein interactions

SUMMARY: We have developed a new program called InterViewer for drawing large-scale protein interaction networks in three-dimensional space. Unique features of InterViewer include (1) it is much faster than other recent implementations of drawing algorithms; (2) it can be used not only for visualizing protein interactions but also for analyzing them interactively; and (3) it provides an integrated framework for querying protein interaction databases and directly visualizes the query results. AVAILABILITY: http://wilab.inha.ac.kr/protein/     

Protein structural analysis as a tool for protein design

The analysis of known protein structures is a very valuable and indispensable tool for deciphering the complex rules relating sequence to structure in proteins. On the other hand, the design of novel proteins is certainly the most severe test of our understanding of such rules. In this report we describe our own attempt to develop appropriate tools for the investigation of known protein structure properties and their applications to the design of a novel, all β protein. The success of the design project is a demonstration of the usefulness of careful analysis of the data base of known protein structures. © 1994 John Wiley & Sons, Inc.     

Protein–protein interactions and genetic diseases: The interactome

Protein–protein interactions mediate essentially all biological processes. Despite the quality of these data being widely questioned a decade ago, the reproducibility of large-scale protein interaction data is now much improved and there is little question that the latest screens are of high quality. Moreover, common data standards and coordinated curation practices between the databases that collect the interactions have made these valuable data available to a wide group of researchers. Here, I will review how protein–protein interactions are measured, collected and quality controlled. I discuss how the architecture of molecular protein networks has informed disease biology, and how these data are now being computationally integrated with the newest genomic technologies, in particular genome-wide association studies and exome-sequencing projects, to improve our understanding of molecular processes perturbed by genetics in human diseases. This article is part of a Special Issue entitled: From Genome to Function.     

Protein protein interactions, evolutionary rate, abundance and age

Background

Does a relationship exist between a protein's evolutionary rate and its number of interactions? This relationship has been put forward many times, based on a biological premise that a highly interacting protein will be more restricted in its sequence changes. However, to date several studies have voiced conflicting views on the presence or absence of such a relationship.

Results

Here we perform a large scale study over multiple data sets in order to demonstrate that the major reason for conflict between previous studies is the use of different but overlapping datasets. We show that lack of correlation, between evolutionary rate and number of interactions in a data set is related to the error rate. We also demonstrate that the correlation is not an artifact of the underlying distributions of evolutionary distance and interactions and is therefore likely to be biologically relevant. Further to this, we consider the claim that the dependence is due to gene expression levels and find some supporting evidence. A strong and positive correlation between the number of interactions and the age of a protein is also observed and we show this relationship is independent of expression levels.

Conclusion

A correlation between number of interactions and evolutionary rate is observed but is dependent on the accuracy of the dataset being used. However it appears that the number of interactions a protein participates in depends more on the age of the protein than the rate at which it changes.     

Protein interactions within and between two F-type type IV secretion systems

Bacterial type IV secretion systems (T4SSs) can mediate conjugation. The T4SS from Neisseria gonorrhoeae possesses the unique ability to mediate DNA secretion into the extracellular environment. The N. gonorrhoeae T4SS can be grouped with F-type conjugative T4SSs based on homology. We tested 17 proteins important for DNA secretion by N. gonorrhoeae for protein interactions. The BACTH-TM bacterial two-hybrid system was successfully used to study periplasmic interactions. By determining if the same interactions were observed for F-plasmid T4SS proteins and when one interaction partner was replaced by the corresponding protein from the other T4SS, we aimed to identify features associated with the unique function of the N. gonorrhoeae T4SS as well as generic features of F-type T4SSs. For both systems, we observed already described interactions shared by homologs from other T4SSs as well as new and described interactions between F-type T4SS-specific proteins. Furthermore, we demonstrate, for the first-time, interactions between proteins with homology to the conserved T4SS outer membrane core proteins and F-type-specific proteins and we confirmed two of them by co-purification. The F-type-specific protein TraH_N was found to localize to the outer membrane and the presence of significant amounts of TraH_N in the outer membrane requires TraG_N.     

Modulation of the G protein regulator phosducin by Ca2+/calmodulin-dependent protein kinase II phosphorylation and 14-3-3 protein binding

Phototransduction is a canonical G protein-mediated cascade of retinal photoreceptor cells that transforms photons into neural responses. Phosducin (Pd) is a Gbetagamma-binding protein that is highly expressed in photoreceptors. Pd is phosphorylated in dark-adapted retina and is dephosphorylated in response to light. Dephosphorylated Pd binds Gbetagamma with high affinity and inhibits the interaction of Gbetagamma with Galpha or other effectors, whereas phosphorylated Pd does not. These results have led to the hypothesis that Pd down-regulates the light response. Consequently, it is important to understand the mechanisms of regulation of Pd phosphorylation. We have previously shown that phosphorylation of Pd by cAMP-dependent protein kinase moderately inhibits its association with Gbetagamma. In this study, we report that Pd was rapidly phosphorylated by Ca(2+)/calmodulin-dependent kinase II, resulting in 100-fold greater inhibition of Gbetagamma binding than cAMP-dependent protein kinase phosphorylation. Furthermore, Pd phosphorylation by Ca(2+)/calmodulin-dependent kinase II at Ser-54 and Ser-73 led to binding of the phosphoserine-binding protein 14-3-3. Importantly, in vivo decreases in Ca(2+) concentration blocked the interaction of Pd with 14-3-3, indicating that Ca(2+) controls the phosphorylation state of Ser-54 and Ser-73 in vivo. These results are consistent with a role for Pd in Ca(2+)-dependent light adaptation processes in photoreceptor cells and also suggest other possible physiological functions.     

Green fluorescent protein-tagged retroviral envelope protein for analysis of virus-cell interactions

Fluorescent retroviral envelope (Env) proteins were developed for direct visualization of viral particles. By fusing the enhanced green fluorescent protein (eGFP) to the N terminus of the amphotropic 4070A envelope protein, extracellular presentation of eGFP was achieved. Viruses incorporated the modified Env protein and efficiently infected cells. We used the GFP-tagged viruses for staining retrovirus receptor-positive cells, thereby circumventing indirect labeling techniques. By generating cells which conditionally expressed the GFP-tagged Env protein, we could confirm an inverse correlation between retroviral Env expression and infectivity (superinfection). eGFP-tagged virus particles are suitable for monitoring the dynamics of virus-cell interactions.