A Novel Co-immunoprecipitation Protocol Based on Protoplast Transient Gene Expression for Studying Protein–protein Interactions in Rice

Protein–protein interactions constitute the regulatory network that coordinates diverse cellular functions. Co-immunoprecipitation (co-IP) is a widely used and effective technique to study protein–protein interactions in living cells. However, the time and cost for the preparation of a highly specific antibody is the major disadvantage associated with this technique. In the present study, a co-IP system was developed to detect protein–protein interactions based on an improved protoplast transient expression system by using commercially available antibodies. This co-IP system eliminates the need for specific antibody preparation and transgenic plant production. Leaf sheaths of rice green seedlings were used for the protoplast transient expression system which demonstrated high transformation and co-transformation efficiencies of plasmids. The transient expression system developed by this study is suitable for subcellular localization and protein detection. This work provides a rapid, reliable, and cost-effective system to study transient gene expression, protein subcellular localization, and characterization of protein–protein interactions in vivo.     

Photoactivatable Reagents Based on Aryl(trifluoromethyl)diazirines: Synthesis and Application for Studying Nucleic Acid–Protein Interactions

Recent data on the synthesis of photoactivatable derivatives of nucleic acids and proteins on the basis of aryl(trifluoromethyl)diazirines—analogs of nucleosides, nucleotides, oligonucleotides, as well as amino acids and peptides—are reviewed. The synthesis of bi- and polyfunctional photoactivatable reagents, including those containing a cleavable function, designed for postsynthetic modification of biopolymers is described. Data are given on the use of the photoactivatable derivatives for studying nucleic acid–protein interactions by the method of photoaffinity labeling. Special consideration is paid to the results obtained by the authors" team in cooperation with other researchers as well as graduate students of the Chemistry of Natural Products Chair, Chemical Faculty, Moscow State University and destined to solve various scientific tasks in the domain of nucleic acid–protein recognition with the use of photoaffinity crosslinking.     

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.     

Membrane Domains Based on Ankyrin and Spectrin Associated with Cell–Cell Interactions

Nodes of Ranvier and axon initial segments of myelinated nerves, sites of cell–cell contact in early embryos and epithelial cells, and neuromuscular junctions of skeletal muscle all perform physiological functions that depend on clustering of functionally related but structurally diverse ion transporters and cell adhesion molecules within microdomains of the plasma membrane. These specialized cell surface domains appeared at different times in metazoan evolution, involve a variety of cell types, and are populated by distinct membrane-spanning proteins. Nevertheless, recent work has shown that these domains all share on their cytoplasmic surfaces a membrane skeleton comprised of members of the ankyrin and spectrin families. This review will summarize basic features of ankyrins and spectrins, and will discuss emerging evidence that these proteins are key players in a conserved mechanism responsible for assembly and maintenance of physiologically important domains on the surfaces of diverse cells.Spectrins are flexible rods 0.2 microns in length with actin-binding sites at each end (Shotton et al. 1979; Bennett et al. 1982) (Fig. 1A). Spectrins are assembled from α and β subunits, each comprised primarily of multiple copies of a 106-amino acid repeat (Speicher and Marchesi 1984). In addition to the canonical 106-residue repeat, β spectrins also have a carboxy-terminal pleckstrin homology domain (Zhang et al. 1995; Macias et al. 1994) and tandem amino-terminal calponin homology domains (Bañuelos et al. 1998), whereas α spectrins contain an Src homology domain 3 (SH3) site (Musacchio et al. 1992), a calmodulin-binding site (Simonovic et al. 2006), and EF hands (Travé et al. 1995) (Fig. 1A). Spectrin α and β subunits are assembled antiparallel and side-to-side into heterodimers, which in turn are associated head-to-head to form tetramers (Clarke 1971; Shotton et al. 1979; Davis and Bennett 1983) (Fig. 1A). In human erythrocytes, in which spectrin was first characterized (Marchesi and Steers 1968; Clarke 1971), actin oligomers containing 10–14 monomers are each linked to five to six spectrin tetramers by accessory proteins to form a geodesic domelike structure that has been resolved by electron microscopy (Byers and Branton 1985). The principal proteins at the spectrin–actin junction are protein 4.1, adducin, tropomyosin, tropomodulin, and dematin (Bennett and Baines 2001) (Open in a separate windowFigure 1.Domain structure and variants of spectrin and ankyrin proteins. (A) Molecular domains of spectrins: Two α spectrins and five β spectrins are shown. Spectrins are comprised of modular units called spectrin repeats (yellow). Other domains such as the ankyrin binding domain (purple), Src-homology domain 3 (SH3, blue), EF-hand domain (red), and calmodulin-binding domain (green) promote interactions with binding targets important for spectrin function. The pleckstrin homology domain (black) promotes association with the plasma membrane and the actin binding domain (grey) tethers the spectrin-based membrane skeleton to the underlying actin cytoskeleton. (B) The spectrin tetramer, the fundamental unit of the spectrin-based membrane skeleton. The spectrin repeat domains of α and β spectrin associate end-to-end to form heterodimers. Heterodimers associate laterally in an antiparallel fashion to form tetramers. The tetramers can then associate end-to-end to form extended macromolecules that link into a geodesic dome shape directly underneath the plasma membrane. (C) Molecular domains present in canonical ankyrins. The membrane binding domain of ankyrin isoforms (orange) is comprised of 24 ANK repeats. The spectrin binding domain (green-blue) allows ankyrins to coordinate integral membrane proteins to the membrane skeleton. The death domain (pink) is the most highly conserved domain. The regulatory domain (brown) is the most variable region of ankyrins. The regulatory domain interacts intramolecularly with the membrane binding domain to modulate ankyrin’s affinity for other binding partners. All ankyrins and spectrins are subject to alternative splicing, which further increases their functional diversity.

Table 1.

Binding partners of spectrin and ankyrins

DAMpred: Recognizing Disease-Associated nsSNPs through Bayes-Guided Neural-Network Model Built on Low-Resolution Structure Prediction of Proteins and Protein–Protein Interactions

Nearly one-third of non-synonymous single-nucleotide polymorphism (nsSNPs) are deleterious to human health, but recognition of the disease-associated mutations remains a significant unsolved problem. We proposed a new algorithm, DAMpred, to identify disease-causing nsSNPs through the coupling of evolutionary profiles with structure predictions of proteins and protein–protein interactions. The pipeline was trained by a novel Bayes-guided artificial neural network algorithm that incorporates posterior probabilities of distinct feature classifiers with the network training process. DAMpred was tested on a large-scale data set involving 10,635 nsSNPs from 2154 ORFs in the human genome and recognized disease-associated nsSNPs with an accuracy 0.80 and a Matthews correlation coefficient of 0.601, which is 9.1% higher than the best of other state-of-the-art methods. In the blind test on the TP53 gene, DAMpred correctly recognized the mutations causative of Li–Fraumeni-like syndrome with a Matthews correlation coefficient that is 27% higher than the control methods. The study demonstrates an efficient avenue to quantitatively model the association of nsSNPs with human diseases from low-resolution protein structure prediction, which should find important usefulness in diagnosis and treatment of genetic diseases.     

Protein–protein interactions and selection: yeast-based approaches that exploit guanine nucleotide-binding protein signaling

For elucidating protein–protein interactions, many methodologies have been developed during the past two decades. For investigation of interactions inside cells under physiological conditions, yeast is an attractive organism with which to quickly screen for hopeful candidates using versatile genetic technologies, and various types of approaches are now available.Among them, a variety of unique systems using the guanine nucleotide-binding protein (G-protein) signaling pathway in yeast have been established to investigate the interactions of proteins for biological study and pharmaceutical research. G-proteins involved in various cellular processes are mainly divided into two groups: small monomeric G-proteins,and heterotrimeric G-proteins. In this minireview, we summarize the basic principles and applications of yeast-based screening systems, using these two types of G-protein, which are typically used for elucidating biological protein interactions but are differentiated from traditional yeast two-hybrid systems.     

Oligodendrocyte–Neuron Interactions: Impact on Myelination and Brain Function

In the past, glial cells were considered to be ‘glue’ cells whose primary role was thought to be merely filling gaps in neural circuits. However, a growing number of reports have indicated the role of glial cells in higher brain function through their interaction with neurons. Myelin was originally thought to be just a sheath structure surrounding neuronal axons, but recently it has been shown that myelin exerts effects on the conduction velocity of neuronal axons even after myelin formation. Therefore, the investigation of glial cell properties and the neuron-glial interactions is important for understanding higher brain function. Moreover, since there are many neurological disorders caused by glial abnormalities, further understanding of glial cell-related diseases and the development of effective therapeutic strategies are warranted. In this review, we focused on oligodendrocyte-neuron interactions, with particular attention on (1) axonal signals underlying oligodendrocyte differentiation and myelination, (2) neuronal activity-dependent myelination and (3) the effects of myelination on higher brain function.

     

Cystatin B and SOD1: Protein–Protein Interaction and Possible Relation to Neurodegeneration

Cystatin B (CSTB), an inhibitor of the cysteine proteases, belongs to the cathepsin family and it is known to interact with a number of proteins involved in cytoskeletal organization. CSTB has an intrinsic tendency to form aggregates depending on the redox environment. The gene encoding for CSTB is frequently mutated in association with the rare neurodegenerative condition progressive myoclonus epilepsy. Increased levels of CSTB have been observed in the spinal cord of transgenic mice modeling SOD1-linked familial amyotrophic lateral sclerosis, a fatal neurodegenerative disease affecting motoneurons. In the present study, we have investigated the relationship occurring between the expression of SOD1 and CSTB either wild-type or double-cysteine substitution mutant (Cys 3 and Cys 64). Whether or not there is a physical interaction between the two proteins was also investigated in overexpression experiments using a human neuroblastoma cell line and mouse-immortalized motoneurons. Here we report evidences for a reciprocal influence of CSTB and SOD1 at the gene expression level and for a direct interaction of the two proteins.     

Protein τ-Mediated Effects on Rat Hippocampal Choline Transporters CHT1 and τ-Amyloid β Interactions

It is suggested that intracellular tau protein (τ), when released extracellularly upon neuron degeneration, could evoke direct toxic effects on the cholinergic neurotransmitter system through muscarinic receptors and thus contribute to the pathogenesis of Alzheimer’s disease. In this study, we evaluated the in vitro effects of six naturally occurring monomeric τ isoforms on rat hippocampal synaptosomal choline transporters CHT1 (large transmembrane proteins associated with high-affinity choline transport and vulnerable to actions of amyloid β peptides (Aβ) applied in vitro or in vivo). Some τ isoforms at nM concentrations inhibited choline transport in a dose- and time-dependent saturable manner (352 = 441 > 410 = 383 > 381 = 412) and effects were associated with changes in the Michaelis constant rather than in maximal velocity. Moreover, the actions of τ 352/441 were not influenced by previous depolarisation of synaptosomes or by previous depletion of membrane cholesterol. Specific binding of [3H]hemicholinium-3 was not significantly altered by τ 352/441 at higher nM concentrations. Results of in vitro tests on CHT1 transporters from cholesterol-depleted synaptosomes supported interactions between Aβ 1-40 and τ 352. In addition, we developed surface plasmon resonance biosensors to monitor complexes of Aβ 1-42 and τ 352 using a sandwich detection format. It seems, therefore, that protein τ, similar to Aβ peptides, can contribute to the pathogenesis of Alzheimer’s disease through its actions on CHT1 transporters. However, the interaction mechanisms are quite different (τ probably exerts its effects through direct interactions of microtubule binding repeats with extracellular portions of the CHT1 protein without influencing the choline recognition site, Aβ rather through lipid rafts in the surrounding membranes). An N-terminal insert of τ is not necessary but the N-terminal projection domain plays a role. The developed biosensor will be used to detect Aβ–τ complexes in cerebrospinal fluid in order to evaluate them as prospective biomarkers of Alzheimer′s disease.     

S-linked protein homocysteinylation: identifying targets based on structural, physicochemical and protein–protein interactions of homocysteinylated proteins

An elevated level of homocysteine, a thiol-containing amino acid is associated with a wide spectrum of disease conditions. A majority (>80 %) of the circulating homocysteine exist in protein-bound form. Homocysteine can bind to free cysteine residues in the protein or could cleave accessible cysteine disulfide bonds via thiol disulfide exchange reaction. Binding of homocysteine to proteins could potentially alter the structure and/or function of the protein. To date only 21 proteins have been experimentally shown to bind homocysteine. In this study we attempted to identify other proteins that could potentially bind to homocysteine based on the criteria that such proteins will have significant 3D structural homology with the proteins that have been experimentally validated and have solvent accessible cysteine residues either with high dihedral strain energy (for cysteine–cysteine disulfide bonds) or low pKa (for free cysteine residues). This analysis led us to the identification of 78 such proteins of which 68 proteins had 154 solvent accessible disulfide cysteine pairs with high dihedral strain energy and 10 proteins had free cysteine residues with low pKa that could potentially bind to homocysteine. Further, protein–protein interaction network was built to identify the interacting partners of these putative homocysteine binding proteins. We found that the 21 experimentally validated proteins had 174 interacting partners while the 78 proteins identified in our analysis had 445 first interacting partners. These proteins are mainly involved in biological activities such as complement and coagulation pathway, focal adhesion, ECM-receptor, ErbB signalling and cancer pathways, etc. paralleling the disease-specific attributes associated with hyperhomocysteinemia.     

Computational Prediction of Protein–Protein Interaction Networks: Algo-rithms and Resources

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.     

Interactome of signaling networks in wheat: the protein–protein interaction between TaRAR1 and TaSGT1

RAR1 and SGT1 are required for development and disease resistance in plants. In many cases, RAR1 and SGT1 regulate the resistance (R)-gene-mediated defense signaling pathways. Lr21 is the first identified NBS-LRR-type R protein in wheat and is required for resistance to the leaf rust pathogen. The Lr21-mediated signaling pathways require the wheat homologs of RAR1, SGT1, and HSP90. However, the molecular mechanisms of the Lr21-mediated signaling networks remain unknown. Here I present the DNA and protein sequences of TaRAR1 and TaSGT1, and demonstrate for the first time a direct protein-protein interaction between them.     

Protein–protein interactions involving voltage-gated sodium channels: Post-translational regulation,intracellular trafficking and functional expression

Voltage-gated sodium channels (VGSCs), classically known to play a central role in excitability and signalling in nerves and muscles, have also been found to be expressed in a range of ‘non-excitable’ cells, including lymphocytes, fibroblasts and endothelia. VGSC abnormalities are associated with various diseases including epilepsy, long-QT syndrome 3, Brugada syndrome, sudden infant death syndrome and, more recently, various human cancers. Given their pivotal role in a wide range of physiological and pathophysiological processes, regulation of functional VGSC expression has been the subject of intense study. An emerging theme is post-translational regulation and macro-molecular complexing by protein–protein interactions and intracellular trafficking, leading to changes in functional VGSC expression in plasma membrane. This partially involves endoplasmic reticulum associated degradation and ubiquitin–proteasome system. Several proteins have been shown to associate with VGSCs. Here, we review the interactions involving VGSCs and the following proteins: p11, ankyrin, syntrophin, β-subunit of VGSC, papin, ERM and Nedd4 proteins. Protein kinases A and C, as well as Ca²⁺-calmodulin dependant kinase II that have also been shown to regulate intracellular trafficking of VGSCs by changing the balance of externalization vs. internalization, and an effort is made to separate these effects from the short-term phosphorylation of mature proteins in plasma membrane. Two further modulatory mechanisms are reciprocal interactions with the cytoskeleton and, late-stage, activity-dependant regulation. Thus, the review gives an updated account of the range of post-translational molecular mechanisms regulating functional VGSC expression. However, many details of VGSC subtype-specific regulation and pathophysiological aspects remain unknown and these are highlighted throughout for completeness.