From protein-protein complexes to interactomics

Interactomics in plant defence: progress and opportunities

Interactomics is a branch of systems biology that deals with the study of protein-protein interactions and how these interactions influence phenotypes. Identifying the interactomes involved during host-pathogen interaction events may bring us a step closer to deciphering the molecular mechanisms underlying plant defence. Here, we conducted a systematic review of plant interactomics studies over the last two decades and found that while a substantial progress has been made in the field, plant-pathogen interactomics remains a less-travelled route. As an effort to facilitate the progress in this field, we provide here a comprehensive research pipeline for an in planta plant-pathogen interactomics study that encompasses the in silico prediction step to the validation step, unconfined to model plants. We also highlight four challenges in plant-pathogen interactomics with plausible solution(s) for each.

Designer nanoparticle: nanobiotechnology tool for cell biology

This article discusses the use of nanotechnology for subcellular compartment isolation and its application towards subcellular omics. This technology review significantly contributes to our understanding on use of nanotechnology for subcellular systems biology. Here we elaborate nanobiotechnology approach of using superparamagnetic nanoparticles (SPMNPs) optimized with different surface coatings for subcellular organelle isolation. Using pulse-chase approach, we review that SPMNPs interacted differently with the cell depending on its surface functionalization. The article focuses on the use of functionalized-SPMNPs as a nanobiotechnology tool to isolate high quality (both purity and yield) plasma membranes and endosomes or lysosomes. Such nanobiotechnology tool can be applied in generating subcellular compartment inventories. As a future perspective, this strategy could be applied in areas such as immunology, cancer and stem cell research.

Mildew-Omics: How Global Analyses Aid the Understanding of Life and Evolution of Powdery Mildews

The common powdery mildew plant diseases are caused by ascomycete fungi of the order Erysiphales. Their characteristic life style as obligate biotrophs renders functional analyses in these species challenging, mainly because of experimental constraints to genetic manipulation. Global large-scale ("-omics") approaches are thus particularly valuable and insightful for the characterisation of the life and evolution of powdery mildews. Here we review the knowledge obtained so far from genomic, transcriptomic and proteomic studies in these fungi. We consider current limitations and challenges regarding these surveys and provide an outlook on desired future investigations on the basis of the various -omics technologies.

Flow cytometric analysis of bimolecular fluorescence complementation: a high throughput quantitative method to study protein-protein interaction

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction.

Solvated protein-DNA docking using HADDOCK

Interfacial water molecules play an important role in many aspects of protein-DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the docking of protein-DNA complexes and demonstrate its feasibility on a benchmark of 30 high-resolution protein-DNA complexes containing crystallographically-determined water molecules at their interfaces. Our protocol is capable of reproducing the solvation pattern at the interface and recovers hydrogen-bonded water-mediated contacts in many of the benchmark cases. Solvated docking leads to an overall improvement in the quality of the generated protein-DNA models for cases with limited conformational change of the partners upon complex formation. The applicability of this approach is demonstrated on real cases by docking a representative set of 6 complexes using unbound protein coordinates, model-built DNA and knowledge-based restraints. As HADDOCK supports the inclusion of a variety of NMR restraints, solvated docking is also applicable for NMR-based structure calculations of protein-DNA complexes.

Protein docking prediction using predicted protein-protein interface

Background

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations.

Results

We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering.

Conclusion

We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Functional proteomics: application of mass spectrometry to the study of enzymology in complex mixtures

This review covers recent developments in mass spectrometry-based applications dealing with functional proteomics with special emphasis on enzymology. The introduction of mass spectrometry into this research field has led to an enormous increase in knowledge in recent years. A major challenge is the identification of "biologically active substances" in complex mixtures. These biologically active substances are, on the one hand, potential regulators of enzymes. Elucidation of function and identity of those regulators may be accomplished by different strategies, which are discussed in this review. The most promising approach thereby seems to be the one-step procedure, because it enables identification of the functionality and identity of biologically active substances in parallel and thus avoids misinterpretation. On the other hand, besides the detection of regulators, the identification of endogenous substrates for known enzymes is an emerging research field, but in this case studies are quite rare. Moreover, the term biologically active substances may also encompass proteins with diverse biological functions. Elucidation of the functionality of those-so far unknown-proteins in complex mixtures is another branch of functional proteomics and those investigations will also be discussed in this review.

Interactions of hemoglobin in live red blood cells measured by the electrophoresis release test

To elucidate the protein-protein interactions of hemoglobin (Hb) variants A and A(2), HbA was first shown to bind with HbA(2) in live red blood cells (RBCs) by diagonal electrophoresis and then the interaction between HbA and HbA(2) outside the RBC was shown by cross electrophoresis. The starch-agarose gel electrophoresis of hemolysate, RBCs, freeze-thawed RBCs and the supernatant of freeze-thawed RBCs showed that the interaction between HbA and HbA(2) was affected by membrane integrity. To identify the proteins involved in the interaction, protein components located between HbA and HbA(2) in RBCs (RBC HbA-HbA(2)) and hemolysate (hemolysate HbA-HbA(2)) were isolated from the starch-agarose gel and separated by 5-12% SDS-PAGE. The results showed that there was a ≈22 kDa protein band located in the RBC HbA-HbA(2) but not in hemolysate HbA-HbA(2). Sequencing by LC/MS/MS showed that this band was a protein complex that included mainly thioredoxin peroxidase B, α-globin, δ-globin and β-globin. Thus, using our unique in vivo whole blood cell electrophoresis release test, Hbs were proven for the first time to interact with other proteins in the live RBC.

Proteomic screen for multiprotein complexes in synaptic plasma membrane from rat hippocampus by blue native gel electrophoresis and tandem mass spectrometry

Neuronal synapses are specialized sites for information exchange between neurons. Many diseases, such as addiction and mood disorders, likely result from altered expression of synaptic proteins, or altered formation of synaptic complexes involved in neurotransmission or neuroplasticity. A detailed description of native multiprotein complexes in synaptic plasma membranes (PM) is therefore essential for understanding biological mechanisms and disease processes. For the first time in this study, two-dimensional Blue Native/SDS-PAGE electrophoresis, combined with tandem mass spectrometry, was used to screen multiprotein complexes in synaptic plasma membranes from rat hippocampus. As a result, 514 unique proteins were identified, of which 36% were integral membrane proteins. In addition, 19 potentially novel and known heterooligomeric multiprotein complexes were found, such as the SNARE and ATPase complexes. A potentially novel protein complex, involving syntaxin, synapsin I and Na+/K+ ATPase alpha-1, was further confirmed by co-immunoprecipitation and immunofluorescence staining. As demonstrated here, Blue Native-PAGE is a powerful tool for the separation of hydrophobic membrane proteins. The combination of Blue Native-PAGE and mass spectrometry could systematically identify multiprotein complexes.

Apoptosis-inducing proteins in chicken anemia virus and TT virus

Torque teno viruses (TTVs) share several genomic similarities with the chicken anemia virus (CAV). CAV encodes the protein apoptin that specifically induces apoptosis in (human) tumor cells. Functional studies reveal that apoptin induces apoptosis in a very broad range of (human) tumor cells. A putative TTV open reading frame (ORF) in TTV genotype 1, named TTV apoptosis inducing protein (TAIP), it induces, like apoptin, p53-independent apoptosis in various human hepatocarcinoma cell lines to a similar level as apoptin. In comparison to apoptin, TAIP action is less pronounced in several analyzed human non-hepatocarcinoma-derived cell lines. Detailed sequence analysis has revealed that the TAIP ORF is conserved within a limited group of the heterogeneous TTV population. However, its N-terminal half, N-TAIP, is rather well conserved in a much broader set of TTV isolates. The similarities between apoptin and TAIP, and their relevance for the development and treatment of diseases is discussed.

Bacterial genome sequencing

For over 30 yr, the Sanger method has been the standard for DNA sequencing. Instruments have been developed and improved over time to increase throughput, but they always relied on the same technology. Today, we are facing a revolution in DNA sequencing with many drastically different platforms that have become or will soon become available on the market. We review a number of sequencing technologies and provide examples of applications. We also discuss the impact genomics and new DNA sequencing approaches have had on various fields of biological research.

Affinity as a tool in life science

The use of affinity-based tools has become invaluable as a platform for basic research and in the development of drugs and diagnostics. Applications include affinity chromatography and affinity tag fusions for efficient purification of proteins as well as methods to probe the protein network interactions on a whole-proteome level. A variety of selection systems has been described for in vitro evolution of affinity reagents using combinatorial libraries, which make it possible to create high-affinity reagents to virtually all biomolecules, as exemplified by generation of therapeutic antibodies and new protein scaffold binders. The strategies for high-throughput generation of affinity reagents have also opened up the possibility of generating specific protein probes on a whole-proteome level. Recently, such affinity proteomics have allowed the detailed analysis of human protein expression in a comprehensive manner both in normal and disease tissue using tissue microarrays and confocal microscopy.