High-throughput screening for protein-protein interactions using two-hybrid assay

Role of BicDR in bristle shaft construction and support of BicD functions

Cell polarization requires asymmetric localization of numerous mRNAs, proteins and organelles. The movement of cargo towards the minus end of microtubules mostly depends on cytoplasmic dynein motors. In the dynein-dynactin-Bicaudal-D transport machinery, Bicaudal-D (BicD) links the cargo to the motor. Here, we focus on the role of Drosophila BicD-related (BicDR, CG32137) in the development of the long bristles. Together with BicD, it contributes to the organization and stability of the actin cytoskeleton in the not-yet-chitinized bristle shaft. BicD and BicDR also support the stable expression and distribution of Rab6 and Spn-F in the bristle shaft, including the distal tip localization of Spn-F, pointing to the role of microtubule-dependent vesicle trafficking for bristle construction. BicDR supports the function of BicD, and we discuss the hypothesis whereby BicDR might transport cargo more locally, with BicD transporting cargo over long distances, such as to the distal tip. We also identified embryonic proteins that interact with BicDR and appear to be BicDR cargo. For one of them, EF1γ (also known as eEF1γ), we show that the encoding gene EF1γ interacts with BicD and BicDR in the construction of the bristles.

Drosophila Me31B is a Dual eIF4E-Interacting Protein

Eukaryotic translation initiation factor 4E (eIF4E) is a key factor involved in different aspects of mRNA metabolism. Drosophila melanogaster genome encodes eight eIF4E isoforms, and the canonical isoform eIF4E-1 is a ubiquitous protein that plays a key role in mRNA translation. eIF4E-3 is specifically expressed in testis and controls translation during spermatogenesis. In eukaryotic cells, translational control and mRNA decay is highly regulated in different cytoplasmic ribonucleoprotein foci, which include the processing bodies (PBs). In this study, we show that Drosophila eIF4E-1 and eIF4E-3 occur in PBs along the DEAD-box RNA helicase Me31B. We show that Me31B interacts with eIF4E-1 and eIF4E-3 by means of yeast two-hybrid system, FRET in D. melanogaster S2 cells and coimmunoprecipitation in testis. Truncation and point mutations of Me31B proteins show two eIF4E-binding sites located in different protein domains. Residues Y401-L407 (at the carboxy-terminus) are essential for interaction with eIF4E-1, whereas residues F63-L70 (at the amino-terminus) are critical for interaction with eIF4E-3. The residue W117 in eIF4E-1 and the homolog position F103 in eIF4E-3 are necessary for Me31B-eIF4E interaction suggesting that the change of tryptophan to phenylalanine provides specificity. Me31B represents a novel type of eIF4E-interacting protein with dual and specific interaction domains that might be recognized by different eIF4E isoforms in different tissues, adding complexity to the control of gene expression in eukaryotes.

Eukaryotic translation initiation factor eIF4E-5 is required for spermiogenesis in Drosophila melanogaster

Drosophila sperm development is characterized by extensive post-transcriptional regulation whereby thousands of transcripts are preserved for translation during later stages. A key step in translation initiation is the binding of eukaryotic initiation factor 4E (eIF4E) to the 5' mRNA cap. In addition to canonical eIF4E-1, Drosophila has multiple eIF4E paralogs, including four (eIF4E-3, -4, -5, and -7) that are highly expressed in the testis. Among these, only eIF4E-3 has been characterized genetically. Here, using CRISPR/Cas9 mutagenesis, we determined that eIF4E-5 is essential for male fertility. eIF4E-5 protein localizes to the distal ends of elongated spermatid cysts, and eIF4E-5 mutants exhibit defects during post-meiotic stages, including a mild defect in spermatid cyst polarization. eIF4E-5 mutants also have a fully penetrant defect in individualization, resulting in failure to produce mature sperm. Indeed, our data indicate that eIF4E-5 regulates non-apoptotic caspase activity during individualization by promoting local accumulation of the E3 ubiquitin ligase inhibitor Soti. Our results further extend the diversity of non-canonical eIF4Es that carry out distinct spatiotemporal roles during spermatogenesis.

Female meiosis II and pronuclear fusion require the microtubule transport factor Bicaudal D

Bicaudal D (BicD) is a dynein adaptor that transports different cargoes along microtubules. Reducing the activity of BicD specifically in freshly laid Drosophila eggs by acute protein degradation revealed that BicD is needed to produce normal female meiosis II products, to prevent female meiotic products from re-entering the cell cycle, and for pronuclear fusion. Given that BicD is required to localize the spindle assembly checkpoint (SAC) components Mad2 and BubR1 to the female meiotic products, it appears that BicD functions to localize these components to control metaphase arrest of polar bodies. BicD interacts with Clathrin heavy chain (Chc), and both proteins localize to centrosomes, mitotic spindles and the tandem spindles during female meiosis II. Furthermore, BicD is required to localize clathrin and the microtubule-stabilizing factors transforming acidic coiled-coil protein (D-TACC/Tacc) and Mini spindles (Msps) correctly to the meiosis II spindles, suggesting that failure to localize these proteins may perturb SAC function. Furthermore, immediately after the establishment of the female pronucleus, D-TACC and Caenorhabditis elegans BicD, tacc and Chc are also needed for pronuclear fusion, suggesting that the underlying mechanism might be more widely used across species.

Interplay between SERCA, 4E-BP, and eIF4E in the Drosophila heart

Appropriate cardiac performance depends on a tightly controlled handling of Ca2+ in a broad range of species, from invertebrates to mammals. The role of the Ca2+ ATPase, SERCA, in Ca2+ handling is pivotal, and its activity is regulated, inter alia, by interacting with distinct proteins. Herein, we give evidence that 4E binding protein (4E-BP) is a novel regulator of SERCA activity in Drosophila melanogaster during cardiac function. Flies over-expressing 4E-BP showed improved cardiac performance in young individuals associated with incremented SERCA activity. Moreover, we demonstrate that SERCA interacts with translation initiation factors eIF4E-1, eIF4E-2 and eIF4E-4 in a yeast two-hybrid assay. The specific identification of eIF4E-4 in cardiac tissue leads us to propose that the interaction of elF4E-4 with SERCA may be the basis of the cardiac effects observed in 4E-BP over-expressing flies associated with incremented SERCA activity.

Exportin Crm1 is important for Swi6 nuclear shuttling and MBF transcription activation in Saccharomyces cerevisiae

BACKGROUND

Swi6 acts as a transcription factor in budding yeast, functioning in two different heterodimeric complexes, SBF and MBF, that activate the expression of distinct but overlapping sets of genes. Swi6 undergoes regulated changes in nucleocytoplasmic localization throughout the cell cycle that correlate with changes in gene expression. This study investigates how nucleocytoplasmic transport by multiple transport factors may influence specific Swi6 activities.

RESULTS

Here we show that the exportin Crm1 is important for Swi6 nuclear export and activity. Loss of a putative Crm1 NES or inhibition of Crm1 activity results in changes in nucleocytoplasmic Swi6 localization. Alteration of the Crm1 NES in Swi6 results in decreased MBF-mediated gene expression, but does not affect SBF reporter expression, suggesting that export of Swi6 by Crm1 regulates a subset of Swi6 transcription activation activity. Finally, alteration of the putative Crm1 NES in Swi6 results in cells that are larger than wild type, and this increase in cell size is exacerbated by deletion of Msn5.

CONCLUSIONS

These data provide evidence that Swi6 has at least two different exportins, Crm1 and Msn5, each of which interacts with a distinct nuclear export signal. We identify a putative nuclear export signal for Crm1 within Swi6, and observe that export by Crm1 or Msn5 independently influences Swi6-regulated expression of a different subset of Swi6-controlled genes. These findings provide new insights into the complex regulation of Swi6 transcription activation activity and the role of nucleocytoplasmic shuttling in regulated gene expression.

Identification of hub genes for early detection of bone metastasis in breast cancer

BACKGROUND

Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patients. Thus, we need to identify and validate early detection markers that can differentiate metastasis from non-metastasis breast cancers.

METHODS

GSE55715, GSE103357, and GSE146661 gene expression profiling data were downloaded from the GEO database. There was 14 breast cancer with bone metastasis samples and 8 breast cancer tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). The volcano plots, Venn diagrams, and annular heatmap were generated by using the ggplot2 package. By using the cluster Profiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, K-M survival and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 143 DEGs were enriched in the following GO terms: extracellular structure organization, extracellular matrix organization, leukocyte migration class II protein complex, collagen tridermic protein complex, extracellular matrix structural constituent, growth factor binding, and platelet-derived growth factor binding. In the KEGG pathway enrichment analysis, DEGs were enriched in Staphylococcus aureus infection, Complement and coagulation cascades, and Asthma. By PPI network analysis, we selected the top 10 genes, including SLCO2B1, STAB1, SERPING1, HLA-DOA, AIF1, GIMAP4, C1orf162, HLA-DMB, ADAP2, and HAVCR2. By using TCGA and THPA databases, we validated 2 genes, SERPING1 and GIMAP4, that were related to the early detection of bone metastasis in BC.

CONCLUSIONS

2 abnormally expressed hub genes could play a pivotal role in the breast cancer with bone metastasis by affecting bone homeostasis imbalance in the bone microenvironment.

Locally Adjust Networks Based on Connectivity and Semantic Similarities for Disease Module Detection

For studying the pathogenesis of complex diseases, it is important to identify the disease modules in the system level. Since the protein-protein interaction (PPI) networks contain a number of incomplete and incorrect interactome, most existing methods often lead to many disease proteins isolating from disease modules. In this paper, we propose an effective disease module identification method IDMCSS, where the used human PPI networks are obtained by adding some potential missing interactions from existing PPI networks, as well as removing some potential incorrect interactions. In IDMCSS, a network adjustment strategy is developed to add or remove links around disease proteins based on both topological and semantic information. Next, neighboring proteins of disease proteins are prioritized according to a suggested similarity between each of them and disease proteins, and the protein with the largest similarity with disease proteins is added into a candidate disease protein set one by one. The stopping criterion is set to the boundary of the disease proteins. Finally, the connected subnetwork having the largest number of disease proteins is selected as a disease module. Experimental results on asthma demonstrate the effectiveness of the method in comparison to existing algorithms for disease module identification. It is also shown that the proposed IDMCSS can obtain the disease modules having crucial biological processes of asthma and 12 targets for drug intervention can be predicted.

Identification of 5 Hub Genes Related to the Early Diagnosis, Tumour Stage, and Poor Outcomes of Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis

BACKGROUND

The majority of primary liver cancers in adults worldwide are hepatocellular carcinomas (HCCs, or hepatomas). Thus, a deep understanding of the underlying mechanisms for the pathogenesis and carcinogenesis of HCC at the molecular level could facilitate the development of novel early diagnostic and therapeutic treatments to improve the approaches and prognosis for HCC patients. Our study elucidates the underlying molecular mechanisms of HBV-HCC development and progression and identifies important genes related to the early diagnosis, tumour stage, and poor outcomes of HCC.

METHODS

GSE55092 and GSE121248 gene expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. There were 119 HCC samples and 128 nontumour tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). Volcano plots and Venn diagrams were drawn by using the ggplot2 package in R. A heat map was generated by using Heatmapper. By using the clusterProfiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, KM survival curves and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 694 DEGs were enriched in the following GO terms: organic acid catabolic process, carboxylic acid catabolic process, carboxylic acid biosynthetic process, collagen-containing extracellular matrix, blood microparticle, condensed chromosome kinetochore, arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. In the KEGG pathway enrichment analysis, DEGs were enriched in arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. By PPI network construction and analysis of hub genes, we selected the top 10 genes, including CDK1, CCNB2, CDC20, BUB1, BUB1B, CCNB1, NDC80, CENPF, MAD2L1, and NUF2. By using TCGA and THPA databases, we found five genes, CDK1, CDC20, CCNB1, CENPF, and MAD2L1, that were related to the early diagnosis, tumour stage, and poor outcomes of HBV-HCC.

CONCLUSIONS

Five abnormally expressed hub genes of HBV-HCC are informative for early diagnosis, tumour stage determination, and poor outcome prediction.

Improved cytokine-receptor interaction prediction by exploiting the negative sample space

Background

Cytokines act by binding to specific receptors in the plasma membrane of target cells. Knowledge of cytokine–receptor interaction (CRI) is very important for understanding the pathogenesis of various human diseases—notably autoimmune, inflammatory and infectious diseases—and identifying potential therapeutic targets. Recently, machine learning algorithms have been used to predict CRIs. “Gold Standard” negative datasets are still lacking and strong biases in negative datasets can significantly affect the training of learning algorithms and their evaluation. To mitigate the unrepresentativeness and bias inherent in the negative sample selection (non-interacting proteins), we propose a clustering-based approach for representative negative sample selection.

Results

We used deep autoencoders to investigate the effect of different sampling approaches for non-interacting pairs on the training and the performance of machine learning classifiers. By using the anomaly detection capabilities of deep autoencoders we deduced the effects of different categories of negative samples on the training of learning algorithms. Random sampling for selecting non-interacting pairs results in either over- or under-representation of hard or easy to classify instances. When K-means based sampling of negative datasets is applied to mitigate the inadequacies of random sampling, random forest (RF) together with the combined feature set of atomic composition, physicochemical-2grams and two different representations of evolutionary information performs best. Average model performances based on leave-one-out cross validation (loocv) over ten different negative sample sets that each model was trained with, show that RF models significantly outperform the previous best CRI predictor in terms of accuracy (+ 5.1%), specificity (+ 13%), mcc (+ 0.1) and g-means value (+ 5.1). Evaluations using tenfold cv and training/testing splits confirm the competitive performance.

Conclusions

A comparative analysis was performed to assess the effect of three different sampling methods (random, K-means and uniform sampling) on the training of learning algorithms using different evaluation methods. Models trained on K-means sampled datasets generally show a significantly improved performance compared to those trained on random selections—with RF seemingly benefiting most in our particular setting. Our findings on the sampling are highly relevant and apply to many applications of supervised learning approaches in bioinformatics.

Prediction of cassava protein interactome based on interolog method

Cassava is a starchy root crop whose role in food security becomes more significant nowadays. Together with the industrial uses for versatile purposes, demand for cassava starch is continuously growing. However, in-depth study to uncover the mystery of cellular regulation, especially the interaction between proteins, is lacking. To reduce the knowledge gap in protein-protein interaction (PPI), genome-scale PPI network of cassava was constructed using interolog-based method (MePPI-In, available at http://bml.sbi.kmutt.ac.th/ppi). The network was constructed from the information of seven template plants. The MePPI-In included 90,173 interactions from 7,209 proteins. At least, 39 percent of the total predictions were found with supports from gene/protein expression data, while further co-expression analysis yielded 16 highly promising PPIs. In addition, domain-domain interaction information was employed to increase reliability of the network and guide the search for more groups of promising PPIs. Moreover, the topology and functional content of MePPI-In was similar to the networks of Arabidopsis and rice. The potential contribution of MePPI-In for various applications, such as protein-complex formation and prediction of protein function, was discussed and exemplified. The insights provided by our MePPI-In would hopefully enable us to pursue precise trait improvement in cassava.

Gene gravity-like algorithm for disease gene prediction based on phenotype-specific network

Background

Polygenic diseases are usually caused by the dysfunction of multiple genes. Unravelling such disease genes is crucial to fully understand the genetic landscape of diseases on molecular level. With the advent of ‘omic’ data era, network-based methods have prominently boosted disease gene discovery. However, how to make better use of different types of data for the prediction of disease genes remains a challenge.

Results

In this study, we improved the performance of disease gene prediction by integrating the similarity of disease phenotype, biological function and network topology. First, for each phenotype, a phenotype-specific network was specially constructed by mapping phenotype similarity information of given phenotype onto the protein-protein interaction (PPI) network. Then, we developed a gene gravity-like algorithm, to score candidate genes based on not only topological similarity but also functional similarity. We tested the proposed network and algorithm by conducting leave-one-out and leave-10%-out cross validation and compared them with state-of-art algorithms. The results showed a preference to phenotype-specific network as well as gene gravity-like algorithm. At last, we tested the predicting capacity of proposed algorithms by test gene set derived from the DisGeNET database. Also, potential disease genes of three polygenic diseases, obesity, prostate cancer and lung cancer, were predicted by proposed methods. We found that the predicted disease genes are highly consistent with literature and database evidence.

Conclusions

The good performance of phenotype-specific networks indicates that phenotype similarity information has positive effect on the prediction of disease genes. The proposed gene gravity-like algorithm outperforms the algorithm of Random Walk with Restart (RWR), implicating its predicting capacity by combing topological similarity with functional similarity. Our work will give an insight to the discovery of disease genes by fusing multiple similarities of genes and diseases.

Electronic supplementary material

The online version of this article (10.1186/s12918-017-0519-9) contains supplementary material, which is available to authorized users.

Cbp80 is needed for the expression of piRNA components and piRNAs

Cap binding protein 80 (Cbp80) is the larger subunit of the nuclear cap-binding complex (nCBC), which is known to play important roles in nuclear mRNA processing, export, stability and quality control events. Reducing Cbp80 mRNA levels in the female germline revealed that Cbp80 is also involved in defending the germline against transposable elements. Combining such knockdown experiments with large scale sequencing of small RNAs further showed that Cbp80 is involved in the initial biogenesis of piRNAs as well as in the secondary biogenesis pathway, the ping-pong amplification cycle. We further found that Cbp80 knockdown not only led to the upregulation of transposons, but also to delocalization of Piwi, Aub and Ago3, key factors in the piRNA biosynthesis pathway. Furthermore, compared to controls, levels of Piwi and Aub were also reduced upon knock down of Cbp80. On the other hand, with the same treatment we could not detect significant changes in levels or subcellular distribution (nuage localization) of piRNA precursor transcripts. This shows that Cbp80 plays an important role in the production and localization of the protein components of the piRNA pathway and it seems to be less important for the production and export of the piRNA precursor transcripts.

Predicting Protein-Protein Interactions Using BiGGER: Case Studies

The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A) in which no specific contact data is available; (Case Study B) when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling) on one of the partners is available; and (Case Study C) when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields.

Modelling and analysis of an ensemble of eukaryotic translation initiation models

Programmed protein synthesis plays an important role in the cell cycle. Deregulated translation has been observed in several cancers. In this study, the authors constructed an ensemble of mathematical models describing the integration of growth factor signals with translation initiation. Using these models, the authors estimated critical structural features of the translation architecture. Sensitivity and robustness analysis with and without growth factors suggested that a balance between competing regulatory programmes governed translation initiation. Proteins such as Akt and mTor promoted initiation by integrating growth factor signals with the assembly of the 80S initiation complex. However, negative regulators such as PTEN and 4EBP1 restrained initiation in the absence of stimulation. Other proteins such as eIF4E were also found to be structurally critical as deletion of amplification of these components resulted in a network incapable of nominal operation. These findings could help understand the molecular basis of translation deregulation observed in cancer and perhaps lead to new anti-cancer therapeutic strategies. [Includes supplementary material].

PsAP2 an AP2/ERF family transcription factor from Papaver somniferum enhances abiotic and biotic stress tolerance in transgenic tobacco

The AP2/ERFs are one of the most important family of transcription factors which regulate multiple responses like stress, metabolism and development in plants. We isolated PsAP2 a novel AP2/ERF from Papaver somniferum which was highly upregulated in response to wounding followed by ethylene, methyl jasmonate and ABA treatment. PsAP2 showed specific binding with both DRE and GCC box elements and it was able to transactivate the reporter genes in yeast. PsAP2 overexpressing transgenic tobacco plants exhibited enhanced tolerance towards both abiotic and biotic stresses . Real time transcript expression analysis showed constitutive upregulation of tobacco Alternative oxidase1a and Myo-inositol-1-phosphate synthase in PsAP2 overexpressing tobacco plants. Further, PsAP2 showed interaction with NtAOX1a promoter in vitro, it also specifically activated the NtAOX1a promoter in yeast and tobacco BY2 cells. The silencing of PsAP2 using VIGS lead to significant reduction in the AOX1 level in P. somniferum. Taken together PsAP2 can directly bind and transcriptionally activate NtAOX1a and its overexpression in tobacco imparted increased tolerance towards both abiotic and biotic stress.

The Protein Interactome of Mycobacteriophage Giles Predicts Functions for Unknown Proteins

Mycobacteriophages are viruses that infect mycobacterial hosts and are prevalent in the environment. Nearly 700 mycobacteriophage genomes have been completely sequenced, revealing considerable diversity and genetic novelty. Here, we have determined the protein complement of mycobacteriophage Giles by mass spectrometry and mapped its genome-wide protein interactome to help elucidate the roles of its 77 predicted proteins, 50% of which have no known function. About 22,000 individual yeast two-hybrid (Y2H) tests with four different Y2H vectors, followed by filtering and retest screens, resulted in 324 reproducible protein-protein interactions, including 171 (136 nonredundant) high-confidence interactions. The complete set of high-confidence interactions among Giles proteins reveals new mechanistic details and predicts functions for unknown proteins. The Giles interactome is the first for any mycobacteriophage and one of just five known phage interactomes so far. Our results will help in understanding mycobacteriophage biology and aid in development of new genetic and therapeutic tools to understand Mycobacterium tuberculosis.

IMPORTANCE

Mycobacterium tuberculosis causes over 9 million new cases of tuberculosis each year. Mycobacteriophages, viruses of mycobacterial hosts, hold considerable potential to understand phage diversity, evolution, and mycobacterial biology, aiding in the development of therapeutic tools to control mycobacterial infections. The mycobacteriophage Giles protein-protein interaction network allows us to predict functions for unknown proteins and shed light on major biological processes in phage biology. For example, Giles gp76, a protein of unknown function, is found to associate with phage packaging and maturation. The functions of mycobacteriophage-derived proteins may suggest novel therapeutic approaches for tuberculosis. Our ORFeome clone set of Giles proteins and the interactome data will be useful resources for phage interactomics.

Massively Parallel Functional Analysis of BRCA1 RING Domain Variants

Interpreting variants of uncertain significance (VUS) is a central challenge in medical genetics. One approach is to experimentally measure the functional consequences of VUS, but to date this approach has been post hoc and low throughput. Here we use massively parallel assays to measure the effects of nearly 2000 missense substitutions in the RING domain of BRCA1 on its E3 ubiquitin ligase activity and its binding to the BARD1 RING domain. From the resulting scores, we generate a model to predict the capacities of full-length BRCA1 variants to support homology-directed DNA repair, the essential role of BRCA1 in tumor suppression, and show that it outperforms widely used biological-effect prediction algorithms. We envision that massively parallel functional assays may facilitate the prospective interpretation of variants observed in clinical sequencing.

Protein interaction networks as starting points to identify novel antimicrobial drug targets

Novel classes of antimicrobials are needed to address the challenge of multidrug-resistant bacteria. Current bacterial drug targets mainly consist of specific proteins or subsets of proteins without regard for either how these targets are integrated in cellular networks or how they may interact with host proteins. However, proteins rarely act in isolation, and the majority of biological processes are dependent on interactions with other proteins. Consequently, protein-protein interaction (PPI) networks offer a realm of unexplored potential for next-generation drug targets. In this review, we argue that the architecture of bacterial or host-pathogen protein interactomes can provide invaluable insights for the identification of novel antibacterial drug targets.

Mextli is a novel eukaryotic translation initiation factor 4E-binding protein that promotes translation in Drosophila melanogaster

Translation is a fundamental step in gene expression, and translational control is exerted in many developmental processes. Most eukaryotic mRNAs are translated by a cap-dependent mechanism, which requires recognition of the 5'-cap structure of the mRNA by eukaryotic translation initiation factor 4E (eIF4E). eIF4E activity is controlled by eIF4E-binding proteins (4E-BPs), which by competing with eIF4G for eIF4E binding act as translational repressors. Here, we report the discovery of Mextli (Mxt), a novel Drosophila melanogaster 4E-BP that in sharp contrast to other 4E-BPs, has a modular structure, binds RNA, eIF3, and several eIF4Es, and promotes translation. Mxt is expressed at high levels in ovarian germ line stem cells (GSCs) and early-stage cystocytes, as is eIF4E-1, and we demonstrate the two proteins interact in these cells. Phenotypic analysis of mxt mutants indicates a role for Mxt in germ line stem cell (GSC) maintenance and in early embryogenesis. Our results support the idea that Mxt, like eIF4G, coordinates the assembly of translation initiation complexes, rendering Mxt the first example of evolutionary convergence of eIF4G function.

Comprehensive analysis of varicella-zoster virus proteins using a new monoclonal antibody collection

Varicella-zoster virus (VZV) is the etiological agent of chickenpox and shingles. Due to the virus's restricted host and cell type tropism and the lack of tools for VZV proteomics, it is one of the least-characterized human herpesviruses. We generated 251 monoclonal antibodies (MAbs) against 59 of the 71 (83%) currently known unique VZV proteins to characterize VZV protein expression in vitro and in situ. Using this new set of MAbs, 44 viral proteins were detected by Western blotting (WB) and indirect immunofluorescence (IF); 13 were detected by WB only, and 2 were detected by IF only. A large proportion of viral proteins was analyzed for the first time in the context of virus infection. Our study revealed the subcellular localization of 46 proteins, 14 of which were analyzed in detail by confocal microscopy. Seven viral proteins were analyzed in time course experiments and showed a cascade-like temporal gene expression pattern similar to those of other herpesviruses. Furthermore, selected MAbs tested positive on human skin lesions by using immunohistochemistry, demonstrating the wide applicability of the MAb collection. Finally, a significant portion of the VZV-specific antibodies reacted with orthologs of simian varicella virus (SVV), thus enabling the systematic analysis of varicella in a nonhuman primate model system. In summary, this study provides insight into the potential function of numerous VZV proteins and novel tools to systematically study VZV and SVV pathogenesis.

Eukaryotic initiation factor 4E-3 is essential for meiotic chromosome segregation, cytokinesis and male fertility in Drosophila

Gene expression is translationally regulated during many cellular and developmental processes. Translation can be modulated by affecting the recruitment of mRNAs to the ribosome, which involves recognition of the 5' cap structure by the cap-binding protein eIF4E. Drosophila has several genes encoding eIF4E-related proteins, but the biological role of most of them remains unknown. Here, we report that Drosophila eIF4E-3 is required specifically during spermatogenesis. Males lacking eIF4E-3 are sterile, showing defects in meiotic chromosome segregation, cytokinesis, nuclear shaping and individualization. We show that eIF4E-3 physically interacts with both eIF4G and eIF4G-2, the latter being a factor crucial for spermatocyte meiosis. In eIF4E-3 mutant testes, many proteins are present at different levels than in wild type, suggesting widespread effects on translation. Our results imply that eIF4E-3 forms specific eIF4F complexes that are essential for spermatogenesis.

RsfA (YbeB) proteins are conserved ribosomal silencing factors

The YbeB (DUF143) family of uncharacterized proteins is encoded by almost all bacterial and eukaryotic genomes but not archaea. While they have been shown to be associated with ribosomes, their molecular function remains unclear. Here we show that YbeB is a ribosomal silencing factor (RsfA) in the stationary growth phase and during the transition from rich to poor media. A knock-out of the rsfA gene shows two strong phenotypes: (i) the viability of the mutant cells are sharply impaired during stationary phase (as shown by viability competition assays), and (ii) during transition from rich to poor media the mutant cells adapt slowly and show a growth block of more than 10 hours (as shown by growth competition assays). RsfA silences translation by binding to the L14 protein of the large ribosomal subunit and, as a consequence, impairs subunit joining (as shown by molecular modeling, reporter gene analysis, in vitro translation assays, and sucrose gradient analysis). This particular interaction is conserved in all species tested, including Escherichia coli, Treponema pallidum, Streptococcus pneumoniae, Synechocystis PCC 6803, as well as human mitochondria and maize chloroplasts (as demonstrated by yeast two-hybrid tests, pull-downs, and mutagenesis). RsfA is unrelated to the eukaryotic ribosomal anti-association/60S-assembly factor eIF6, which also binds to L14, and is the first such factor in bacteria and organelles. RsfA helps cells to adapt to slow-growth/stationary phase conditions by down-regulating protein synthesis, one of the most energy-consuming processes in both bacterial and eukaryotic cells.

The YbeB/DUF143 family of proteins is one of the most widely conserved proteins with homologues present in almost all bacteria and eukaryotic organelles such as mitochondria and chloroplasts (but not archaea). While it has been shown that these proteins associate with ribosomes, their molecular function remained mysterious. Here we show that a knock-out of the ybeB gene causes a dramatic adaptation block during a shift from rich to poor media and seriously deteriorates the viability during stationary phase. YbeB of six different species binds to ribosomal protein L14. This interaction blocks the association of the two ribosomal subunits and, as a consequence, translation. YbeB is thus renamed “RsfA” (ribosomal silencing factor A). RsfA inhibits translation when nutrients are depleted (or when cells are in stationary phase), which helps the cell to save energy and nutrients, a critical function for all cells that are regularly struggling with limited resources.

Overexpression of CaTLP1, a putative transcription factor in chickpea (Cicer arietinum L.), promotes stress tolerance

Dehydration is the most crucial environmental constraint on plant growth and development, and agricultural productivity. To understand the underlying mechanism of stress tolerance, and to identify proteins for improving such important trait, we screened the dehydration-responsive proteome of chickpea and identified a tubby-like protein, referred to as CaTLP1. The CaTLP1 was found to predominantly bind to double-stranded DNA but incapable of transcriptional activation. We investigated the gene structure and organization and demonstrated, for the first time, that CaTLP1 may be involved in osmotic stress response in plants. The transcripts are strongly expressed in vegetative tissues but weakly in reproductive tissues. CaTLP1 is upregulated by dehydration and high salinity, and by treatment with abscisic acid (ABA), suggesting that its stress-responsive function might be associated with ABA-dependent network. Overexpression of CaTLP1 in transgenic tobacco plants conferred dehydration, salinity and oxidative stress tolerance along with improved shoot and root architecture. Molecular genetic analysis showed differential expression of CaTLP1 under normal and stress condition, and its preferential expression in the nucleus might be associated with enhanced stress tolerance. Our work suggests important roles of CaTLP1 in stress response as well as in the regulation of plant development.

Analysis of protein-protein interactions using high-throughput yeast two-hybrid screens

The yeast two-hybrid (Y2H) system is a powerful tool to identify binary protein-protein interactions. Here, we describe array-based two-hybrid methods that use defined libraries of open reading frames (ORFs) and pooled prey library screenings that use random genomic or cDNA libraries. The array-based Y2H system is well-suited for interactome studies of existing ORFeomes or subsets thereof, preferentially in a recombination-based cloning system. Array-based Y2H screens efficiently reduce false positives by using built-in controls, retesting, and evaluation of background activation. Hands-on time and the amount of used resources grow exponentially with the number of tested proteins; this is a disadvantage for large genome sizes. For large genomes, random library screen may be more efficient in terms of time and resources, but not as comprehensive as array screens, and it requires significant sequencing capacity. Furthermore, multiple variants of the Y2H vector systems detect markedly different subsets of interactions in the same interactome. Hence, only multiple variations of the Y2H systems ensure comprehensive coverage of an interactome.

In vivo approaches to dissecting the function of RNA helicases in eukaryotic ribosome assembly

In eukaryotes, ribosome biogenesis involves the nucleolar transcription and processing of pre-ribosomal RNA molecules (pre-rRNA) in a complex pathway requiring the participation of myriad protein and ribonucleoprotein factors. Through efforts aimed at categorizing and characterizing these factors, at least 20 RNA helicases have been shown to interact with or participate in the activities of the major ribosome biogenesis complexes. Unfortunately, little is known about the enzymatic properties of most of these helicases, and less is known about their roles in ribosome biogenesis and pre-rRNA maturation. This chapter presents approaches for characterizing RNA helicases involved in ribosome biogenesis. Included are methods for depletion of specific protein targets, with standard protocols for assaying the typical ribosome biogenesis defects that may result. Procedures and rationales for mutagenic studies of target proteins are discussed, as well as several approaches for identifying protein-protein interactions in order to determine functional context and potential cofactors of RNA helicases.

High throughput flow cytometry based yeast two-hybrid array approach for large-scale analysis of protein-protein interactions

The analysis of protein-protein interactions is a key focus of proteomics efforts. The yeast two-hybrid system (Y2H) has been the most commonly used method in genome-wide searches for protein interaction partners. However, the throughput of the current yeast two-hybrid array approach is hampered by the involvement of the time-consuming LacZ assay and/or the incompatibility of liquid handling automation due to the requirement for selection of colonies/diploids on agar plates. To facilitate large-scale Y2H assays, we report a novel array approach by coupling a GFP reporter based Y2H system with high throughput flow cytometry that enables the processing of a 96-well plate in as little as 3 min. In this approach, the yEGFP reporter has been established in both AH109 (MATa) and Y187 (MATα) reporter cells. It not only allows the generation of two copies of GFP reporter genes in diploid cells, but also allows the convenient determination of self-activators generated from both bait and prey constructs by flow cytometry. We demonstrate a Y2H array assay procedure that is carried out completely in liquid media in 96-well plates by mating bait and prey cells in liquid YPD media, selecting the diploids containing positive interaction pairs in selective media and analyzing the GFP reporter directly by flow cytometry. We have evaluated this flow cytometry based array procedure by showing that the interaction of the positive control pair P53/T is able to be reproducibly detected at 72 hr postmating compared with the negative control pairs. We conclude that our flow cytometry based yeast two-hybrid approach is robust, convenient, quantitative, and is amenable to large-scale analysis using liquid-handling automation.

Modeling and analysis of retinoic acid induced differentiation of uncommitted precursor cells

Manipulation of differentiation programs has therapeutic potential in a spectrum of human cancers and neurodegenerative disorders. In this study, we integrated computational and experimental methods to unravel the response of a lineage uncommitted precursor cell-line, HL-60, to Retinoic Acid (RA). HL-60 is a human myeloblastic leukemia cell-line used extensively to study human differentiation programs. Initially, we focused on the role of the BLR1 receptor in RA-induced differentiation and G1/0-arrest in HL-60. BLR1, a putative G protein-coupled receptor expressed following RA exposure, is required for RA-induced cell-cycle arrest and differentiation and causes persistent MAPK signaling. A mathematical model of RA-induced cell-cycle arrest and differentiation was formulated and tested against BLR1 wild-type (wt) knock-out and knock-in HL-60 cell-lines with and without RA. The current model described the dynamics of 729 proteins and protein complexes interconnected by 1356 interactions. An ensemble strategy was used to compensate for uncertain model parameters. The ensemble of HL-60 models recapitulated the positive feedback between BLR1 and MAPK signaling. The ensemble of models also correctly predicted Rb and p47phox regulation and the correlation between p21-CDK4-cyclin D formation and G1/0-arrest following exposure to RA. Finally, we investigated the robustness of the HL-60 network architecture to structural perturbations and generated experimentally testable hypotheses for future study. Taken together, the model presented here was a first step toward a systematic framework for analysis of programmed differentiation. These studies also demonstrated that mechanistic network modeling can help prioritize experimental directions by generating falsifiable hypotheses despite uncertainty.

The proteome and interactome of Streptococcus pneumoniae phage Cp-1

Mass spectrometry analysis of Streptococcus pneumoniae bacteriophage Cp-1 identified a total of 12 proteins, and proteome-wide yeast two-hybrid screens revealed 17 binary interactions mainly among these structural proteins. On the basis of the resulting linkage map, we suggest an improved structural model of the Cp-1 virion.

Genome annotation and intraviral interactome for the Streptococcus pneumoniae virulent phage Dp-1

Streptococcus pneumoniae causes several diseases, including pneumonia, septicemia, and meningitis. Phage Dp-1 is one of the very few isolated virulent S. pneumoniae bacteriophages, but only a partial characterization is currently available. Here, we confirmed that Dp-1 belongs to the family Siphoviridae. Then, we determined its complete genomic sequence of 56,506 bp. It encodes 72 open reading frames, of which 44 have been assigned a function. We have identified putative promoters, Rho-independent terminators, and several genomic clusters. We provide evidence that Dp-1 may be using a novel DNA replication system as well as redirecting host protein synthesis through queuosine-containing tRNAs. Liquid chromatography-mass spectrometry analysis of purified phage Dp-1 particles identified at least eight structural proteins. Finally, using comprehensive yeast two-hybrid screens, we identified 156 phage protein interactions, and this intraviral interactome was used to propose a structural model of Dp-1.

Interaction of the Aspergillus nidulans microtubule-organizing center (MTOC) component ApsB with gamma-tubulin and evidence for a role of a subclass of peroxisomes in the formation of septal MTOCs

Peroxisomes are a diverse class of organelles involved in different physiological processes in eukaryotic cells. Although proteins imported into peroxisomes carry a peroxisomal targeting sequence at the C terminus (PTS1) or an alternative one close to the N terminus (PTS2), the protein content of peroxisomes varies drastically. Here we suggest a new class of peroxisomes involved in microtubule (MT) formation. Eukaryotic cells assemble MTs from distinct points in the cell. In the fungus Aspergillus nidulans, septum-associated microtubule-organizing centers (sMTOCs) are very active in addition to the spindle pole bodies (SPBs). Previously, we identified a novel MTOC-associated protein, ApsB (Schizosaccharomyces pombe mto1), whose absence affected MT formation from sMTOCs more than from SPBs, suggesting that the two protein complexes are organized differently. We show here that sMTOCs share at least two further components, gamma-tubulin and GcpC (S. pombe Alp6) with SPBs and found that ApsB interacts with gamma-tubulin. In addition, we discovered that ApsB interacts with the Woronin body protein HexA and is targeted to a subclass of peroxisomes via a PTS2 peroxisomal targeting sequence. The PTS2 motif was necessary for function but could be replaced with a PTS1 motif at the C terminus of ApsB. These results suggest a novel function for a subclass of peroxisomes in cytoskeletal organization.

Proteasome nuclear activity affects chromosome stability by controlling the turnover of Mms22, a protein important for DNA repair

To expand the known spectrum of genes that maintain genome stability, we screened a recently released collection of temperature sensitive (Ts) yeast mutants for a chromosome instability (CIN) phenotype. Proteasome subunit genes represented a major functional group, and subsequent analysis demonstrated an evolutionarily conserved role in CIN. Analysis of individual proteasome core and lid subunit mutations showed that the CIN phenotype at semi-permissive temperature is associated with failure of subunit localization to the nucleus. The resultant proteasome dysfunction affects chromosome stability by impairing the kinetics of double strand break (DSB) repair. We show that the DNA repair protein Mms22 is required for DSB repair, and recruited to chromatin in a ubiquitin-dependent manner as a result of DNA damage. Moreover, subsequent proteasome-mediated degradation of Mms22 is necessary and sufficient for cell cycle progression through the G₂/M arrest induced by DNA damage. Our results demonstrate for the first time that a double strand break repair protein is a proteasome target, and thus link nuclear proteasomal activity and DSB repair.

Chromosome Instability (CIN) is a genome phenotype that involves changes in chromosome number or structure, and accounts for most malignancies. In this paper, we describe a screen to identify a set of novel CIN genes and find that proteasomal subunits represent a major functional group. We show that proteasome dysfunction affects CIN by impairing DNA double strand break (DSB) repair. Previous studies speculated that the proteasome is required to degrade one or more components of the DSB repair machinery; however, until now, no such target has been identified. Here we identify the previously described CIN gene MMS22 as a proteasomal target. We found that, as a result of DNA damage, Mms22 is ubiquitinated and recruited to chromatin. Mms22 then undergoes polyubiquitination and subsequent proteasome-mediated degradation. We also provide evidence that the degradation of Mms22 is important for the normal course of DNA repair and for exit from the G₂/M arrest induced by DNA damage. Our results demonstrate for the first time that a DSB repair protein is a proteasome target, linking nuclear proteasomal activity and DSB repair. The mechanism of regulation of Mms22 may serve as a paradigm to understand how these additional proteins are regulated by the proteasome.

One-plasmid tunable coexpression for mycobacterial protein-protein interaction studies

A single plasmid that allows controlled coexpression has been developed for use in mycobacteria. The tetracycline inducible promoter, PtetO, was used to provide tetracycline-dependent induction of one gene, while the Psmyc, Pimyc, or Phsp promoters were used to provide three different levels of constitutive expression of a second gene. The functions of these four individual promoters were established using green fluorescent protein (GFP) and a newly identified red fluorescence inducible protein from Geobacillus sterothermophilus strain G1.13 (RFIP) as reporters. The tandem use of GFP and RFIP as reporter genes allowed optimization of the tunable coexpression in Mycobacterium smegmatis; either time at a fixed inducer concentration or changes in inducer concentration could be used to control the protein:protein ratio. This single vector system was used to coexpress the two-protein Mycobacterium tuberculosis stearoyl-CoA Delta(9) desaturase complex (integral membrane desaturase Rv3229c and NADPH oxidoreductase Rv3230c) in M. smegmatis. The catalytic activity was found to increase in a manner corresponding to increasing the level of Rv3230c relative to a fixed level of Rv3229c. This system, which can yield finely tuned coexpression of the fatty acid desaturase complex in mycobacteria, may be useful for study of other multicomponent complexes. Furthermore, the tunable coexpression strategy used herein should also be applicable in other species with minor modifications.

Evolutionarily conserved herpesviral protein interaction networks

Herpesviruses constitute a family of large DNA viruses widely spread in vertebrates and causing a variety of different diseases. They possess dsDNA genomes ranging from 120 to 240 kbp encoding between 70 to 170 open reading frames. We previously reported the protein interaction networks of two herpesviruses, varicella-zoster virus (VZV) and Kaposi's sarcoma-associated herpesvirus (KSHV). In this study, we systematically tested three additional herpesvirus species, herpes simplex virus 1 (HSV-1), murine cytomegalovirus and Epstein-Barr virus, for protein interactions in order to be able to perform a comparative analysis of all three herpesvirus subfamilies. We identified 735 interactions by genome-wide yeast-two-hybrid screens (Y2H), and, together with the interactomes of VZV and KSHV, included a total of 1,007 intraviral protein interactions in the analysis. Whereas a large number of interactions have not been reported previously, we were able to identify a core set of highly conserved protein interactions, like the interaction between HSV-1 UL33 with the nuclear egress proteins UL31/UL34. Interactions were conserved between orthologous proteins despite generally low sequence similarity, suggesting that function may be more conserved than sequence. By combining interactomes of different species we were able to systematically address the low coverage of the Y2H system and to extract biologically relevant interactions which were not evident from single species.

Herpesvirus proteins interact with each other in a complex manner throughout the infectious cycle. This is probably best exemplified in the process where a large number of viral proteins come together to form new viral particles which are subsequently released from the infected cell. A more detailed understanding of how viral proteins interact with each other might assist the development of drugs which may inhibit these interactions and consequently block viral replication. Here we present three genome-wide studies of protein-protein interactions in the herpesviruses herpes simplex virus I, murine cytomegalovirus and Epstein-Barr virus. Altogether we identified 735 interactions in the three viruses, most of which have not previously been reported. By combining these studies with our previously published studies for Kaposi's sarcoma-associated herpesvirus and varicella-zoster virus we were able to perform a comparative analysis of interactions in five related viral species. We observed that a high proportion of interactions were conserved between the different species, despite a low degree of sequence conservation. This implies that by comparing interaction data, we were able to increase the coverage of our viral networks and thus obtain a better and more complete picture of interactions between herpesviral proteins.

CaZF, a plant transcription factor functions through and parallel to HOG and calcineurin pathways in Saccharomyces cerevisiae to provide osmotolerance

Salt-sensitive yeast mutants were deployed to characterize a gene encoding a C2H2 zinc finger protein (CaZF) that is differentially expressed in a drought-tolerant variety of chickpea (Cicer arietinum) and provides salinity-tolerance in transgenic tobacco. In Saccharomyces cerevisiae most of the cellular responses to hyper-osmotic stress is regulated by two interconnected pathways involving high osmolarity glycerol mitogen-activated protein kinase (Hog1p) and Calcineurin (CAN), a Ca(2+)/calmodulin-regulated protein phosphatase 2B. In this study, we report that heterologous expression of CaZF provides osmotolerance in S. cerevisiae through Hog1p and Calcineurin dependent as well as independent pathways. CaZF partially suppresses salt-hypersensitive phenotypes of hog1, can and hog1can mutants and in conjunction, stimulates HOG and CAN pathway genes with subsequent accumulation of glycerol in absence of Hog1p and CAN. CaZF directly binds to stress response element (STRE) to activate STRE-containing promoter in yeast. Transactivation and salt tolerance assays of CaZF deletion mutants showed that other than the transactivation domain a C-terminal domain composed of acidic and basic amino acids is also required for its function. Altogether, results from this study suggests that CaZF is a potential plant salt-tolerance determinant and also provide evidence that in budding yeast expression of HOG and CAN pathway genes can be stimulated in absence of their regulatory enzymes to provide osmotolerance.

Analysis of protein-protein interactions using array-based yeast two-hybrid screens

The yeast two-hybrid system (Y2H) is a powerful tool to identify protein-protein interactions. Here we describe array-based two-hybrid methods that use defined libraries of open reading frames (ORFs) as opposed to random genomic or cDNA libraries. The array-based Y2H system is well suited for interactome studies of existing ORFeomes or subsets thereof, preferentially in a recombination-based cloning system. Array-based Y2H screens efficiently reduce false positives by using built-in controls, retesting, and evaluation of background activation. Hands-on time and the amount of used resources grow exponentially with the number of tested proteins; this is a disadvantage for large genome sizes. For large genomes, random library screen may be more efficient in terms of time and resources, but not as comprehensive as array screens, and they require an efficient sequencing facility. However, large array screens require some extent of automation although they can be carried out manually on smaller scales. Future-generation Y2H plasmid constructs including tightly regulated expression systems and features that facilitate biochemical characterization will provide more efficient and powerful tools to identify interacting proteins.

The FF domains of yeast U1 snRNP protein Prp40 mediate interactions with Luc7 and Snu71

Background

The FF domain is conserved across all eukaryotes and usually acts as an adaptor module in RNA metabolism and transcription. Saccharomyces cerevisiae encodes two FF domain proteins, Prp40, a component of the U1 snRNP, and Ypr152c, a protein of unknown function. The structure of Prp40, its relationship to other proteins within the U1 snRNP, and its precise function remain little understood.

Results

Here we have investigated the essentiality and interaction properties of the FF domains of yeast Prp40. We show that the C-terminal two FF domains of Prp40 are dispensable. Deletion of additional FF domains is lethal. The first FF domain of Prp40 binds to U1 protein Luc7 in yeast two-hybrid and GST pulldown experiments. FF domains 2 and 3 bind to Snu71, another known U1 protein. Peptide array screens identified binding sites for FF1-2 within Snu71 (NDVHY) and for FF1 within Luc7 (ϕ[FHL] × [KR] × [GHL] with ϕ being a hydrophobic amino acid).

Conclusion

Prp40, Luc7, and Snu71 appear to form a subcomplex within the yeast U1snRNP. Our data suggests that the N-terminal FF domains are critical for these interactions. Crystallization of Prp40, Luc7, and Snu71 have failed so far but co-crystallization of pairs or the whole tri-complex may facilitate crystallographic and further functional analysis.

Proteomics: A Paradigm Shift

Proteome--the protein complement of a genome--has become the protein renaissance and a key research tool in the post-genomic era. The basic technology involves the routine usage of gel electrophoresis and spectrometry procedures for deciphering the primary protein sequence/structure as well as knowing certain unique post-translational modifications that a particular protein has undergone to perform a specific function in the cell. However, the recent advancements in protein analysis have ushered this science to provide deeper, bigger and more valuable perspectives regarding performance of subtle protein-protein interactions. Applications of this branch of molecular biology are as vast as the subject is and include clinical diagnostics, pharmaceutical and biotechnological industries. The 21st century hails the use of products, procedures and advancements of this science as finer touches required for the grooming of fast-paced technology.

The interactome: predicting the protein-protein interactions in cells

The term Interactome describes the set of all molecular interactions in cells, especially in the context of protein-protein interactions. These interactions are crucial for most cellular processes, so the full representation of the interaction repertoire is needed to understand the cell molecular machinery at the system biology level. In this short review, we compare various methods for predicting protein-protein interactions using sequence and structure information. The ultimate goal of those approaches is to present the complete methodology for the automatic selection of interaction partners using their amino acid sequences and/or three dimensional structures, if known. Apart from a description of each method, details of the software or web interface needed for high throughput prediction on the whole genome scale are also provided. The proposed validation of the theoretical methods using experimental data would be a better assessment of their accuracy.

Crystal structure of human Edc3 and its functional implications

Edc3 is an enhancer of decapping and serves as a scaffold that aggregates mRNA ribonucleoproteins together for P-body formation. Edc3 forms a network of interactions with the components of the mRNA decapping machinery and has a modular domain architecture consisting of an N-terminal Lsm domain, a central FDF domain, and a C-terminal YjeF-N domain. We have determined the crystal structure of the N-terminally truncated human Edc3 at a resolution of 2.2 A. The structure reveals that the YjeF-N domain of Edc3 possesses a divergent Rossmann fold topology that forms a dimer, which is supported by sedimentation velocity and sedimentation equilibrium analysis in solution. The dimerization interface of Edc3 is highly conserved in eukaryotes despite the overall low sequence homology across species. Structure-based site-directed mutagenesis revealed dimerization is required for efficient RNA binding, P-body formation, and likely for regulating the yeast Rps28B mRNA as well, suggesting that the dimeric form of Edc3 is a structural and functional unit in mRNA degradation.

High-throughput screening for protein-protein interactions using yeast two-hybrid arrays

Arrays are used for parallel assays of large numbers of proteins in a single experiment. They provide an alternative to libraries for protein screening purposes. This unit describes a protein array composed of living yeast (Saccharomyces cerevisiae) cells that can be used in a functional screen for protein interactions, the two-hybrid assay. The protocols described here use the yeast proteome as an example, but they can be applied to any other genome or subset thereof.

A test of highly optimized tolerance reveals fragile cell-cycle mechanisms are molecular targets in clinical cancer trials

Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g., those involved in cell-cycle regulation, can be resistant to some perturbations while highly sensitive to others. The “robust yet fragile” duality of networks has been termed Highly Optimized Tolerance (HOT) and has been the basis of new lines of inquiry in computational and experimental biology. In this study, we tested the working hypothesis that cell-cycle control architectures obey the HOT paradigm. Three cell-cycle models were analyzed using monte-carlo sensitivity analysis. Overall state sensitivity coefficients, which quantify the robustness or fragility of a given mechanism, were calculated using a monte-carlo strategy with three different numerical techniques along with multiple parameter perturbation strategies to control for possible numerical and sampling artifacts. Approximately 65% of the mechanisms in the G1/S restriction point were responsible for 95% of the sensitivity, conversely, the G2-DNA damage checkpoint showed a much stronger dependence on a few mechanisms; ∼32% or 13 of 40 mechanisms accounted for 95% of the sensitivity. Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex. Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems. Comparison of the predicted fragile mechanisms with literature and current preclinical and clinical trials suggested a strong correlation between efficacy and fragility. Thus, when taken together, these results support the working hypothesis that cell-cycle control architectures are HOT networks and establish the mathematical estimation and subsequent therapeutic exploitation of fragile mechanisms as a novel strategy for anti-cancer lead generation.

An optimized split-ubiquitin cDNA-library screening system to identify novel interactors of the human Frizzled 1 receptor

The yeast split-ubiquitin system has previously been shown to be suitable to detect protein interactions of membrane proteins and of transcription factors in vivo. Therefore, this technology complements the classical split-transcription factor based yeast two-hybrid system (Y2H). Success or failure of the Y2H depends primarily on the ability to avoid false-negative and false-positive hits that become a limiting factor for the value of the system, especially in large scale proteomic analyses. We provide here a systematic assessment of parameters to help improving the quality of split-ubiquitin cDNA-library screenings. We experimentally defined the optimal 5-fluoroorotic acid (5-FOA) concentration as a key parameter to increase the reproducibility of interactions and, at the same time, to keep non-specific background growth low. Furthermore, we show that the efficacy of the 5-FOA selection is modulated by the plating density of the yeast clones. Moreover, a reporter-specific class of false-positive hits was identified, and a simple phenotypic assay for efficient de-selection was developed. We demonstrate the application of this improved system to identify novel interacting proteins of the human Frizzled 1 receptor. We identified several novel interactors with components of the Wnt-Frizzled signalling pathways and discuss their potential roles as direct mediators of Frizzled receptor signalling. The present work is the first example of a split-ubiquitin interaction screen using an in-situ expressed receptor of the serpentine class, emphasizing the suitability of the described improvements in the screening protocol.

Pat1 contains distinct functional domains that promote P-body assembly and activation of decapping

The control of mRNA degradation and translation are important aspects of gene regulation. Recent results suggest that translation repression and mRNA decapping can be intertwined and involve the formation of a quiescent mRNP, which can accumulate in cytoplasmic foci referred to as P bodies. The Pat1 protein is a key component of this complex and an important activator of decapping, yet little is known about its function. In this work, we analyze Pat1 in Saccharomyces cerevisiae function by deletion and functional analyses. Our results identify two primary functional domains in Pat1: one promoting translation repression and P-body assembly and a second domain promoting mRNA decapping after assembly of the mRNA into a P-body mRNP. In addition, we provide evidence that Pat1 binds RNA and has numerous domain-specific interactions with mRNA decapping factors. These results indicate that Pat1 is an RNA binding protein and a multidomain protein that functions at multiple stages in the process of translation repression and mRNA decapping.

Edc3p and a glutamine/asparagine-rich domain of Lsm4p function in processing body assembly in Saccharomyces cerevisiae

Processing bodies (P-bodies) are cytoplasmic RNA granules that contain translationally repressed messenger ribonucleoproteins (mRNPs) and messenger RNA (mRNA) decay factors. The physical interactions that form the individual mRNPs within P-bodies and how those mRNPs assemble into larger P-bodies are unresolved. We identify direct protein interactions that could contribute to the formation of an mRNP complex that consists of core P-body components. Additionally, we demonstrate that the formation of P-bodies that are visible by light microscopy occurs either through Edc3p, which acts as a scaffold and cross-bridging protein, or via the “prionlike” domain in Lsm4p. Analysis of cells defective in P-body formation indicates that the concentration of translationally repressed mRNPs and decay factors into microscopically visible P-bodies is not necessary for basal control of translation repression and mRNA decay. These results suggest a stepwise model for P-body assembly with the initial formation of a core mRNA–protein complex that then aggregates through multiple specific mechanisms.

A yeast two-hybrid system reconstituting substrate recognition of the von Hippel-Lindau tumor suppressor protein

The von Hippel-Lindau tumor suppressor protein (pVHL) is inactivated in the hereditary cancer syndrome von Hippel-Lindau disease and in the majority of sporadic renal carcinomas. pVHL is the substrate-binding subunit of the CBC^VHL ubiquitin ligase complex that negatively regulates cell growth by promoting the degradation of hypoxia-inducible transcription factor subunits (HIF1/2α). Proteomics-based identification of novel pVHL substrates is hampered by their short half-life and low abundancy in mammalian cells. The usefulness of yeast two-hybrid (Y2H) approaches, on the other hand, has been limited by the failure of pVHL to adopt its native structure and by the absence of prolylhydroxylase activity critical for pVHL substrate recognition. Therefore, we modified the Y2H system to faithfully reconstitute the physical interaction between pVHL and its substrates. Our approach relies on the coexpression of pVHL with the cofactors Elongin B and Elongin C and with HIF1/2α prolylhydroxylases. In a proof-of-principle Y2H screen, we identified the known substrates HIF1/2α and new candidate substrates including diacylglycerol kinase iota, demonstrating that our strategy allows detection of stable interactions between pVHL and otherwise elusive cellular targets. Additional future applications may include structure/function analyses of pVHL-HIF1/2α binding and screens for therapeutically relevant compounds that either stabilize or disrupt this interaction.

The protein network of bacterial motility

Motility is achieved in most bacterial species by the flagellar apparatus. It consists of dozens of different proteins with thousands of individual subunits. The published literature about bacterial chemotaxis and flagella documented 51 protein–protein interactions (PPIs) so far. We have screened whole genome two-hybrid arrays of Treponema pallidum and Campylobacter jejuni for PPIs involving known flagellar proteins and recovered 176 and 140 high-confidence interactions involving 110 and 133 proteins, respectively. To explore the biological relevance of these interactions, we tested an Escherichia coli gene deletion array for motility defects (using swarming assays) and found 159 gene deletion strains to have reduced or no motility. Comparing our interaction data with motility phenotypes from E. coli, Bacillus subtilis, and Helicobacter pylori, we found 23 hitherto uncharacterized proteins involved in motility. Integration of phylogenetic information with our interaction and phenotyping data reveals a conserved core of motility proteins, which appear to have recruited many additional species-specific components over time. Our interaction data also predict 18 110 interactions for 64 flagellated bacteria.

Intracellular protein interaction mapping with FRET hybrids

A quantitative methodology was developed to identify protein interactions in a broad range of cell types by using FRET between fluorescent proteins. Genetic fusions of a target receptor to a FRET acceptor and a large library of candidate peptide ligands to a FRET donor enabled high-throughput optical screening for optimal interaction partners in the cytoplasm of Escherichia coli. Flow cytometric screening identified a panel of peptide ligands capable of recognizing the target receptors in the intracellular environment. For both SH3 and PDZ domain-type target receptors, physiologically meaningful consensus sequences were apparent among the isolated ligands. The relative dissociation constants of interacting partners could be measured directly by using a dilution series of cell lysates containing FRET hybrids, providing a previously undescribed high-throughput approach to rank the affinity of many interaction partners. FRET hybrid interaction screening provides a powerful tool to discover protein ligands in the cellular context with potential applications to a wide variety of eukaryotic cell types.

Expression of CAP2, an APETALA2-family transcription factor from chickpea, enhances growth and tolerance to dehydration and salt stress in transgenic tobacco

The APETALA2 (AP2) domain defines a large family of DNA-binding proteins that play important roles in plant morphology, development, and stress response. We describe isolation and characterization of a gene (CAP2) from chickpea (Cicer arietinum) encoding a novel AP2-family transcription factor. Recombinant CAP2 protein bound specifically to C-repeat/dehydration-responsive element in gel-shift assay and transactivated reporter genes in yeast (Saccharomyces cerevisiae) one-hybrid assay. CAP2 appeared to be a single/low copy intronless gene, and the protein product localized in the nucleus. Transcript level of CAP2 increased by dehydration and by treatment with sodium chloride, abscisic acid, and auxin, but not by treatment with low temperature, salicylic acid, and jasmonic acid. The 35S promoter-driven expression of CAP2 in tobacco (Nicotiana tabacum) caused drastic increase in the leaf cell size, and, thereby, in leaf surface area and number of lateral roots. Transgenic plants demonstrated more tolerance to dehydration and salt stress than the wild-type plants. Transgenic plants expressed higher steady-state transcript levels of abiotic stress-response genes NtERD10B and NtERD10C and auxin-response genes IAA4.2 and IAA2.5. Taken together, our results indicated a mutual interrelation between plant growth-development and abiotic stress-response pathways and a probable involvement of CAP2 in both the signaling pathways.

Novel conserved assembly factor of the bacterial flagellum

TP0658 (FliW) and its orthologs, conserved proteins of unknown function in Treponema pallidum and other species, interact with a C-terminal region of flagellin (FlaB1-3 in T. pallidum; FliC in most other species). Mutants of orthologs in Bacillus subtilis and Campylobacter jejuni (yviF, CJ1075) showed strongly reduced motility. TP0658 stabilizes flagellin in a way similar to FliS, suggesting that TP0658 is a conserved assembly factor for the bacterial flagellum.