Purification of MAP–kinase protein complexes and identification of candidate components by XL–TAP–MS

The purification of low-abundance protein complexes and detection of in vivo protein–protein interactions in complex biological samples remains a challenging task. Here, we devised crosslinking and tandem affinity purification coupled to mass spectrometry (XL–TAP–MS), a quantitative proteomics approach for analyzing tandem affinity-purified, crosslinked protein complexes from plant tissues. We exemplarily applied XL–TAP–MS to study the MKK2–Mitogen-activated protein kinase (MPK4) signaling module in Arabidopsis thaliana. A tandem affinity tag consisting of an in vivo-biotinylated protein domain flanked by two hexahistidine sequences was adopted to allow for the affinity-based isolation of formaldehyde–crosslinked protein complexes under fully denaturing conditions. Combined with ¹⁵N stable isotopic labeling and tandem MS we captured and identified a total of 107 MKK2–MPK4 module-interacting proteins. Consistent with the role of the MPK signaling module in plant immunity, many of the module-interacting proteins are involved in the biotic and abiotic stress response of Arabidopsis. Validation of binary protein–protein interactions by in planta split-luciferase assays and in vitro kinase assays disclosed several direct phosphorylation targets of MPK4. Together, the XL–TAP–MS approach purifies low abundance protein complexes from biological samples and discovers previously unknown protein–protein interactions.

XL–TAP–MS: a novel technique that allows purification of crosslinked, low abundant protein complexes from plant tissues under denatured conditions and detection of in vivo protein–protein interactions.     

基于TurboID的植物蛋白邻近标记实验方法

邻近标记作为近些年发展起来的一项检测活细胞内蛋白互作关系和亚细胞结构蛋白组的新型技术,已成功应用于多种动植物体系的研究。该技术通过给诱饵蛋白融合一个具有特定催化连接活性的酶,在酶的催化作用下将小分子底物(如生物素)共价连接到酶邻近的内源蛋白,通过富集和分析被标记的蛋白可获得与诱饵互作的蛋白组。经定向进化产生的生物素连接...     

Direct measurement of protein–protein interactions by FLIM-FRET at UV laser-induced DNA damage sites in living cells

Protein–protein interactions are essential to ensure timely and precise recruitment of chromatin remodellers and repair factors to DNA damage sites. Conventional analyses of protein–protein interactions at a population level may mask the complexity of interaction dynamics, highlighting the need for a method that enables quantification of DNA damage-dependent interactions at a single-cell level. To this end, we integrated a pulsed UV laser on a confocal fluorescence lifetime imaging (FLIM) microscope to induce localized DNA damage. To quantify protein–protein interactions in live cells, we measured Förster resonance energy transfer (FRET) between mEGFP- and mCherry-tagged proteins, based on the fluorescence lifetime reduction of the mEGFP donor protein. The UV-FLIM-FRET system offers a unique combination of real-time and single-cell quantification of DNA damage-dependent interactions, and can distinguish between direct protein–protein interactions, as opposed to those mediated by chromatin proximity. Using the UV-FLIM-FRET system, we show the dynamic changes in the interaction between poly(ADP-ribose) polymerase 1, amplified in liver cancer 1, X-ray repair cross-complementing protein 1 and tripartite motif containing 33 after DNA damage. This new set-up complements the toolset for studying DNA damage response by providing single-cell quantitative and dynamic information about protein–protein interactions at DNA damage sites.     

Localizing protein-protein interactions by bimolecular fluorescence complementation in planta

The application of novel assays for basic cell research is tightly linked to the development of easy-to-use and versatile tools and protocols for implementing such technologies for a wide range of applications and model species. The bimolecular fluorescence complementation (BiFC) assay is one such novel method for which tools and protocols for its application in plant cell research are still being developed. BiFC is a powerful tool which enables not only detection, but also visualization and subcellular localization of protein–protein interactions in living cells. Here we describe the application of BiFC in plant cells while focusing on the use of our versatile set of vectors which were specifically designed to facilitate the transformation, expression and imaging of protein–protein interactions in various plant species. We discuss the considerations of using our system in various plant model systems, the use of single versus multiple expression cassettes, the application of our vectors using various transformation methods and the use of internal fluorescent markers which can assist in signal localization and easy data acquisition in living cells.     

Mass spectrometry‐based protein–protein interaction networks for the study of human diseases

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein–protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)‐based approaches have allowed unbiased mapping of these disease‐mediated changes in protein–protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein–protein interactions at a system‐level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS‐based protein–protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.     

Protein–protein interaction analysis by C-terminally specific fluorescence labeling and fluorescence cross-correlation spectroscopy

Here, we describe novel puromycin derivatives conjugated with iminobiotin and a fluorescent dye that can be linked covalently to the C-terminus of full-length proteins during cell-free translation. The iminobiotin-labeled proteins can be highly purified by affinity purification with streptavidin beads. We confirmed that the purified fluorescence-labeled proteins are useful for quantitative protein–protein interaction analysis based on fluorescence cross-correlation spectroscopy (FCCS). The apparent dissociation constants of model protein pairs such as proto-oncogenes c-Fos/c-Jun and archetypes of the family of Ca²⁺-modulated calmodulin/related binding proteins were in accordance with the reported values. Further, detailed analysis of the interactions of the components of polycomb group complex, Bmi1, M33, Ring1A and RYBP, was successfully conducted by means of interaction assay for all combinatorial pairs. The results indicate that FCCS analysis with puromycin-based labeling and purification of proteins is effective and convenient for in vitro protein–protein interaction assay, and the method should contribute to a better understanding of protein functions by using the resource of available nucleotide sequences.     

When peptides fly: Advances in Drosophila proteomics

In the past decade, improvements in genome annotation, protein fractionation methods and mass spectrometry instrumentation resulted in rapid growth of Drosophila proteomics. This review presents the current status of proteomics research in the fly. Areas that have seen major advances in recent years include efforts to map and catalog the Drosophila proteome and high-throughput as well as targeted studies to analyze protein–protein interactions and post-translational modifications. Stable isotope labeling of flies and other applications of quantitative proteomics have opened up new possibilities for functional analyses. It is clear that proteomics is becoming an indispensable tool in Drosophila systems biology research that adds a unique dimension to studying gene function.     

A real-time assay for monitoring nucleic acid cleavage by quadruplex formation

Direct and straightforward methods to follow nucleic acid cleavage are needed. A spectrophotometric quadruplex formation assay (QFA) was developed, which allows real-time monitoring of site-specific cleavage of nucleic acids. QFA was applied to study both protein and nucleic acid restriction enzymes, and was demonstrated to accurately determine Michaelis–Menten parameters for the cleavage reaction catalyzed by EcoRI. QFA can be used to study the mechanisms of protein–nucleic acid recognition. QFA is also a useful tool for dissecting individual nicking rates of a double-stranded cleavage.     

Mutual interactions between subunits of the human RNase MRP ribonucleoprotein complex

The eukaryotic ribonuclease for mitochondrial RNA processing (RNase MRP) is mainly located in the nucleoli and belongs to the small nucleolar ribonucleoprotein (snoRNP) particles. RNase MRP is involved in the processing of pre-rRNA and the generation of RNA primers for mitochondrial DNA replication. A closely related snoRNP, which shares protein subunits with RNase MRP and contains a structurally related RNA subunit, is the pre-tRNA processing factor RNase P. Up to now, 10 protein subunits of these complexes have been described, designated hPop1, hPop4, hPop5, Rpp14, Rpp20, Rpp21, Rpp25, Rpp30, Rpp38 and Rpp40. To get more insight into the assembly of the human RNase MRP complex we studied protein–protein and protein–RNA interactions by means of GST pull-down experiments. A total of 19 direct protein–protein and six direct protein–RNA interactions were observed. The analysis of mutant RNase MRP RNAs showed that distinct regions are involved in the direct interaction with protein subunits. The results provide insight into the way the protein and RNA subunits assemble into a ribonucleoprotein particle. Based upon these data a new model for the architecture of the human RNase MRP complex was generated.     

In vitro selection of Jun-associated proteins using mRNA display

Although yeast two-hybrid assay and biochemical methods combined with mass spectrometry have been successfully employed for the analyses of protein–protein interactions in the field of proteomics, these methods encounter various difficulties arising from the usage of living cells, including inability to analyze toxic proteins and restriction of testable interaction conditions. Totally in vitro display technologies such as ribosome display and mRNA display are expected to circumvent these difficulties. In this study, we applied an mRNA display technique to screening for interactions of a basic leucine zipper domain of Jun protein in a mouse brain cDNA library. By performing iterative affinity selection and sequence analyses, we selected 16 novel Jun-associated protein candidates in addition to four known interactors. By means of real-time PCR and pull-down assay, 10 of the 16 newly discovered candidates were confirmed to be direct interactors with Jun in vitro. Furthermore, interaction of 6 of the 10 proteins with Jun was observed in cultured cells by means of co-immunoprecipitation and observation of subcellular localization. These results demonstrate that this in vitro display technology is effective for the discovery of novel protein–protein interactions and can contribute to the comprehensive mapping of protein–protein interactions.     

Discarding functional residues from the substitution table improves predictions of active sites within three-dimensional structures

Substitutions of individual amino acids in proteins may be under very different evolutionary restraints depending on their structural and functional roles. The Environment Specific Substitution Table (ESST) describes the pattern of substitutions in terms of amino acid location within elements of secondary structure, solvent accessibility, and the existence of hydrogen bonds between side chains and neighbouring amino acid residues. Clearly amino acids that have very different local environments in their functional state compared to those in the protein analysed will give rise to inconsistencies in the calculation of amino acid substitution tables. Here, we describe how the calculation of ESSTs can be improved by discarding the functional residues from the calculation of substitution tables. Four categories of functions are examined in this study: protein–protein interactions, protein–nucleic acid interactions, protein–ligand interactions, and catalytic activity of enzymes. Their contributions to residue conservation are measured and investigated. We test our new ESSTs using the program CRESCENDO, designed to predict functional residues by exploiting knowledge of amino acid substitutions, and compare the benchmark results with proteins whose functions have been defined experimentally. The new methodology increases the Z-score by 98% at the active site residues and finds 16% more active sites compared with the old ESST. We also find that discarding amino acids responsible for protein–protein interactions helps in the prediction of those residues although they are not as conserved as the residues of active sites. Our methodology can make the substitution tables better reflect and describe the substitution patterns of amino acids that are under structural restraints only.     

Common patterns in type II restriction enzyme binding sites

Restriction enzymes are among the best studied examples of DNA binding proteins. In order to find general patterns in DNA recognition sites, which may reflect important properties of protein–DNA interaction, we analyse the binding sites of all known type II restriction endonucleases. We find a significantly enhanced GC content and discuss three explanations for this phenomenon. Moreover, we study patterns of nucleotide order in recognition sites. Our analysis reveals a striking accumulation of adjacent purines (R) or pyrimidines (Y). We discuss three possible reasons: RR/YY dinucleotides are characterized by (i) stronger H-bond donor and acceptor clusters, (ii) specific geometrical properties and (iii) a low stacking energy. These features make RR/YY steps particularly accessible for specific protein–DNA interactions. Finally, we show that the recognition sites of type II restriction enzymes are underrepresented in host genomes and in phage genomes.     

Protein–protein interaction prediction methods: from docking-based to AI-based approaches

Protein–protein interactions (PPIs), such as protein–protein inhibitor, antibody–antigen complex, and supercomplexes play diverse and important roles in cells. Recent advances in structural analysis methods, including cryo-EM, for the determination of protein complex structures are remarkable. Nevertheless, much room remains for improvement and utilization of computational methods to predict PPIs because of the large number and great diversity of unresolved complex structures. This review introduces a wide array of computational methods, including our own, for estimating PPIs including antibody–antigen interactions, offering both historical and forward-looking perspectives.     

Root–root interactions: extending our perspective to be more inclusive of the range of theories in ecology and agriculture using in-vivo analyses

Background

There is a large body of literature on competitive interactions among plants, but many studies have only focused on above-ground interactions and little is known about root–root dynamics between interacting plants. The perspective on possible mechanisms that explain the outcome of root–root interactions has recently been extended to include non-resource-driven mechanisms (as well as resource-driven mechanisms) of root competition and positive interactions such as facilitation. These approaches have often suffered from being static, partly due to the lack of appropriate methodologies for in-situ non-destructive root characterization.

Scope

Recent studies show that interactive effects of plant neighbourhood interactions follow non-linear and non-additive paths that are hard to explain. Common outcomes such as accumulation of roots mainly in the topsoil cannot be explained solely by competition theory but require a more inclusive theoretical, as well as an improved methodological framework. This will include the question of whether we can apply the same conceptual framework to crop versus natural species.

Conclusions

The development of non-invasive methods to dynamically study root–root interactions in vivo will provide the necessary tools to study a more inclusive conceptual framework for root–root interactions. By following the dynamics of root–root interactions through time in a whole range of scenarios and systems, using a wide variety of non-invasive methods, (such as fluorescent protein which now allows us to separately identify the roots of several individuals within soil), we will be much better equipped to answer some of the key questions in root physiology, ecology and agronomy.