A Computationally Guided Protein-Interaction Screen Uncovers Coiled-Coil Interactions Involved in Vesicular Trafficking

Mapping protein-protein interactions at a domain or motif level can provide structural annotation of the interactome. The α-helical coiled coil is among the most common protein-interaction motifs, and proteins predicted to contain coiled coils participate in diverse biological processes. Here, we introduce a combined computational/experimental screening strategy that we used to uncover coiled-coil interactions among proteins involved in vesicular trafficking in Saccharomyces cerevisiae. A number of coiled-coil complexes have already been identified and reported to play important roles in this important biological process. We identify additional examples of coiled coils that can form physical associations. The computational strategy used to prioritize coiled-coil candidates for testing dramatically improved the efficiency of discovery in a large experimental screen. As assessed by comprehensive yeast two-hybrid assays, computational prefiltering retained 90% of positive interacting pairs and eliminated > 60% of negatives from a set of interaction candidates. The coiled-coil-mediated interaction network elucidated using the combined computational/experimental approach comprises 80 coiled-coil associations between 58 protein pairs, among which 21 protein interactions have not been previously reported in interaction databases and 26 interactions were previously known at the protein level but have now been localized to the coiled-coil motif. The coiled-coil-mediated interactions were specific rather than promiscuous, and many interactions could be recapitulated in a green fluorescent protein complementation assay. Our method provides an efficient route to discovering new coiled-coil interactions and uncovers a number of associations that may have functional significance for vesicular trafficking.     

Live-cell imaging of membrane proteins by a coiled-coil labeling method—Principles and applications

In situ investigations in living cell membranes are important to elucidate the dynamic behaviors of membrane proteins in complex biomembrane environments. Protein-specific labeling is a key technique for the detection of a target protein by fluorescence imaging. The use of post-translational labeling methods using a genetically encodable tag and synthetic probes targeting the tag offer a smaller label size, labeling with synthetic fluorophores, and precise control of the labeling ratio in multicolor labeling compared with conventional genetic fusions with fluorescent proteins. This review focuses on tag–probe labeling studies for live-cell analysis of membrane proteins based on heterodimeric peptide pairs that form coiled-coil structures. The robust and simple peptide–peptide interaction enables not only labeling of membrane proteins by noncovalent interactions, but also covalent crosslinking and acyl transfer reactions guided by coiled-coil assembly. A number of studies have demonstrated that membrane protein behaviors in live cells, such as internalization of receptors and the oligomeric states of various membrane proteins (G-protein-coupled receptors, epidermal growth factor receptors, influenza A M2 channel, and glycopholin A), can be precisely analyzed using coiled-coil labeling, indicating the potential of this labeling method in membrane protein research.     

A coiled-coil domain of melanophilin is essential for Myosin Va recruitment and melanosome transport in melanocytes

Melanophilin (Mlph) regulates retention of melanosomes at the peripheral actin cytoskeleton of melanocytes, a process essential for normal mammalian pigmentation. Mlph is proposed to be a modular protein binding the melanosome-associated protein Rab27a, Myosin Va (MyoVa), actin, and microtubule end-binding protein (EB1), via distinct N-terminal Rab27a-binding domain (R27BD), medial MyoVa-binding domain (MBD), and C-terminal actin-binding domain (ABD), respectively. We developed a novel melanosome transport assay using a Mlph-null cell line to study formation of the active Rab27a:Mlph:MyoVa complex. Recruitment of MyoVa to melanosomes correlated with rescue of melanosome transport and required intact R27BD together with MBD exon F-binding region (EFBD) and unexpectedly a potential coiled-coil forming sequence within ABD. In vitro binding studies indicate that the coiled-coil region enhances binding of MyoVa by Mlph MBD. Other regions of Mlph reported to interact with MyoVa globular tail, actin, or EB1 are not essential for melanosome transport rescue. The strict correlation between melanosomal MyoVa recruitment and rescue of melanosome distribution suggests that stable interaction with Mlph and MyoVa activation are nondissociable events. Our results highlight the importance of the coiled-coil region together with R27BD and EFBD regions of Mlph in the formation of the active melanosomal Rab27a-Mlph-MyoVa complex.     

Application of the augmented theory of alpha-helix-to-random-coil transitions of two-chain, coiled coils to extant data on synthetic, tropomyosin-analog peptides

The statistical mechanical theory for the helix-to-random-coil transition in two-chain coiled coils is applied to extant data for two synthetic coiled-coil polypeptides. These peptides have the primary structure K(LEALEGK)_n, in which n = 4, 5. This repeating heptet sequence mimics the pattern of hydrophobic, acidic, and basic residues characteristic of the 284-residue tropomyosin molecule, the prototypical coiled-coil protein. Theoretical calculations for single chains show that such model peptides cannot be directly compared to proteins like tropomyosin because of differences in chain length (29 and 36 residues vs 284) and in intrachain interactions, the latter caused by the differences in amino acid composition and seqeunce between protein and model. Application of the theory to extant data on the two synthetic peptides provides a semiquantitative fit and results in an assessment of the interhelix interaction in the model peptides. The value obtained, ～ 2000 cal · (mol of turn pairs)^–1, is four to five times larger than has been obtained for tropomyosin. This probably is a result of greater regularity in the structure of the synthetics and of the exclusive presence of leucine in the hydrophobic interface. The theory employed here insists that this powerful interhelix interaction in the synthetic is the principal reason that such short chains can be so highly helical at moderate and low temperatures. Theory predicts, indeed, that a tropomyosin-length chain with a sequence homologous to these synthetics would be completely thermally stable in the entire temperature range accessible in aqueous solutions. Theory also predicts a much more pronounced effect of concentration on the 29- and 36-residue synthetic polymers than is predicted or observed in the case of tropomyosin, and it also predicts a pronounced stabilizing effect of pH-reduction on the thermal curves. On the last two points, sufficient data are not yet available with which to test the theory.     

Dissecting the specificity of protein-protein interaction in bacterial two-component signaling: orphans and crosstalks

Predictive understanding of the myriads of signal transduction pathways in a cell is an outstanding challenge of systems biology. Such pathways are primarily mediated by specific but transient protein-protein interactions, which are difficult to study experimentally. In this study, we dissect the specificity of protein-protein interactions governing two-component signaling (TCS) systems ubiquitously used in bacteria. Exploiting the large number of sequenced bacterial genomes and an operon structure which packages many pairs of interacting TCS proteins together, we developed a computational approach to extract a molecular interaction code capturing the preferences of a small but critical number of directly interacting residue pairs. This code is found to reflect physical interaction mechanisms, with the strongest signal coming from charged amino acids. It is used to predict the specificity of TCS interaction: Our results compare favorably to most available experimental results, including the prediction of 7 (out of 8 known) interaction partners of orphan signaling proteins in Caulobacter crescentus. Surveying among the available bacterial genomes, our results suggest 15～25% of the TCS proteins could participate in out-of-operon "crosstalks". Additionally, we predict clusters of crosstalking candidates, expanding from the anecdotally known examples in model organisms. The tools and results presented here can be used to guide experimental studies towards a system-level understanding of two-component signaling.     

Interaction between human myelin basic protein and lipophilin

The interaction of human myelin basic protein with lipophilin has been demonstrated by affinity chromatography. The interaction was specific since neither basic protein, nor albumin bound to an affinity column consisting of BP bound to agarose. Conversely an albumin affinity column failed to bind BP. The pH dependency of the interaction correlated with the known pK for histidine. By the use of large peptides formed by tryptophanyl cleavage by BNPS-skatole, peptide 1–117 bound to the BP affinity column while neither the smaller peptide, 118–170, nor the synthetic nonapeptide bound. The large fragment contains 9 of the 10 histidines in the molecule which may explain the binding of this fragment. The result of such protein-protein interactions makes available a large number of new antigenic sites and extends considerably the range of encephalitogens for disease induction.Special Issue dedicated to Dr. Elizabeth Roboz-Einstein.     

Mining protein networks for synthetic genetic interactions

Background  

The local connectivity and global position of a protein in a protein interaction network are known to correlate with some of its functional properties, including its essentiality or dispensability. It is therefore of interest to extend this observation and examine whether network properties of two proteins considered simultaneously can determine their joint dispensability, i.e., their propensity for synthetic sick/lethal interaction. Accordingly, we examine the predictive power of protein interaction networks for synthetic genetic interaction in Saccharomyces cerevisiae, an organism in which high confidence protein interaction networks are available and synthetic sick/lethal gene pairs have been extensively identified.     

Genome-Wide Scoring of Positive and Negative Epistasis through Decomposition of Quantitative Genetic Interaction Fitness Matrices

Recent technological developments in genetic screening approaches have offered the means to start exploring quantitative genotype-phenotype relationships on a large-scale. What remains unclear is the extent to which the quantitative genetic interaction datasets can distinguish the broad spectrum of interaction classes, as compared to existing information on mutation pairs associated with both positive and negative interactions, and whether the scoring of varying degrees of such epistatic effects could be improved by computational means. To address these questions, we introduce here a computational approach for improving the quantitative discrimination power encoded in the genetic interaction screening data. Our matrix approximation model decomposes the original double-mutant fitness matrix into separate components, representing variability across the array and query mutants, which can be utilized for estimating and correcting the single-mutant fitness effects, respectively. When applied to three large-scale quantitative interaction datasets in yeast, we could improve the accuracy of scoring various interaction classes beyond that obtained with the original fitness data, especially in synthetic genetic array (SGA) and in genetic interaction mapping (GIM) datasets. In addition to the known pairs of interactions used in the evaluation of the computational approach, a number of novel interaction pairs were also predicted, along with underlying biological mechanisms, which remained undetected by the original datasets. It was shown that the optimal choice of the scoring function depends heavily on the screening approach and on the interaction class under analysis. Moreover, a simple preprocessing of the fitness matrix could further enhance the discrimination power of the epistatic miniarray profiling (E-MAP) dataset. These systematic evaluation results provide in-depth information on the optimal analysis of the future, large-scale screening experiments. In general, the modeling framework, enabling accurate identification and classification of genetic interactions, provides a solid basis for completing and mining the genetic interaction networks in yeast and other organisms.     

Coiled-coil networking shapes cell molecular machinery

The highly abundant α-helical coiled-coil motif not only mediates crucial protein–protein interactions in the cell but is also an attractive scaffold in synthetic biology and material science and a potential target for disease intervention. Therefore a systematic understanding of the coiled-coil interactions (CCIs) at the organismal level would help unravel the full spectrum of the biological function of this interaction motif and facilitate its application in therapeutics. We report the first identified genome-wide CCI network in Saccharomyces cerevisiae, which consists of 3495 pair-wise interactions among 598 predicted coiled-coil regions. Computational analysis revealed that the CCI network is specifically and functionally organized and extensively involved in the organization of cell machinery. We further show that CCIs play a critical role in the assembly of the kinetochore, and disruption of the CCI network leads to defects in kinetochore assembly and cell division. The CCI network identified in this study is a valuable resource for systematic characterization of coiled coils in the shaping and regulation of a host of cellular machineries and provides a basis for the utilization of coiled coils as domain-based probes for network perturbation and pharmacological applications.     

Bacterial beta-lactamase fragmentation complementation strategy can be used as a method for identifying interacting protein pairs

We investigated the applicability of the TEM-1 beta- lactamase fragment complementation (BFC) system to develop a strategy for the screening of protein-protein interactions in bacteria. A BFC system containing a human Fas-associated death domain (hFADD) and human Fas death domain (hFasDD) was generated. The hFADD-hFasDD interaction was verified by cell survivability in ampicillin-containing medium and the colorimetric change of nitrocefin. It was also confirmed by His pull-down assay using cell lysates obtained in selection steps. A coiled-coil helix coiled-coil domain-containing protein 5 (CHCH5) was identified as an interacting protein of human uracil DNA glycosylase (hUNG) from the bacterial BFC cDNA library strategy. The interaction between hUNG and CHCH5 was further confirmed with immunoprecipitation using a mammalian expression system. CHCH5 enhanced the DNA glycosylase activity of hUNG to remove uracil from DNA duplexes containing a U/G mismatch pair. These results suggest that the bacterial BFC cDNA library strategy can be effectively used to identify interacting protein pairs.     

合成生物学及其在生物技术中的应用进展

合成生物学是一门21世纪生物学的新兴学科,它着眼生物科学与工程科学的结合,把生物系统当作工程系统"从下往上"进行处理,由"单元"(unit)到"部件"(device)再到"系统"(system)来设计,修改和组装细胞构件及生物系统.合成生物学是分子和细胞生物学、进化系统学、生物化学、信息学、数学、计算机和工程等多学科交叉的产物.目前研究应用包括两个主要方面:一是通过对现有的、天然存在的生物系统进行重新设计和改造,修改已存在的生物系统,使该系统增添新的功能.二是通过设计和构建新的生物零件、组件和系统,创造自然界中尚不存在的人工生命系统.合成生物学作为一门建立在基因组方法之上的学科,主要强调对创造人工生命形态的计算生物学与实验生物学的协同整合.必须强调的是,用来构建生命系统新结构、产生新功能所使用的组件单元既可以是基因、核酸等生物组件,也可以是化学的、机械的和物理的元件.本文跟踪合成生物学研究及应用,对其在DNA水平编程、分子修饰、代谢途径、调控网络和工业生物技术等方面的进展进行综述.     

Interaction between the IncHI1 plasmid R27 coupling protein and type IV secretion system: TraG associates with the coiled-coil mating pair formation protein TrhB

Assemblies of plasmid-encoded proteins direct the conjugative transfer of plasmid DNA molecules between bacteria. These include the membrane-associated mating pair formation (Mpf) complex necessary for pilus production and the cytoplasmic relaxosome required for DNA processing. The proposed link between these distinct protein complexes is the coupling protein (the TraG family of proteins). Interactions between the coupling protein and relaxosome components have been previously characterized and we document here, for the first time, a direct interaction between the coupling protein and an Mpf protein. Using the adenylate cyclase bacterial two-hybrid (BTH) system, we present in vivo evidence that the IncHI1 plasmid R27-encoded proteins TraG and TrhB interact. This interaction was verified through a co-immunoprecipitation reaction. We have also been able to delineate the interaction domain of TrhB to TraG by showing a positive interaction using the first 220 amino acids of TrhB (452 aa). TrhB has a proline-rich domain from amino acids 135-173 which may serve to facilitate protein interactions and/or periplasmic extension. TrhB self association was detected using far-Western, co-immunoprecipitation, and also BTH analysis, which was used to define the homotypic interaction domain, comprising a predicted coiled-coil region at residues 77-124 of TrhB. These data support a model in which the coupling protein interacts with an Mpf component to target the transferring DNA strand held by the relaxosome to the transmembrane Mpf complex.     

蛋白质相互作用数据库

随着“蛋白质组学”的蓬勃发展和人类对生物大分子功能机制的知识积累,涌现出海量的蛋白质相互作用数据。随之,研究者开发了300多个蛋白质相互作用数据库,用于存储、展示和数据的重利用。蛋白质相互作用数据库是系统生物学、分子生物学和临床药物研究的宝贵资源。本文将数据库分为3类：（1）综合蛋白质相互作用数据库;（2）特定物种的蛋白质相互作用数据库;（3）生物学通路数据库。重点介绍常用的蛋白质相互作用数据库,包括BioGRID、STRING、IntAct、MINT、DIP、IMEx、HPRD、Reactome和KEGG等。     

Nanoparticles for Protein Sensing in Primary Containers: Interaction Analysis and Application

Silver nanoparticles (AgNPs) are known to interact with proteins, leading to modifications of the plasmonic absorption that can be used to monitor this interaction, entailing a promising application for sensing adsorption of therapeutic proteins in primary containers. First, transmission electron microscopy in combination with plasmonic absorption and light scattering responses were used to characterize AgNPs and protein-AgNP complexes, including its concentration dependence, using two therapeutic molecules as models: a monoclonal antibody (mAb) and a synthetic copolymer (SC). Upon interaction, a protein corona was formed around AgNPs with the consequent shifting and broadening of their characteristic surface plasmon resonance (SPR) band (400 nm) to 410 nm and longer wavelenghts. Additional studies revealed secondary and three-dimensional structure modifications of model proteins upon interaction with AgNPs by circular dichroism and fluorescence techniques, respectively. Based on the modification of the SPR condition of AgNPs upon interaction with proteins, we developed a novel protein-sensing application of AgNPs in primary containers. This strategy was used to conduct a compatibility assessment of model proteins towards five commercially available prefillable glass syringe (PFS) models. mAb- and SC-exposed PFSs showed that 74 and 94% of cases were positive for protein adsorption, respectively. Interestingly, protein adsorption on 15% of total tested PFSs was negligible (below the nanogram level). Our results highlight the need of a case-by-case compatibility assessment of therapeutic proteins and their primary containers. This strategy has the potential to be easily applied on other containers and implemented during early-stage product development by pharmaceutical companies and for routine use during batch release by packaging manufacturers.     

Genome-wide identification of Arabidopsis coiled-coil proteins and establishment of the ARABI-COIL database

Increasing evidence demonstrates the importance of long coiled-coil proteins for the spatial organization of cellular processes. Although several protein classes with long coiled-coil domains have been studied in animals and yeast, our knowledge about plant long coiled-coil proteins is very limited. The repeat nature of the coiled-coil sequence motif often prevents the simple identification of homologs of animal coiled-coil proteins by generic sequence similarity searches. As a consequence, counterparts of many animal proteins with long coiled-coil domains, like lamins, golgins, or microtubule organization center components, have not been identified yet in plants. Here, all Arabidopsis proteins predicted to contain long stretches of coiled-coil domains were identified by applying the algorithm MultiCoil to a genome-wide screen. A searchable protein database, ARABI-COIL (http://www.coiled-coil.org/arabidopsis), was established that integrates information on number, size, and position of predicted coiled-coil domains with subcellular localization signals, transmembrane domains, and available functional annotations. ARABI-COIL serves as a tool to sort and browse Arabidopsis long coiled-coil proteins to facilitate the identification and selection of candidate proteins of potential interest for specific research areas. Using the database, candidate proteins were identified for Arabidopsis membrane-bound, nuclear, and organellar long coiled-coil proteins.     

Protein Interaction Networks

The study of protein interactions is playing an ever increasing role in our attempts to understand cells and diseases on a system-wide level. This article reviews several experimental approaches that are currently being used to measure protein–protein, protein–DNA and gene–gene interactions. These techniques have now been scaled up to produce extensive genome-wide data sets that are providing us with a first glimpse of global interaction networks. Complementing these experimental approaches, several computational methodologies to predict protein interactions are also reviewed. Existing databases that serve as repositories for protein interaction information and how such databases are used to analyze high-throughput data from a pathway perspective is also addressed. Finally, current efforts to combine multiple data types to obtain more accurate and comprehensive models of protein interactions are discussed. It is clear that the evolution of these experimental and computational approaches is rapidly changing our view of biology, and promises to provide us with an unprecedented ability to model cells and organisms at a system-wide level.     

Interaction between Intrinsically Disordered Proteins Frequently Occurs in a Human Protein-Protein Interaction Network

Intrinsic protein disorder is a widespread phenomenon characterised by a lack of stable three-dimensional structures and is considered to play an important role in protein-protein interactions (PPIs). This study examined the genome-wide preference of disorder in PPIs by using exhaustive disorder prediction in human PPIs. We categorised the PPIs into three types (interaction between disordered proteins, interaction between structured proteins, and interaction between a disordered protein and a structured protein) with regard to the flexibility of molecular recognition and compared these three interaction types in an existing human PPI network with those in a randomised network. Although the structured regions were expected to become the identifiers for binding recognition, this comparative analysis revealed unexpected results. The occurrence of interactions between disordered proteins was significantly frequent, and that between a disordered protein and a structured protein was significantly infrequent. We found that this propensity was much stronger in interactions between nonhub proteins. We also analysed the interaction types from a functional standpoint by using GO, which revealed that the interaction between disordered proteins frequently occurred in cellular processes, regulation, and metabolic processes. The number of interactions, especially in metabolic processes between disordered proteins, was 1.8 times as large as that in the randomised network. Another analysis conducted by using KEGG pathways provided results where several signaling pathways and disease-related pathways included many interactions between disordered proteins. All of these analyses suggest that human PPIs preferably occur between disordered proteins and that the flexibility of the interacting protein pairs may play an important role in human PPI networks.     

基因组工程在医学合成生物学中的应用

合成生物学旨在建立一套完整的工程理论和方法,通过设计和组装基本生物学元件,更为有效地实现复杂生物系统的设计,并使其完成可编程的生物学功能。近年来随着可编程基因组元件的出现,特别是CRISPR和CRISPRi技术平台的建立和完善,使得合成生物学进入了一个全新发展的时期。本文重点综述CRISPR等基因组编辑和调控技术,其在构建可编程生物学元件和复杂基因线路的应用以及合成生物学在医学中(称为医学合成生物学)的发展前景。