A rapid, efficient, and low-cost BiFC protocol and its application in studying in vivo interaction of seed-specific transcription factors, RISBZ and RPBF.

Proteins regulate cellular and biological processes in all living organisms. More than 80% of the proteins interact with one another to perform their respective functions; therefore, studying the protein-protein-interaction has gained attention in functional characterization studies. Bimolecular fluorescence complement (BiFC) assay is widely adopted to determine the physical interaction of two proteins in vivo. Here, we developed a simple, yet effective BiFC assay for protein-protein-interaction using transient Agrobacterium-mediated-transformation of onion epidermal cells by taking case study of Rice-P-box-Binding-Factor (RPBF) and rice-seed-specific-bZIP (RISBZ) in vivo interaction. Our result revealed that both the proteins, i.e., RISBZ and RPBF, interacted in the nucleus and cytosol. These two transcription factors are known for their coordinate/synergistic regulation of seed-protein content via concurrent binding to the promoter region of the seed storage protein (SSP) encoding genes. We further validated our results with BiFC assay in Nicotiana by agroinfiltration method, which exhibited similar results as Agrobacterium-mediated-transformation of onion epidermal cells. We also examined the subcellular localization of RISBZ and RPBF to assess the efficacy of the protocol. The subcellular localization and BiFC assay presented here is quite easy-to-follow, reliable, and reproducible, which can be completed within 2-3 days without using costly instruments and technologies that demand a high skill set.

High-throughput methods for identification of protein-protein interactions involving short linear motifs.

Interactions between modular domains and short linear motifs (3-10 amino acids peptide stretches) are crucial for cell signaling. The motifs typically reside in the disordered regions of the proteome and the interactions are often transient, allowing for rapid changes in response to changing stimuli. The properties that make domain-motif interactions suitable for cell signaling also make them difficult to capture experimentally and they are therefore largely underrepresented in the known protein-protein interaction networks. Most of the knowledge on domain-motif interactions is derived from low-throughput studies, although there exist dedicated high-throughput methods for the identification of domain-motif interactions. The methods include arrays of peptides or proteins, display of peptides on phage or yeast, and yeast-two-hybrid experiments. We here provide a survey of scalable methods for domain-motif interaction profiling. These methods have frequently been applied to a limited number of ubiquitous domain families. It is now time to apply them to a broader set of peptide binding proteins, to provide a comprehensive picture of the linear motifs in the human proteome and to link them to their potential binding partners. Despite the plethora of methods, it is still a challenge for most approaches to identify interactions that rely on post-translational modification or context dependent or conditional interactions, suggesting directions for further method development.

Plasmonic nanosensors for simultaneous quantification of multiple protein-protein binding affinities.

Most of current techniques used for the quantification of protein-protein interactions require the analysis of one pair of binding partners at a time. Herein we present a label-free, simple, fast, and cost-effective route to characterize binding affinities between multiple macromolecular partners simultaneously, using optical dark-field spectroscopy and individual protein-functionalized gold nanorods as sensing elements. Our NanoSPR method could easily become a simple and standard tool in biological, biochemical, and medical laboratories.

Cost-effective strategies for completing the interactome.

Comprehensive protein-interaction mapping projects are underway for many model species and humans. A key step in these projects is estimating the time, cost and personnel required for obtaining an accurate and complete map. Here we modeled the cost of interaction-map completion for various experimental designs. We showed that current efforts may require up to 20 independent tests covering each protein pair to approach completion. We explored designs for reducing this cost substantially, including prioritization of protein pairs, probability thresholding and interaction prediction. The best experimental designs lowered cost by fourfold overall and >100-fold in early stages of mapping. We demonstrate the best strategy in an ongoing project in Drosophila melanogaster, in which we mapped 450 high-confidence interactions using 47 microtiter plates, versus thousands of plates expected using current designs. This study provides a framework for assessing the feasibility of interaction mapping projects and for future efforts to increase their efficiency.

A benchmarked protein microarray-based platform for the identification of novel low-affinity extracellular protein interactions.

Low-affinity extracellular protein interactions are critical for cellular recognition processes, but existing methods to detect them are limited in scale, making genome-wide interaction screens technically challenging. To address this, we report here the miniaturization of the AVEXIS (avidity-based extracellular interaction screen) assay by using protein microarray technology. To achieve this, we have developed protein tags and sample preparation methods that enable the parallel purification of hundreds of recombinant proteins expressed in mammalian cells. We benchmarked the protein microarray-based assay against a set of known quantified receptor-ligand pairs and show that it is sensitive enough to detect even very weak interactions that are typical of this class of interactions. The increase in scale enables interaction screening against a dilution series of immobilized proteins on the microarray enabling the observation of saturation binding behaviors to show interaction specificity and also the estimation of interaction affinities directly from the primary screen. These methodological improvements now permit screening for novel extracellular receptor-ligand interactions on a genome-wide scale.

Novel peptide-protein assay for identification of antimicrobial peptides by fluorescence quenching.

The specific interaction of peptides with proteins is often a key factor which determines biological activities. The determination of K(d) values of such interactions is commonly performed with fluorescence polarization. However, fluorescence polarization assays are prone to false-positive results due to the potential for non-specific interactions and only afford very low signal-to-background ratios. Here, we present as an alternative a fluorescence resonance energy transfer based quenching assay to measure peptide-protein interactions in solution. In a test setup where antimicrobial peptides were tested for their affinity towards the protein DnaK, the assay provided high specificity and good reproducibility and correlated with the results obtained by fluorescence polarization methods. Furthermore, we established a fast prescreening method which will allow a highly efficient screening of peptide libraries by reducing the amount of sample by 98% compared to conventional fluorescence polarization assays.

Calculations of the binding affinities of protein-protein complexes with the fast multipole method.

In this paper, we used a coarse-grained model at the residue level to calculate the binding free energies of three protein-protein complexes. General formulations to calculate the electrostatic binding free energy and the van der Waals free energy are presented by solving linearized Poisson-Boltzmann equations using the boundary element method in combination with the fast multipole method. The residue level model with the fast multipole method allows us to efficiently investigate how the mutations on the active site of the protein-protein interface affect the changes in binding affinities of protein complexes. Good correlations between the calculated results and the experimental ones indicate that our model can capture the dominant contributions to the protein-protein interactions. At the same time, additional effects on protein binding due to atomic details are also discussed in the context of the limitations of such a coarse-grained model.

LuMPIS--a modified luminescence-based mammalian interactome mapping pull-down assay for the investigation of protein-protein interactions encoded by GC-low ORFs.

The GC content is highly variable among the genomes of different organisms. It has been shown that recombinant gene expression in mammalian cells is much more efficient when GC-rich coding sequences of a certain protein are used. In order to study protein-protein interactions in Varicella zoster virus, a GC-low herpesvirus, we have developed a novel luminescence-based maltose-binding protein pull-down interaction screening system (LuMPIS) that is able to overcome the impaired protein expression levels of GC-low ORFs in mammalian expression systems.

A bead aggregation assay for detection of low-affinity protein-protein interactions reveals interactions between N-terminal domains of inositol 1,4,5-trisphosphate receptors.

Interactions between proteins are a hallmark of all cellular activities. Such interactions often occur with low affinity, a feature that allows them to be rapidly reversible, but it makes them difficult to detect using conventional methods such as yeast 2-hybrid analyses, co-immunoprecipitation or analytical ultracentrifugation. We developed a simple and economical bead aggregation assay to study low-affinity interactions between proteins. By coating beads with interacting proteins, the weak interactions between many proteins are sufficient to allow stable aggregation of beads, an avidity effect. The aggregation is easily measured to allow quantification of protein-protein interactions under a variety of controlled conditions. We use this assay to demonstrate low-affinity interactions between the N-terminal domains of an intracellular Ca(2+) channel, the type 1 inositol 1,4,5-trisphosphate receptor. This simple bead aggregation assay may have widespread application in the study of low-affinity interactions between macromolecules.

FRETex: a FRET-based, high-throughput technique to analyze protein-protein interactions.

Protein-protein interactions (PPIs) are essential for cellular viability and activity. Here, we present a rapid, semi-quantitative method (termed FRETex) to analyze PPIs, taking advantage of the strong and specific FRET signal between fused CyPET donor and YPET acceptor molecules. To demonstrate the robustness of this approach, we analyzed the interactions between three protein pairs and their muteins: TEM1-ß-lactamase binding its inhibitor BLIP, barnase binding barstar and ornithine decarboxylase binding its inhibitor antizyme. The CyPET/YPET fused proteins were produced in small quantities, and the measurements were conducted directly in the proteins crude Escherichia coli lysates without any purification step. Protein concentrations were determined from the fluorescence intensities of the lysates. While binding titration curves were produced, the resulting affinities were not always precise. Therefore, we also conducted time-resolved chase experiments using non-labeled binding partners as chasers. The acquired dissociation rate constants were in a good agreement with those measured by surface plasmon resonance. Due to the simplicity of FRETex, and the ability to obtain semi-quantitative binding data, FRETex is a suitable method for tasks such as mutant scans, protein-engineering, scanning for inhibitors and more.

Fast and accurate alignment of multiple protein networks.

Comparative analysis of protein networks has proven to be a powerful approach for elucidating network structure and predicting protein function and interaction. A fundamental challenge for the successful application of this approach is to devise an efficient multiple network alignment algorithm. Here we present a novel framework for the problem. At the heart of the framework is a novel representation of multiple networks that is only linear in their size as opposed to current exponential representations. Our alignment algorithm is very efficient, being capable of aligning 10 networks with tens of thousands of proteins each in minutes. We show that our algorithm outperforms previous approaches for the problem, and produces results that are more in line with current biological knowledge.