Mapping structural interactions using in-cell NMR spectroscopy (STINT-NMR)

We describe a high-throughput in-cell nuclear magnetic resonance (NMR)-based method for mapping the structural changes that accompany protein-protein interactions (STINT-NMR). The method entails sequentially expressing two (or more) proteins within a single bacterial cell in a time-controlled manner and monitoring the protein interactions using in-cell NMR spectroscopy. The resulting spectra provide a complete titration of the interaction and define structural details of the interacting surfaces at atomic resolution.     

In-cell NMR spectroscopy

Structural studies by in-cell nuclear magnetic resonance are a developing new field of research, and their objective is to obtain structural information of proteins and other biological macromolecules in the cytoplasm of Escherichia coli cells. The major limitation of in-cell experiments is cell lysis that occurs during the experiments. In this article, we describe how inhibition of autologous expression by rifampicin at a high concentration decreases cell lysis in E. coli. We suggest that rifampicin is acting in the programmed cell death gene system MazEF, which is triggered by stress conditions and ultimately leads to cell lysis.     

In-cell NMR spectroscopy.

The recent development of "in-cell NMR" techniques by two independent groups has demonstrated that NMR spectroscopy can be used to characterize the conformation and dynamics of biological macromolecules inside living cells. In this article, we describe different methods and discuss current and future applications as well as critical parameters of this new technique. We show experimental results, compare them with traditional in vitro experiments, and demonstrate that differences between the in vitro and the in vivo state of a macromolecule exist and can be detected and characterized.     

Weak protein-protein interactions as probed by NMR spectroscopy

Weak protein-protein interactions (PPIs) are fundamental to many cellular processes, such as reversible cell-cell contact, rapid enzyme turnover and transient assembly and/or reassembly of large signaling complexes. However, structural and functional characterizations of weak PPIs have been technically challenging and lagged behind those for strong PPIs. Here, we describe nuclear magnetic resonance (NMR) spectroscopy as a highly effective tool for unraveling the atomic details of weak PPIs. We highlight the recent advances of how NMR can be used to rapidly detect and structurally determine extremely weak PPIs (K(d)>10(-4)M). Coupled with functional approaches, NMR has the potential to look into a wide variety of biologically important weak PPIs at the detailed molecular level, thereby facilitating a thorough view of how proteins function in living cells.     

In-cell biochemistry using NMR spectroscopy

Biochemistry and structural biology are undergoing a dramatic revolution. Until now, mostly in vitro techniques have been used to study subtle and complex biological processes under conditions usually remote from those existing in the cell. We developed a novel in-cell methodology to post-translationally modify interactor proteins and identify the amino acids that comprise the interaction surface of a target protein when bound to the post-translationally modified interactors. Modifying the interactor proteins causes structural changes that manifest themselves on the interacting surface of the target protein and these changes are monitored using in-cell NMR. We show how Ubiquitin interacts with phosphorylated and non-phosphorylated components of the receptor tyrosine kinase (RTK) endocytic sorting machinery: STAM2 (Signal-transducing adaptor molecule), Hrs (Hepatocyte growth factor regulated substrate) and the STAM2-Hrs heterodimer. Ubiquitin binding mediates the processivity of a large network of interactions required for proper functioning of the RTK sorting machinery. The results are consistent with a weakening of the network of interactions when the interactor proteins are phosphorylated. The methodology can be applied to any stable target molecule and may be extended to include other post-translational modifications such as ubiquitination or sumoylation, thus providing a long-awaited leap to high resolution in cell biochemistry.     

Mapping protein-protein interactions in solution by NMR spectroscopy.

NMR is very well suited to the study of especially weak protein-protein interactions, as no crystallization is required. The available NMR methods to this end are reviewed and illustrated with applications from the recent biochemical literature: intermolecular NOEs, cross-saturation, chemical shift perturbation, dynamics and exchange perturbation, paramagnetic methods, and dipolar orientation. Most of these methods are now routinely applied for complexes with total molecular mass of 60 kDa and can likely be applied to systems up to 1000 kDa. A substantial fraction of complexes studied show distinct effects of induced fit affecting structural and dynamical properties beyond the contact interface.     

In-cell protein NMR and protein leakage

In-cell nuclear magnetic resonance spectroscopy is a tool for studying proteins under physiologically relevant conditions. In some instances, however, protein signals from leaked protein are observed in the liquid surrounding the cells. Here, we examine the expression of four proteins in Escherichia coli. We describe the controls that should be used for in-cell NMR experiments and show that leakage is likely when the protein being studied exceeds ～20% of the total cellular protein.     

Facile detection of protein-protein interactions by one-dimensional NMR spectroscopy

Two methods for detecting protein-protein interactions in solution using one-dimensional (1D) NMR spectroscopy are described. Both methods rely on measurement of the intensity of the strongest methyl resonance (SMR), which for most proteins is observed at 0.8-0.9 ppm. The severe resonance overlap in this region facilitates detection of the SMR at low micromolar and even sub-micromolar protein concentrations. A decreased SMR intensity in the 1H NMR spectrum of a protein mixture compared to the added SMR intensities of the isolated proteins reports that the proteins interact (SMR method). Decreased SMR intensities in 1D 13C-edited 1H NMR spectra of 13C-labeled proteins upon addition of unlabeled proteins or macromolecules also demonstrate binding (SMRC method). Analysis of the interaction between XIAP and Smac, two proteins involved in apoptosis, illustrates both methods. A study showing that phospholipids compete with the neuronal core complex for Ca2+-dependent binding to the presynaptic Ca2+-sensor synaptotagmin 1 illustrates the usefulness of the SMRC method in studying multicomponent systems.     

Mining literature for protein-protein interactions

MOTIVATION: A central problem in bioinformatics is how to capture information from the vast current scientific literature in a form suitable for analysis by computer. We address the special case of information on protein-protein interactions, and show that the frequencies of words in Medline abstracts can be used to determine whether or not a given paper discusses protein-protein interactions. For those papers determined to discuss this topic, the relevant information can be captured for the Database of Interacting PROTEINS: Furthermore, suitable gene annotations can also be captured. RESULTS: Our Bayesian approach scores Medline abstracts for probability of discussing the topic of interest according to the frequencies of discriminating words found in the abstract. More than 80 discriminating words (e.g. complex, interaction, two-hybrid) were determined from a training set of 260 Medline abstracts corresponding to previously validated entries in the Database of Interacting Proteins. Using these words and a log likelihood scoring function, approximately 2000 Medline abstracts were identified as describing interactions between yeast proteins. This approach now forms the basis for the rapid expansion of the Database of Interacting Proteins.     

Single bead affinity detection (SINBAD) for the analysis of protein-protein interactions

We present a miniaturized pull-down method for the detection of protein-protein interactions using standard affinity chromatography reagents. Binding events between different proteins, which are color-coded with quantum dots (QDs), are visualized on single affinity chromatography beads by fluorescence microscopy. The use of QDs for single molecule detection allows the simultaneous analysis of multiple protein-protein binding events and reduces the amount of time and material needed to perform a pull-down experiment.     

In-cell NMR spectroscopy of proteins inside Xenopus laevis oocytes

In-cell NMR is an application of solution NMR that enables the investigation of protein conformations inside living cells. We have measured in-cell NMR spectra in oocytes from the African clawed frog Xenopus laevis. ¹⁵N-labeled ubiquitin, its derivatives and calmodulin were injected into Xenopus oocytes and two-dimensional ¹H–¹⁵N correlation spectra of the proteins were obtained. While the spectrum of wild-type ubiquitin in oocytes had rather fewer cross-peaks compared to its in vitro spectrum, ubiquitin derivatives that are presumably unable to bind to ubiquitin-interacting proteins gave a markedly larger number of cross-peaks. This observation suggests that protein–protein interactions between ubiquitin and ubiquitin-interacting proteins may cause NMR signal broadening, and hence spoil the quality of the in-cell HSQC spectra. In addition, we observed the maturation of ubiquitin precursor derivative in living oocytes using the in-cell NMR technique. This process was partly inhibited by pre-addition of ubiquitin aldehyde, a specific inhibitor for ubiquitin C-terminal hydrolase (UCH). Our work demonstrates the potential usefulness of in-cell NMR with Xenopus oocytes for the investigation of protein conformations and functions under intracellular environmental conditions.Electronic Supplementary Material Supplementary material is available to authorized users in the online version of this article at .     

Targeting protein-protein interactions for parasite control

Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs) offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank). EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite) and B. malayi (H. sapiens parasite), which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly applicable.     

Bioluminescence resonance energy transfer (BRET) for the real-time detection of protein-protein interactions

A substantial range of protein-protein interactions can be readily monitored in real time using bioluminescence resonance energy transfer (BRET). The procedure involves heterologous coexpression of fusion proteins, which link proteins of interest to a bioluminescent donor enzyme or acceptor fluorophore. Energy transfer between these proteins is then detected. This protocol encompasses BRET1, BRET2 and the recently described eBRET, including selection of the donor, acceptor and substrate combination, fusion construct generation and validation, cell culture, fluorescence and luminescence detection, BRET detection and data analysis. The protocol is particularly suited to studying protein-protein interactions in live cells (adherent or in suspension), but cell extracts and purified proteins can also be used. Furthermore, although the procedure is illustrated with references to mammalian cell culture conditions, this protocol can be readily used for bacterial or plant studies. Once fusion proteins are generated and validated, the procedure typically takes 48-72 h depending on cell culture requirements.     

A lock-and-key model for protein-protein interactions

MOTIVATION: Protein-protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism's proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs, and also to identify potentially missing or spurious interactions. RESULTS: Our new graph model explains observed interactions between proteins by an underlying interaction of complementary binding domains (lock-and-key model). This leads to a novel graph-theoretical algorithm to identify bipartite subgraphs within protein-protein interaction networks where the underlying data are taken from yeast two-hybrid experimental results. By testing on synthetic data, we demonstrate that under certain modelling assumptions, the algorithm will return correct domain information about each protein in the network. Tests on data from various model organisms show that the local and global patterns predicted by the model are indeed found in experimental data. Using functional and protein structure annotations, we show that bipartite subnetworks can be identified that correspond to biologically relevant interaction motifs. Some of these are novel and we discuss an example involving SH3 domains from the Saccharomyces cerevisiae interactome. AVAILABILITY: The algorithm (in Matlab format) is available (see http://www.maths.strath.ac.uk/~aas96106/lock_key.html).     

Biochemical approaches for discovering protein-protein interactions

Protein–protein interactions or protein complexes are integral in nearly all cellular processes, ranging from metabolism to structure. Elucidating both individual protein associations and complex protein interaction networks, while challenging, is an essential goal of functional genomics. For example, discovering interacting partners for a 'protein of unknown function' can provide insight into actual function far beyond what is possible with sequence-based predictions, and provide a platform for future research. Synthetic genetic approaches such as two-hybrid screening often reveal a perplexing array of potential interacting partners for any given target protein. It is now known, however, that this type of anonymous screening approach can yield high levels of false-positive results, and therefore putative interactors must be confirmed by independent methods. In vitro biochemical strategies for identifying interacting proteins are varied and time-honored, some being as old as the field of protein chemistry itself. Herein we discuss five biochemical approaches for isolating and characterizing protein–protein interactions in vitro : co-immunoprecipitation, blue native gel electrophoresis, in vitro binding assays, protein cross-linking, and rate-zonal centrifugation. A perspective is provided for each method, and where appropriate specific, trial-tested methods are included.     

Polypeptide modulators of caspase recruitment domain (CARD)-CARD-mediated protein-protein interactions

The caspase recruitment domain (CARD) is present in a large number of proteins. Initially, the CARD was recognized as part of the caspase activation machinery. CARD-CARD interactions play a role in apoptosis and are responsible for the Apaf-1-mediated activation of procaspase-9 in the apoptosome. CARD-containing proteins mediate the inflammasome-dependent activation of proinflammatory caspase-1. More recently, new roles for CARD-containing proteins have been reported in signaling pathways associated with immune responses. The functional role of CARD-containing proteins and CARDs in coordinating apoptosis and inflammatory and immune responses is not completely understood. We have explored the putative cross-talk between apoptosis and inflammation by analyzing the modulatory activity on both the Apaf-1/procaspase-9 interaction and the inflammasome-mediated procaspase-1 activation of CARD-derived polypeptides. To this end, we analyzed the activity of individual recombinant CARDs, rationally designed CARD-derived peptides, and peptides derived from phage display.     

Principles of protein-protein interactions

In the postgenomic era, one of the most interesting and important challenges is to understand protein interactions on a large scale. The physical interactions between protein domains are fundamental to the workings of a cell: in multi-domain polypeptide chains, in multi-subunit proteins and in transient complexes between proteins that also exist independently. Thus experimental investigation of protein-protein interactions has been extensive, including recent large-scale screens using mass spectrometry. The role of computational research on protein-protein interactions encompasses not only prediction, but also understanding the nature of the interactions and their three-dimensional structures. I will discuss properties such as sequence conservation and co-regulation of genes and proteins involved in different types of physical interactions. Given that all proteins consist of their evolutionary units, the domains, all interactions occur between these domains. The interactions between domains belonging to different protein families will be the second topic of my talk.