3.4.4 Determination of interaction networks
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Module description: Protein interactions The interactions between proteins are important for very numerous—if not all—biological functions. Methods to investigate protein-protein interactions:
Biochemical methods
· Co-immunoprecipitation is considered to be the gold standard assay for protein-protein interactions, especially when it is performed with endogenous (not overexpressed and not tagged) proteins. The protein of interest is isolated with a specific antibody. Interaction partners which stick to this protein are subsequently identified by western blotting. Interactions detected by this approach are considered to be real. However, this method can only verify interactions between suspected interaction partners. Thus, it is not a screening approach. A note of caution also is that immunoprecipitation experiments reveal direct and indirect interactions. Thus, positive results may indicate that two proteins interact directly or may interact via a bridging protein.
· Bimolecular Fluorescence Complementation (BiFC) is a new technique in observing the interactions of proteins. Combining with other new techniques, this method can be used to screen protein-protein interactions and their modulators.
· Affinity electrophoresis as used for estimation of binding constants, as for instance in lectin affinity electrophoresis or characterization of molecules with specific features like glycan content or ligand binding.
· Pull-down assays are a common variation of immunoprecipitation and immunoelectrophoresis and are used identically, although this approach is more amenable to an initial screen for interacting proteins.
· Label transfer can be used for screening or confirmation of protein interactions and can provide information about the interface where the interaction takes place. Label transfer can also detect weak or transient interactions that are difficult to capture using other in vitro detection strategies. In a label transfer reaction, a known protein is tagged with a detectable label. The label is then passed to an interacting protein, which can then be identified by the presence of the label.
· The yeast two-hybrid screen investigates the interaction between artificial fusion proteins inside the nucleus of yeast. This approach can identify binding partners of a protein in an unbiased manner.
· In-vivo crosslinking of protein complexes using photo-reactive amino acid analogs was introduced in 2005 by researchers from the Max Planck Institute. In this method, cells are grown with photoreactive diazirine analogs to leucine and methionine, which are incorporated into proteins. Upon exposure to ultraviolet light, the diazirines are activated and bind to interacting proteins that are within a few angstroms of the photo-reactive amino acid analog.
· Tandem affinity purification (TAP) method allows high throughput identification of protein interactions. In contrast to Y2H approach accuracy of the method can be compared to those of small-scale experiments (Collins et al., 2007) and the interactions are detected within the correct cellular environment as by co-immunoprecipitation. However, the TAP tag method requires two successive steps of protein purification and consequently it can not readily detect transient protein-protein interactions. Recent genome-wide TAP experiments were performed by Krogan et al., 2006 and Gavin et al., 2006 providing updated protein interaction data for yeast organism.
· Chemical crosslinking is often used to "fix" protein interactions in place before trying to isolate/identify interacting proteins. Common crosslinkers for this application include the non-cleavable NHS-ester crosslinker, bis-sulfosuccinimidyl suberate (BS3); a cleavable version of BS3, dithiobis(sulfosuccinimidyl propionate) (DTSSP); and the imidoester crosslinker dimethyl dithiobispropionimidate (DTBP) that is popular for fixing interactions in ChIP assays.
· Chemical crosslinking followed by high mass MALDI mass spectrometry can be used to analyze intact protein interactions in place before trying to isolate/identify interacting proteins. This method detects interactions among non-tagged proteins and is available from CovalX.
· SPINE (Strep-protein interaction experiment) uses a combination of reversible crosslinking with formaldehyde and an incorporation of an affinity tag to detect interaction partners in vivo.
· Quantitative immunoprecipitation combined with knock-down (QUICK) relies on co-immunoprecipitation, quantitative mass spectrometry (SILAC) and RNA interference (RNAi). This method detects interactions among endogenous non-tagged proteins. Thus, it has the same high confidence as co-immunoprecipitation. However, this method also depends on the availability of suitable antibodies.
Physical/Biophysical and Theoretical methods
· Dual Polarisation Interferometry (DPI) can be used to measure protein-protein interactions. DPI provides real-time, high-resolution measurements of molecular size, density and mass. While tagging is not necessary, one of the protein species must be immobilized on the surface of a waveguide. As well as kinetics and affinity, conformational changes during interaction can also be quantified.
· Static Light scattering (SLS) measures changes in the Rayleigh scattering of protein complexes in solution and can non-destructively characterize both weak and strong interactions without tagging or immobilization of the protein. The measurement consists of mixing a series of aliquots of different concentrations or compositions with the anylate, measuring the effect of the changes in light scattering as a result of the interaction, and fitting the correlated light scattering changes with concentration to a model. Weak, non-specific interactions are typically characterized via the second virial coefficient. This type of analysis can determine the equilibrium association constant for associated complexes. Additional light scattering methods for protein activity determination were previously developed by Timasheff. More recent Dynamic Light scattering (DLS) methods for proteins were reported by H. Chou that are also applicable at high protein concentrations and in protein gels; DLS may thus also be applicable for in vivo cytoplasmic observations of various protein-protein interactions.
· Surface plasmon resonance can be used to measure protein-protein interaction.
· With Fluorescence correlation spectroscopy, one protein is labeled with a fluorescent dye and the other is left unlabeled. The two proteins are then mixed and the data outputs the fraction of the labeled protein that is unbound and bound to the other protein, allowing you to get a measure of KD and binding affinity. You can also take time-course measurements to characterize binding kinetics. FCS also tells you the size of the formed complexes so you can measure the stoichiometry of binding. A more powerful methods is [[fluorescence cross-correlation spectroscopy (FCCS) that employs double labeling techniques and cross-correlation resulting in vastly improved signal-to-noise ratios over FCS. Furthermore, the two-photon and three-photon excitation practically eliminates photobleaching effects and provide ultra-fast recording of FCCS or FCS data.
· Fluorescence resonance energy transfer (FRET) is a common technique when observing the interactions of only two different proteins. · Protein activity determination by NMR multi-nuclear relaxation measurements, or 2D-FT NMR spectroscopy in solutions, combined with nonlinear regression analysis of NMR relaxation or 2D-FT spectroscopy data sets. Whereas the concept of water activity is widely known and utilized in the applied biosciences, its complement--the protein activity which quantitates protein-protein interactions-- is much less familiar to bioscientists as it is more difficult to determine in dilute solutions of proteins; protein activity is also much harder to determine for concentrated protein solutions when protein aggregation, not merely transient protein association, is often the dominant process. · Theoretical modeling of protein-protein interactions involves a detailed physical chemistry/thermodynamic understanding of several effects involved, such as intermolecular forces, ion-binding, proton fluctuations and proton exchange. The theory of thermodynamically linked functions is one such example in which ion-binding and protein-protein interactions are treated as linked processes; this treatment is especially important for proteins that have enzymatic activity which depends on cofactor ions dynamically bound at the enzyme active site, as for example, in the case of oxygen-evolving enzyme system (OES) in photosynthetic biosystems where the oxygen molecule binding is linked to the chloride anion binding as well as the linked state transition of the manganese ions present at the active site in Photosystem II(PSII). Another example of thermodynamically linked functions of ions and protein activity is that of divalent calcium and magnesium cations to myosin in mechanical energy transduction in muscle. Last-but-not least, chloride ion and oxygen binding to hemoglobin (from several mammalian sources, including human) is a very well-known example of such thermodynamically linked functions for which a detailed and precise theory has been already developed. ·Molecular dynamics (MD) computations of protein-protein interactions. · Protein-protein docking, the prediction of protein-protein interactions based only on the three-dimensional protein structures from X-ray diffraction of protein crystals might not be satisfactory. Transcriptional interactions Transcriptional interactions occur between transcription factors (TFs) and their DNA binding sites (TFBSs). These interactions control many important processes, such as critical steps in development and responses to environmental stresses, and their defects can result in various diseases. Much progress has been made recently in the accumulation and analysis of mRNA transcript profiles of a variety of cell and tissue types, including those associated with various human diseases. Much remains to be understood, however, about the transcriptional regulatory networks that govern these expression dynamics. A more complete understanding of TFs, TFBSs, and their interactions, will permit a more comprehensive and quantitative mapping of the regulatory pathways within cells, as well as a deeper understanding of the potential functions of individual genes regulated by newly identified DNA-binding sites. Traditional methodology is based on pattern discovery: - Consensus http://ural.wustl.edu/consensus/ determines consensus patterns in unaligned sequences - MEME http://meme.sdsc.edu/meme4_1/intro.html The MEME system allows you to 1. discover motifs (highly conserved regions) in groups of related DNA or protein sequences using MEME and, 2. search sequence databases using motifs using MAST (Motif Alignment and Search Tool). - Motifsampler http://homes.esat.kuleuven.be/~thijs/Work/MotifSampler.html finds over-represented motifs in the upstream region of a set of co-regulated genes. Or Known sequences detection: - Patch (Biobase) http://www.gene-regulation.com/cgi-bin/pub/programs/patch/bin/patch.cgi? TF binding sites of the TRANSFAC Professional database and the consensus sequences of weight matrices of TRANSFAC Professional. - Motifscanner http://homes.esat.kuleuven.be/~thijs/Work/MotifScanner.html to screen DNA sequences with precompiled motif models - Motif Locator http://homes.esat.kuleuven.be/~thijs/help/help_motiflocator.html The MotifLocator is an algorithm to find pre-defined motifs in DNA sequences using a adapted position-weight matrix scoring scheme Currently, a model that could serve this purpose is the solenoidal model of chromosomes, based on transcriptomic regularities observed in bacteria and in yeast [Képès, 2003; 2004; Képès & Vaillant, 2003]. In brief, gene targets of the same TF – co-regulated genes – tend to be periodically positioned along the genome. The observed period is the same for different TFs. However, the period differs among the yeast chromosome arms, or among various bacterial strains. This remarkable regularity is consistent with a solenoidal folding of chromosomes, where one observed period along the 1-D chromosome corresponds to one DNA loop of the 3-D solenoid. The mechanistic justification for this interpretation exists, as we know that the resulting spatial clustering of co-regulated genes optimizes their transcription with strong effects in the 70-fold range [e.g. Dröge & Müller-Hill, 2001].
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