Exhaustive benchmarking of the yeast two-hybrid system

Drought-inducible HpbHLH70 enhances drought tolerance and may accelerate floral bud induction in pitaya

Floral bud induction is of great importance for fruit crops, which may substantially affect fruit yield. Previously, a FLOWERING BHLH (FBH) transcription factor gene HpbHLH70 was identified in pitaya (Hylocereus polyrhizus) as subjected to drought stress. In present work, HpbHLH70 was found predominantly activated in pitaya anthers. GUS fusing reporter assay showed its selective activation in anthers and vasculatures of transgenic Arabidopsis. Moreover, HpbHLH70 is drought inducible, which was further supported by the deepened GUS staining under drought condition, indicating a HpbHLH70-mediated crosstalk between drought response and floral bud induction, which partially explained the advanced floral bud induction in pitaya by drought stress. Overexpression of HpbHLH70 in pitaya improved the drought tolerance by enhancing the water-holding capacity and the ROS-scavenging activity. Meanwhile, overexpression of HpbHLH70 in Arabidopsis improved their behaviors under drought stress. Intriguingly, the transgenic Arabidopsis flowered earlier than the wild-type. In addition, HpbHLH70 was verified to heterodimerize with HpbHLH59 and transactivate the floral-bud-induction regulator HpSOC1 via direct binding to the promoter. Overexpression of HpbHLH70 up-regulated the expression of HpSOC1 in pitaya. Collectively, our data uncover that drought-induced HpbHLH70 enhances drought tolerance and may accelerate floral bud induction in pitaya via heterodimerization with HpbHLH59 and transactivation of HpSOC1.

Studies on the PII-PipX-NtcA Regulatory Axis of Cyanobacteria Provide Novel Insights into the Advantages and Limitations of Two-Hybrid Systems for Protein Interactions

Yeast two-hybrid approaches, which are based on fusion proteins that must co-localise to the nucleus to reconstitute the transcriptional activity of GAL4, have greatly contributed to our understanding of the nitrogen interaction network of cyanobacteria, the main hubs of which are the trimeric PII and the monomeric PipX regulators. The bacterial two-hybrid system, based on the reconstitution in the E. coli cytoplasm of the adenylate cyclase of Bordetella pertussis, should provide a relatively faster and presumably more physiological assay for cyanobacterial proteins than the yeast system. Here, we used the bacterial two-hybrid system to gain additional insights into the cyanobacterial PipX interaction network while simultaneously assessing the advantages and limitations of the two most popular two-hybrid systems. A comprehensive mutational analysis of PipX and bacterial two-hybrid assays were performed to compare the outcomes between yeast and bacterial systems. We detected interactions that were previously recorded in the yeast two-hybrid system as negative, as well as a "false positive", the self-interaction of PipX, which is rather an indirect interaction that is dependent on PII homologues from the E. coli host, a result confirmed by Western blot analysis with relevant PipX variants. This is, to our knowledge, the first report of the molecular basis of a false positive in the bacterial two-hybrid system.

Analysing the Cyanobacterial PipX Interaction Network Using NanoBiT Complementation in Synechococcus elongatus PCC7942

The conserved cyanobacterial protein PipX is part of a complex interaction network with regulators involved in essential processes that include metabolic homeostasis and ribosome assembly. Because PipX interactions depend on the relative levels of their different partners and of the effector molecules binding to them, in vivo studies are required to understand the physiological significance and contribution of environmental factors to the regulation of PipX complexes. Here, we have used the NanoBiT complementation system to analyse the regulation of complex formation in Synechococcus elongatus PCC 7942 between PipX and each of its two best-characterized partners, PII and NtcA. Our results confirm previous in vitro analyses on the regulation of PipX-PII and PipX-NtcA complexes by 2-oxoglutarate and on the regulation of PipX-PII by the ATP/ADP ratio, showing the disruption of PipX-NtcA complexes due to increased levels of ADP-bound PII in Synechococcus elongatus. The demonstration of a positive role of PII on PipX-NtcA complexes during their initial response to nitrogen starvation or the impact of a PipX point mutation on the activity of PipX-PII and PipX-NtcA reporters are further indications of the sensitivity of the system. This study reveals additional regulatory complexities in the PipX interaction network, opening a path for future research on cyanobacteria.

The protein interactome of the citrus Huanglongbing pathogen Candidatus Liberibacter asiaticus

The bacterium Candidatus Liberibacter asiaticus (CLas) causes citrus Huanglongbing disease. Our understanding of the pathogenicity and biology of this microorganism remains limited because CLas has not yet been cultivated in artificial media. Its genome is relatively small and encodes approximately 1136 proteins, of which 415 have unknown functions. Here, we use a high-throughput yeast-two-hybrid (Y2H) screen to identify interactions between CLas proteins, thus providing insights into their potential functions. We identify 4245 interactions between 542 proteins, after screening 916 bait and 936 prey proteins. The false positive rate of the Y2H assay is estimated to be 2.9%. Pull-down assays for nine protein-protein interactions (PPIs) likely involved in flagellar function support the robustness of the Y2H results. The average number of PPIs per node in the CLas interactome is 15.6, which is higher than the numbers previously reported for interactomes of free-living bacteria, suggesting that CLas genome reduction has been accompanied by increased protein multi-functionality. We propose potential functions for 171 uncharacterized proteins, based on the PPI results, guilt-by-association analyses, and comparison with data from other bacterial species. We identify 40 hub-node proteins, including quinone oxidoreductase and LysR, which are known to protect other bacteria against oxidative stress and might be important for CLas survival in the phloem. We expect our PPI database to facilitate research on CLas biology and pathogenicity mechanisms.

Molecular characterization of Satsuma mandarin (Citrus unshiu Marc.) VASCULAR PLANT ONE-ZINC FINGER2 (CuVOZ2) interacting with CuFT1 and CuFT3

Shortening the juvenility is a burning issue in breeding fruit trees such as Satsuma mandarin (Citrus unshiu Marc.). Decreasing the breeding period requires a comprehensive understanding of the flowering process in woody plants. Throughout the Arabidopsis flowering system, FLOWERING LOCUS T (FT) interacts with other transcription factors (TFs) and functions as a transmissible floral inducer. In a previous study, a VASCULAR PLANT ONE-ZINC FINGER1 (VOZ1)-like TF from the Satsuma mandarin, CuVOZ1, showed protein-protein interaction with two citrus FTs in a yeast two-hybrid (Y2H) system and precocious flowering in Arabidopsis. In this study, another VOZ, CuVOZ2, was isolated from the Satsuma mandarin 'Aoshima' and protein-protein interaction was confirmed between CuVOZ2 and CuFTs. No apical meristem (NAM) and zinc coordination motifs were identified within the N-terminal of CuVOZ2. Docking simulation predicted that interactions between CuVOZ2 and CuFTs might occur in domain B of CuVOZ2, which contains a zinc finger motif. According to docking predictions, the distances between the amino acid residues involved ranged from 1.09 to 4.37 Å, indicating weak Van der Waals forces in the interaction. Cys216, Cys221, Cys235, and His239 in CuVOZ2 were suggested to bond with a Zn2+ in the Zn coordination motif. Ectopic expression of 35SΩ:CuVOZ2 in Arabidopsis affected the flowering time, length of inflorescence and internode, and number of siliques, suggesting that CuVOZ2 might regulate both vegetative and reproductive development, act as a trigger for early flowering, and be involved in the elongation of inflorescence possibly in a slightly different way than CuVOZ1.

What Has Genomics Taught An Evolutionary Biologist?

Genomics, an interdisciplinary field of biology on the structure, function, and evolution of genomes, has revolutionized many subdisciplines of life sciences, including my field of evolutionary biology, by supplying huge data, bringing high-throughput technologies, and offering a new approach to biology. In this review, I describe what I have learned from genomics and highlight the fundamental knowledge and mechanistic insights gained. I focus on three broad topics that are central to evolutionary biology and beyond-variation, interaction, and selection-and use primarily my own research and study subjects as examples. In the next decade or two, I expect that the most important contributions of genomics to evolutionary biology will be to provide genome sequences of nearly all known species on Earth, facilitate high-throughput phenotyping of natural variants and systematically constructed mutants for mapping genotype-phenotype-fitness landscapes, and assist the determination of causality in evolutionary processes using experimental evolution.

Yeast Two-Hybrid System for Mapping Novel Dengue Protein Interactions

Yeast two-hybrid (Y2H) systems are one of the principal choices for identifying novel binary protein-protein interactions (PPIs). Since its development, it has contributed for the discovery of several PPIs between pathogens and host, allowing not only a comprehensive look at the disease pathogenesis but also for therapeutic strategies. Identification of viral-host PPIs that impact on viral replication and pathogenesis can lead to new advances in antiviral therapies such as the development of drug candidates and vaccine design. In this chapter, we revise the Y2H key parameters necessary for screening PPIs and discuss the possible approaches for using this technique to identify novel dengue-host protein interactions.

JUPPI: A Multi-Level Feature Based Method for PPI Prediction and a Refined Strategy for Performance Assessment

Over the years, several methods have been proposed for the computational PPI prediction with different performance evaluation strategies. While attempting to benchmark performance scores, most of these methods often suffer with ill-treated cross-validation strategies, adhoc selection of positive/negative samples etc. To address these issues, in our proposed multi-level feature based PPI prediction approach (JUPPI), using sequence, domain and GO information as features, a refined evaluation strategy has been introduced. During the evaluation process, we first extract high quality negative data using three-stage filtering, and then introduce a pair-input based cross validation strategy with three difficulty levels for test-set predictions. Our proposed evaluation strategy reduces the component-level overlapping issue in test sets. Performance of JUPPI is compared with those of the state-of-the-art approaches in this domain and tested on six independent PPI datasets. In almost all the datasets, JUPPI outperforms the state-of-the-art not only at human proteome level for PPI prediction, but also for prediction of interactors for intrinsic disordered human proteins. https://figshare.com/projects/JUPPI_A_Multi-level_Feature_Based_Method_for_PPI_Prediction_and_a_Refined_Strategy_for_Performance_Assessment/81656 JUPPI tool and the developed datasets (JUPPId) are available in public domain for academic use along with supplementary materials, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TCBB.2020.3004970.

A reference map of the human binary protein interactome

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships^1,2. Here, we present a human “all-by-all” reference interactome map of human binary protein interactions, or “HuRI”. With ~53,000 high-quality protein-protein interactions (PPIs), HuRI has approximately four times more such interactions than high-quality curated interactions from small-scale studies. Integrating HuRI with genome³, transcriptome⁴, and proteome⁵ data enables the study of cellular function within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying specific subcellular roles of PPIs. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI represents a systematic proteome-wide reference linking genomic variation to phenotypic outcomes.

An abscisic acid-responsive protein interaction network for sucrose non-fermenting related kinase1 in abiotic stress response

Yeast Snf1 (Sucrose non-fermenting1), mammalian AMPK (5′ AMP-activated protein kinase) and plant SnRK1 (Snf1-Related Kinase1) are conserved heterotrimeric kinase complexes that re-establish energy homeostasis following stress. The hormone abscisic acid (ABA) plays a crucial role in plant stress response. Activation of SnRK1 or ABA signaling results in overlapping transcriptional changes, suggesting these stress pathways share common targets. To investigate how SnRK1 and ABA interact during stress response in Arabidopsis thaliana, we screened the SnRK1 complex by yeast two-hybrid against a library of proteins encoded by 258 ABA-regulated genes. Here, we identify 125 SnRK1- interacting proteins (SnIPs). Network analysis indicates that a subset of SnIPs form signaling modules in response to abiotic stress. Functional studies show the involvement of SnRK1 and select SnIPs in abiotic stress responses. This targeted study uncovers the largest set of SnRK1 interactors, which can be used to further characterize SnRK1 role in plant survival under stress.

Carianopol et al. construct a detailed protein interaction network for the SnRK1 kinase complex to investigate the interaction of SnRK1 and ABA during stress response. They identify 125 proteins that interact with SnRK1, which can be used further to characterise the role of SnRK1 in plant survival under stress.

Increased talin-vinculin spatial proximities in livers in response to spotted fever group rickettsial and Ebola virus infections

Talin and vinculin, both actin-cytoskeleton-related proteins, have been documented to participate in establishing bacterial infections, respectively, as the adapter protein to mediate cytoskeleton-driven dynamics of the plasma membrane. However, little is known regarding the potential role of the talin-vinculin complex during spotted fever group rickettsial and Ebola virus infections, two dreadful infectious diseases in humans. Many functional properties of proteins are determined by their participation in protein-protein complexes, in a temporal and/or spatial manner. To resolve the limitation of application in using mouse primary antibodies on archival, multiple formalin-fixed mouse tissue samples, which were collected from experiments requiring high biocontainment, we developed a practical strategic proximity ligation assay (PLA) capable of employing one primary antibody raised in mouse to probe talin-vinculin spatial proximal complex in mouse tissue. We observed an increase of talin-vinculin spatial proximities in the livers of spotted fever Rickettsia australis or Ebola virus-infected mice when compared with mock mice. Furthermore, using EPAC1-knockout mice, we found that deletion of EPAC1 could suppress the formation of spatial proximal complex of talin-vinculin in rickettsial infections. In addition, we observed increased colocalization between spatial proximity of talin-vinculin and filamentous actin-specific phalloidin staining in single survival mouse from an ordinarily lethal dose of rickettsial or Ebola virus infection. These findings may help to delineate a fresh insight into the mechanisms underlying liver specific pathogenesis during infection with spotted fever rickettsia or Ebola virus in the mouse model.

Maximizing binary interactome mapping with a minimal number of assays

Complementary assays are required to comprehensively map complex biological entities such as genomes, proteomes and interactome networks. However, how various assays can be optimally combined to approach completeness while maintaining high precision often remains unclear. Here, we propose a framework for binary protein-protein interaction (PPI) mapping based on optimally combining assays and/or assay versions to maximize detection of true positive interactions, while avoiding detection of random protein pairs. We have engineered a novel NanoLuc two-hybrid (N2H) system that integrates 12 different versions, differing by protein expression systems and tagging configurations. The resulting union of N2H versions recovers as many PPIs as 10 distinct assays combined. Thus, to further improve PPI mapping, developing alternative versions of existing assays might be as productive as designing completely new assays. Our findings should be applicable to systematic mapping of other biological landscapes.

Caenorhabditis elegans sperm membrane protein interactome

The interaction and organization of proteins in the sperm membrane are important for all aspects of sperm function. We have determined the interactions between 12 known mutationally defined and cloned sperm membrane proteins in a model system for reproduction, the nematode Caenorhabditis elegans. Identification of the interactions between sperm membrane proteins will improve our understanding of and ability to characterize defects in sperm function. To identify interacting proteins, we conducted a split-ubiquitin membrane yeast two-hybrid analysis of gene products identified through genetic screens that are necessary for sperm function and predicted to encode transmembrane proteins. Our analysis revealed novel interactions between sperm membrane proteins known to have roles in spermatogenesis, spermiogenesis, and fertilization. For example, we found that a protein known to play a role in sperm function during fertilization, SPE-38 (a predicted four pass transmembrane protein), interacts with proteins necessary for spermiogenesis and spermatogenesis and could serve as a central organizing protein in the plasma membrane. These novel interaction pairings will provide the foundation for investigating previously unrealized membrane protein interactions during spermatogenesis, spermiogenesis, and sperm function during fertilization.

Discovering cellular protein-protein interactions: Technological strategies and opportunities

The analysis of protein interaction networks is one of the key challenges in the study of biology. It connects genotypes to phenotypes, and disruption often leads to diseases. Hence, many technologies have been developed to study protein-protein interactions (PPIs) in a cellular context. The expansion of the PPI technology toolbox however complicates the selection of optimal approaches for diverse biological questions. This review gives an overview of the binary and co-complex technologies, with the former evaluating the interaction of two co-expressed genetically tagged proteins, and the latter only needing the expression of a single tagged protein or no tagged proteins at all. Mass spectrometry is crucial for some binary and all co-complex technologies. After the detailed description of the different technologies, the review compares their unique specifications, advantages, disadvantages, and applicability, while highlighting opportunities for further advancements.

Protein-protein interactions of human viruses

Viruses infect their human hosts by a series of interactions between viral and host proteins, indicating that detailed knowledge of such virus-host interaction interfaces are critical for our understanding of viral infection mechanisms, disease etiology and the development of new drugs. In this review, we primarily survey human host-virus interaction data that are available from public databases following the standardized PSI-MS format. Notably, available host-virus protein interaction information is strongly biased toward a small number of virus families including herpesviridae, papillomaviridae, orthomyxoviridae and retroviridae. While we explore the reliability and relevance of these protein interactions we also survey the current knowledge about viruses functional and topological targets. Furthermore, we assess emerging frontiers of host-virus protein interaction research, focusing on protein interaction interfaces of hosts that are infected by different viruses and viruses that infect multiple hosts. Finally, we cover the current status of research that investigates the relationships of virus-targeted host proteins to other comorbidities as well as the influence of host-virus protein interactions on human metabolism.

LuTHy: a double-readout bioluminescence-based two-hybrid technology for quantitative mapping of protein-protein interactions in mammalian cells

Information on protein-protein interactions (PPIs) is of critical importance for studying complex biological systems and developing therapeutic strategies. Here, we present a double-readout bioluminescence-based two-hybrid technology, termed LuTHy, which provides two quantitative scores in one experimental procedure when testing binary interactions. PPIs are first monitored in cells by quantification of bioluminescence resonance energy transfer (BRET) and, following cell lysis, are again quantitatively assessed by luminescence-based co-precipitation (LuC). The double-readout procedure detects interactions with higher sensitivity than traditional single-readout methods and is broadly applicable, for example, for detecting the effects of small molecules or disease-causing mutations on PPIs. Applying LuTHy in a focused screen, we identified 42 interactions for the presynaptic chaperone CSPα, causative to adult-onset neuronal ceroid lipofuscinosis (ANCL), a progressive neurodegenerative disease. Nearly 50% of PPIs were found to be affected when studying the effect of the disease-causing missense mutations L115R and ∆L116 in CSPα with LuTHy. Our study presents a robust, sensitive research tool with high utility for investigating the molecular mechanisms by which disease-associated mutations impair protein activity in biological systems.

Analyses of Protein Interaction Networks Using Computational Tools

The knowledge of protein-protein interactions (PPIs) and PPI networks (PPINs) is the key to starting to understand the biological processes inside the cell. Many computational tools have been designed to help explore PPIs and PPINs, such as those for interaction detection, reliability assessment and interaction network construction. Here, the application of computational tools is reviewed from three perspectives: PPI database construction, PPI prediction, and interaction network construction and analysis. This overview will provide researchers guidance on choosing appropriate methods for exploring PPIs.

KISS: A Mammalian Two-Hybrid Method for In Situ Analysis of Protein-Protein Interactions

KISS (KInase Substrate Sensor) is a recently developed two-hybrid technology that allows in situ analysis of protein-protein interactions in intact mammalian cells. In this method, which is derived from MAPPIT (mammalian protein-protein interaction trap), the bait protein is coupled to the kinase domain of TYK2, while the prey protein is fused to a fragment of the gp130 cytokine receptor chain. Bait and prey interaction leads to phosphorylation of the gp130 anchor by TYK2, followed by recruitment and activation of STAT3, resulting in transcription of a STAT3-dependent reporter system. This approach enables the identification of interactions between proteins, including transmembrane and cytosolic proteins, and their modulation in response to physiological or pharmacological challenges. Here, we describe a detailed step-by-step protocol for the detection of an interaction between two proteins of interest using KISS.

Making the Right Choice: Critical Parameters of the Y2H Systems

Two-hybrid methods remain among the most preferred choices for detecting protein-protein interactions (PPIs) and much of the PPI data in databases have been produced using yeast two-hybrid (Y2H) screens. The Y2H methods are extensively used to detect PPIs because of their scalability and accessibility. Several variants of Y2H methods have been developed and used by different research groups, increasing the accessibility of these methods and their applications in detecting different types of PPIs. However, the availability of variations on the same core methodology emphasizes the need to have a systematic comparison of available Y2H methods in the context of their applicability, coverage and efficiency. In this chapter, we discuss the key parameters of Y2H methods, namely proteins of interest, vectors, libraries, screening strategies, data analysis, and provide a flowchart that should help to decide which Y2H strategy is most appropriate for a protein interaction screen.

Virus-host protein-protein interactions of mycobacteriophage Giles

Mycobacteriophage are viruses that infect mycobacteria. More than 1,400 mycobacteriophage genomes have been sequenced, coding for over one hundred thousand proteins of unknown functions. Here we investigate mycobacteriophage Giles-host protein-protein interactions (PPIs) using yeast two-hybrid screening (Y2H). A total of 25 reproducible PPIs were found for a selected set of 10 Giles proteins, including a putative virion assembly protein (gp17), the phage integrase (gp29), the endolysin (gp31), the phage repressor (gp47), and six proteins of unknown function (gp34, gp35, gp54, gp56, gp64, and gp65). We note that overexpression of the proteins is toxic to M. smegmatis, although whether this toxicity and the associated changes in cellular morphology are related to the putative interactions revealed in the Y2H screen is unclear.

Mechanisms of action of Coxiella burnetii effectors inferred from host-pathogen protein interactions

Coxiella burnetii is an obligate Gram-negative intracellular pathogen and the etiological agent of Q fever. Successful infection requires a functional Type IV secretion system, which translocates more than 100 effector proteins into the host cytosol to establish the infection, restructure the intracellular host environment, and create a parasitophorous vacuole where the replicating bacteria reside. We used yeast two-hybrid (Y2H) screening of 33 selected C. burnetii effectors against whole genome human and murine proteome libraries to generate a map of potential host-pathogen protein-protein interactions (PPIs). We detected 273 unique interactions between 20 pathogen and 247 human proteins, and 157 between 17 pathogen and 137 murine proteins. We used orthology to combine the data and create a single host-pathogen interaction network containing 415 unique interactions between 25 C. burnetii and 363 human proteins. We further performed complementary pairwise Y2H testing of 43 out of 91 C. burnetii-human interactions involving five pathogen proteins. We used the combined data to 1) perform enrichment analyses of target host cellular processes and pathways, 2) examine effectors with known infection phenotypes, and 3) infer potential mechanisms of action for four effectors with uncharacterized functions. The host-pathogen interaction profiles supported known Coxiella phenotypes, such as adapting cell morphology through cytoskeletal re-arrangements, protein processing and trafficking, organelle generation, cholesterol processing, innate immune modulation, and interactions with the ubiquitin and proteasome pathways. The generated dataset of PPIs-the largest collection of unbiased Coxiella host-pathogen interactions to date-represents a rich source of information with respect to secreted pathogen effector proteins and their interactions with human host proteins.

High-throughput characterization of protein-protein interactions by reprogramming yeast mating

High-throughput methods for screening protein-protein interactions enable the rapid characterization of engineered binding proteins and interaction networks. While existing approaches are powerful, none allow quantitative library-on-library characterization of protein interactions in a modifiable extracellular environment. Here, we show that sexual agglutination of Saccharomyces cerevisiae can be reprogrammed to link interaction strength with mating efficiency using synthetic agglutination (SynAg). Validation of SynAg with 89 previously characterized interactions shows a log-linear relationship between mating efficiency and protein binding strength for interactions with K_ds ranging from below 500 pM to above 300 μM. Using induced chromosomal translocation to pair barcodes representing binding proteins, thousands of distinct interactions can be screened in a single pot. We demonstrate the ability to characterize protein interaction networks in a modifiable environment by introducing a soluble peptide that selectively disrupts a subset of interactions in a representative network by up to 800-fold. SynAg enables the high-throughput, quantitative characterization of protein-protein interaction networks in a fully defined extracellular environment at a library-on-library scale.

The Plasmodium falciparum exported protein PF3D7_0402000 binds to erythrocyte ankyrin and band 4.1

Plasmodium falciparum extensively modifies the infected red blood cell (RBC), resulting in changes in deformability, shape and surface properties. These alterations suggest that the RBC cytoskeleton is a major target for modification during infection. However, the molecular mechanisms leading to these changes are largely unknown. To begin to address this question, we screened for exported P. falciparum proteins that bound to the erythrocyte cytoskeleton proteins ankyrin 1 (ANK1) and band 4.1 (4.1R), which form critical interactions with other cytoskeletal proteins that contribute to the deformability and stability of RBCs. Yeast two-hybrid screens with ANK1 and 4.1R identified eight interactions with P. falciparum exported proteins, including an interaction between 4.1R and PF3D7_0402000 (PFD0090c). This interaction was first identified in a large-scale screen (Vignali et al., Malaria J, 7:211, 2008), which also reported an interaction between PF3D7_0402000 and ANK1. We confirmed the interactions of PF3D7_0402000 with 4.1R and ANK1 in pair-wise yeast two-hybrid and co-precipitation assays. In both cases, an intact PHIST domain in PF3D7_0402000 was required for binding. Complex purification followed by mass spectrometry analysis provided additional support for the interaction of PF3D7_0402000 with ANK1 and 4.1R. RBC ghost cells loaded with maltose-binding protein (MBP)-PF3D7_0402000 passed through a metal microsphere column less efficiently than mock- or MBP-loaded controls, consistent with an effect of PF3D7_0402000 on RBC rigidity or membrane stability. This study confirmed the interaction of PF3D7_0402000 with 4.1R in multiple independent assays, provided the first evidence that PF3D7_0402000 also binds to ANK1, and suggested that PF3D7_0402000 affects deformability or membrane stability of uninfected RBC ghosts.

Multiplexed gene control reveals rapid mRNA turnover

The rates of mRNA synthesis and decay determine the mRNA expression level. The two processes are under coordinated control, which makes the measurements of these rates challenging, as evidenced by the low correlation among the methods of measurement of RNA half-lives. We developed a minimally invasive method, multiplexed gene control, to shut off expression of genes with controllable synthetic promoters. The method was validated by measuring the ratios of the nascent to mature mRNA molecules and by measuring the half-life with endogenous promoters that can be controlled naturally or through inserting short sequences that impart repressibility. The measured mRNA half-lives correlated highly with those obtained with the metabolic pulse-labeling method in yeast. However, mRNA degradation was considerably faster in comparison to previous estimates, with a median half-life of around 2 min. The half-life permits the estimation of promoter-dependent and promoter-independent transcription rates. The dynamical range of the promoter-independent transcription rates was larger than that of the mRNA half-lives. The rapid mRNA turnover and the broad adjustability of promoter-independent transcription rates are expected to have a major impact on stochastic gene expression and gene network behavior.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions

The functions of roughly a third of all proteins in Streptococcus pneumoniae, a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein's function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae. We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae, the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins.

Bacterial protein meta-interactomes predict cross-species interactions and protein function

Background

Protein-protein interactions (PPIs) can offer compelling evidence for protein function, especially when viewed in the context of proteome-wide interactomes. Bacteria have been popular subjects of interactome studies: more than six different bacterial species have been the subjects of comprehensive interactome studies while several more have had substantial segments of their proteomes screened for interactions. The protein interactomes of several bacterial species have been completed, including several from prominent human pathogens. The availability of interactome data has brought challenges, as these large data sets are difficult to compare across species, limiting their usefulness for broad studies of microbial genetics and evolution.

Results

In this study, we use more than 52,000 unique protein-protein interactions (PPIs) across 349 different bacterial species and strains to determine their conservation across data sets and taxonomic groups. When proteins are collapsed into orthologous groups (OGs) the resulting meta-interactome still includes more than 43,000 interactions, about 14,000 of which involve proteins of unknown function. While conserved interactions provide support for protein function in their respective species data, we found only 429 PPIs (~1% of the available data) conserved in two or more species, rendering any cross-species interactome comparison immediately useful. The meta-interactome serves as a model for predicting interactions, protein functions, and even full interactome sizes for species with limited to no experimentally observed PPI, including Bacillus subtilis and Salmonella enterica which are predicted to have up to 18,000 and 31,000 PPIs, respectively.

Conclusions

In the course of this work, we have assembled cross-species interactome comparisons that will allow interactomics researchers to anticipate the structures of yet-unexplored microbial interactomes and to focus on well-conserved yet uncharacterized interactors for further study. Such conserved interactions should provide evidence for important but yet-uncharacterized aspects of bacterial physiology and may provide targets for anti-microbial therapies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1585-0) contains supplementary material, which is available to authorized users.

Proteome-Scale Human Interactomics

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life.

A Comparison of Two-Hybrid Approaches for Detecting Protein-Protein Interactions

Two-hybrid systems are one of the most popular, preferred, cost effective, and scalable in vivo genetic approaches for screening protein-protein interactions. A number of variants of yeast and bacterial two-hybrid systems exist, rendering them ideal for modern, flexible proteomics-driven studies. For mapping protein interactions at genome scales (that is, constructing an interactome), the yeast two-hybrid system has been extensively tested and is preferred over bacterial two-hybrid systems, given that users have created more resources such as a variety of vectors and other modifications. Each system has its own advantages and limitations and thus needs to be compared directly. For instance, the bacterial two-hybrid method seems a better fit than the yeast two-hybrid system to screen membrane-associated proteins. In this chapter, we provide detailed protocols for yeast and bacterial two-hybrid systems as well as a comparison of outcomes for each approach using our own and published data.

Integrative methods for analyzing big data in precision medicine

We provide an overview of recent developments in big data analyses in the context of precision medicine and health informatics. With the advance in technologies capturing molecular and medical data, we entered the area of "Big Data" in biology and medicine. These data offer many opportunities to advance precision medicine. We outline key challenges in precision medicine and present recent advances in data integration-based methods to uncover personalized information from big data produced by various omics studies. We survey recent integrative methods for disease subtyping, biomarkers discovery, and drug repurposing, and list the tools that are available to domain scientists. Given the ever-growing nature of these big data, we highlight key issues that big data integration methods will face.

Harnessing molecular motors for nanoscale pulldown in live cells

Nanoscale pulldown (NanoSPD) miniaturizes the concept of affinity pulldown to detect protein–protein interactions in live cells. NanoSPD hijacks the myosin-based intracellular trafficking machinery to assess interactions under physiological buffer conditions and is microscopy-based, allowing for sensitive detection and quantification.

Protein–protein interactions (PPIs) regulate assembly of macromolecular complexes, yet remain challenging to study within the native cytoplasm where they normally exert their biological effect. Here we miniaturize the concept of affinity pulldown, a gold-standard in vitro PPI interrogation technique, to perform nanoscale pulldowns (NanoSPDs) within living cells. NanoSPD hijacks the normal process of intracellular trafficking by myosin motors to forcibly pull fluorescently tagged protein complexes along filopodial actin filaments. Using dual-color total internal reflection fluorescence microscopy, we demonstrate complex formation by showing that bait and prey molecules are simultaneously trafficked and actively concentrated into a nanoscopic volume at the tips of filopodia. The resulting molecular traffic jams at filopodial tips amplify fluorescence intensities and allow PPIs to be interrogated using standard epifluorescence microscopy. A rigorous quantification framework and software tool are provided to statistically evaluate NanoSPD data sets. We demonstrate the capabilities of NanoSPD for a range of nuclear and cytoplasmic PPIs implicated in human deafness, in addition to dissecting these interactions using domain mapping and mutagenesis experiments. The NanoSPD methodology is extensible for use with other fluorescent molecules, in addition to proteins, and the platform can be easily scaled for high-throughput applications.

HVint: A Strategy for Identifying Novel Protein-Protein Interactions in Herpes Simplex Virus Type 1

Human herpesviruses are widespread human pathogens with a remarkable impact on worldwide public health. Despite intense decades of research, the molecular details in many aspects of their function remain to be fully characterized. To unravel the details of how these viruses operate, a thorough understanding of the relationships between the involved components is key. Here, we present HVint, a novel protein-protein intraviral interaction resource for herpes simplex virus type 1 (HSV-1) integrating data from five external sources. To assess each interaction, we used a scoring scheme that takes into consideration aspects such as the type of detection method and the number of lines of evidence. The coverage of the initial interactome was further increased using evolutionary information, by importing interactions reported for other human herpesviruses. These latter interactions constitute, therefore, computational predictions for potential novel interactions in HSV-1. An independent experimental analysis was performed to confirm a subset of our predicted interactions. This subset covers proteins that contribute to nuclear egress and primary envelopment events, including VP26, pUL31, pUL40, and the recently characterized pUL32 and pUL21. Our findings support a coordinated crosstalk between VP26 and proteins such as pUL31, pUS9, and the CSVC complex, contributing to the development of a model describing the nuclear egress and primary envelopment pathways of newly synthesized HSV-1 capsids. The results are also consistent with recent findings on the involvement of pUL32 in capsid maturation and early tegumentation events. Further, they open the door to new hypotheses on virus-specific regulators of pUS9-dependent transport. To make this repository of interactions readily accessible for the scientific community, we also developed a user-friendly and interactive web interface. Our approach demonstrates the power of computational predictions to assist in the design of targeted experiments for the discovery of novel protein-protein interactions.

The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages

Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets.

Probing protein interactions in living mammalian cells on a microtubule bench

Microtubules are μm-long cylinders of about 25 nm in diameter which are present in the cytoplasm of eukaryotic cells. Here, we have developed a new method which uses these cylindrical structures as platforms to detect protein interactions in cells. The principle is simple: a protein of interest used as bait is brought to microtubules by fusing it to Tau, a microtubule-associated protein. The presence of a protein prey on microtubules then reveals an interaction between bait and prey. This method requires only a conventional optical microscope and straightforward fluorescence image analysis for detection and quantification of protein interactions. To test the reliability of this detection scheme, we used it to probe the interactions among three mRNA-binding proteins in both fixed and living cells and compared the results to those obtained by pull-down assays. We also tested whether the molecular interactions of Cx43, a membrane protein, can be investigated with this system. Altogether, the results indicate that microtubules can be used as platforms to detect protein interactions in mammalian cells, which should provide a basis for investigating pathogenic protein interactions involved in human diseases.

The Hepatitis E virus intraviral interactome

Hepatitis E virus (HEV) is an emerging virus causing epidemic acute hepatitis in developing countries as well as sporadic cases in industrialized countries. The life cycle of HEV is still poorly understood and the lack of efficient cell culture systems and animal models are the principal limitations for a detailed study of the viral replication cycle. Here we exhaustively examine all possible intraviral protein-protein interactions (PPIs) of HEV by systematic Yeast two-hybrid (Y2H) and LuMPIS screens, providing a basis for studying the function of these proteins in the viral replication cycle. Key PPIs correlate with the already published HEV 3D structure. Furthermore, we report 20 novel PPIs including the homodimerization of the RNA dependent RNA polymerase (RdRp), the self-interaction of the papain like protease, and ORF3 interactions with the papain-like protease and putative replicase components: RdRp, methylase and helicase. Furthermore, we determined the dissociation constant (K_d) of ORF3 interactions with the viral helicase, papain-like protease and methylase, which suggest a regulatory function for ORF3 in orchestrating the formation of the replicase complex. These interactions may represent new targets for antiviral drugs.

Mapping the Protein-Protein Interactome Networks Using Yeast Two-Hybrid Screens

The yeast two-hybrid system (Y2H) is a powerful method to identify binary protein-protein interactions in vivo. Here we describe Y2H screening strategies that use defined libraries of open reading frames (ORFs) and cDNA libraries. The array-based Y2H system is well suited for interactome studies of small genomes with an existing ORFeome clones preferentially in a recombination based cloning system. For large genomes, pooled library screening followed by Y2H pairwise retests may be more efficient in terms of time and resources, but multiple sampling is necessary to ensure comprehensive screening. While the Y2H false positives can be efficiently reduced by using built-in controls, retesting, and evaluation of background activation; implementing the multiple variants of the Y2H vector systems is essential to reduce the false negatives and ensure comprehensive coverage of an interactome.

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.

Discovery of a novel ligand that modulates the protein-protein interactions of the AAA+ superfamily oncoprotein reptin

Developing approaches to discover protein-protein interactions (PPIs) remains a fundamental challenge. A chemical biology platform is applied here to identify novel PPIs for the AAA+ superfamily oncoprotein reptin. An in silico screen coupled with chemical optimization provided Liddean, a nucleotide-mimetic which modulates reptin's oligomerization status, protein-binding activity and global conformation. Combinatorial peptide phage library screening of Liddean-bound reptin with next generation sequencing identified interaction motifs including a novel reptin docking site on the p53 tumor suppressor protein. Proximity ligation assays demonstrated that endogenous reptin forms a predominantly cytoplasmic complex with its paralog pontin in cancer cells and Liddean promotes a shift of this complex to the nucleus. An emerging view of PPIs in higher eukaryotes is that they occur through a striking diversity of linear peptide motifs. The discovery of a compound that alters reptin's protein interaction landscape potentially leads to novel avenues for therapeutic development.

The yeast two-hybrid system: a tool for mapping protein-protein interactions

Virtually all processes in living cells are dependent on protein-protein interactions (PPIs). Understanding PPI networks is thus essential for molecular biology and disease research. One powerful genetic system for mapping PPIs both at a small scale and in a high-throughput manner is the yeast two-hybrid (Y2H) screen. In Y2H screening, PPIs are detected through the activation of reporter genes responding to a reconstituted transcription factor. In this introduction, we describe library- and array-based Y2H methods and explain their basic theory. We also include the rationale behind different Y2H approaches and strategies for optimizing results.

Mapping protein-protein interactions using yeast two-hybrid assays

Yeast two-hybrid (Y2H) screens are an efficient system for mapping protein-protein interactions and whole interactomes. The screens can be performed using random libraries or collections of defined open reading frames (ORFs) called ORFeomes. This protocol describes both library and array-based Y2H screening, with an emphasis on array-based assays. Array-based Y2H is commonly used to test a number of "prey" proteins for interactions with a single "bait" (target) protein or pool of proteins. The advantage of this approach is the direct identification of interacting protein pairs without further downstream experiments: The identity of the preys is known and does not require further confirmation. In contrast, constructing and screening a random prey library requires identification of individual prey clones and systematic retesting. Retesting is typically performed in an array format.

A visual review of the interactome of LRRK2: Using deep-curated molecular interaction data to represent biology

Molecular interaction databases are essential resources that enable access to a wealth of information on associations between proteins and other biomolecules. Network graphs generated from these data provide an understanding of the relationships between different proteins in the cell, and network analysis has become a widespread tool supporting –omics analysis. Meaningfully representing this information remains far from trivial and different databases strive to provide users with detailed records capturing the experimental details behind each piece of interaction evidence. A targeted curation approach is necessary to transfer published data generated by primarily low-throughput techniques into interaction databases. In this review we present an example highlighting the value of both targeted curation and the subsequent effective visualization of detailed features of manually curated interaction information. We have curated interactions involving LRRK2, a protein of largely unknown function linked to familial forms of Parkinson's disease, and hosted the data in the IntAct database. This LRRK2-specific dataset was then used to produce different visualization examples highlighting different aspects of the data: the level of confidence in the interaction based on orthogonal evidence, those interactions found under close-to-native conditions, and the enzyme–substrate relationships in different in vitro enzymatic assays. Finally, pathway annotation taken from the Reactome database was overlaid on top of interaction networks to bring biological functional context to interaction maps.

The EHEC-host interactome reveals novel targets for the translocated intimin receptor

Enterohemorrhagic E. coli (EHEC) manipulate their human host through at least 39 effector proteins which hijack host processes through direct protein-protein interactions (PPIs). To identify their protein targets in the host cells, we performed yeast two-hybrid screens, allowing us to find 48 high-confidence protein-protein interactions between 15 EHEC effectors and 47 human host proteins. In comparison to other bacteria and viruses we found that EHEC effectors bind more frequently to hub proteins as well as to proteins that participate in a higher number of protein complexes. The data set includes six new interactions that involve the translocated intimin receptor (TIR), namely HPCAL1, HPCAL4, NCALD, ARRB1, PDE6D, and STK16. We compared these TIR interactions in EHEC and enteropathogenic E. coli (EPEC) and found that five interactions were conserved. Notably, the conserved interactions included those of serine/threonine kinase 16 (STK16), hippocalcin-like 1 (HPCAL1) as well as neurocalcin-delta (NCALD). These proteins co-localize with the infection sites of EPEC. Furthermore, our results suggest putative functions of poorly characterized effectors (EspJ, EspY1). In particular, we observed that EspJ is connected to the microtubule system while EspY1 appears to be involved in apoptosis/cell cycle regulation.

Kinase Substrate Sensor (KISS), a mammalian in situ protein interaction sensor

Probably every cellular process is governed by protein-protein interaction (PPIs), which are often highly dynamic in nature being modulated by in- or external stimuli. Here we present KISS, for KInase Substrate Sensor, a mammalian two-hybrid approach designed to map intracellular PPIs and some of the dynamic features they exhibit. Benchmarking experiments indicate that in terms of sensitivity and specificity KISS is on par with other binary protein interaction technologies while being complementary with regard to the subset of PPIs it is able to detect. We used KISS to evaluate interactions between different types of proteins, including transmembrane proteins, expressed at their native subcellular location. In situ analysis of endoplasmic reticulum stress-induced clustering of the endoplasmic reticulum stress sensor ERN1 and ligand-dependent β-arrestin recruitment to GPCRs illustrated the method's potential to study functional PPI modulation in complex cellular processes. Exploring its use as a tool for in cell evaluation of pharmacological interference with PPIs, we showed that reported effects of known GPCR antagonists and PPI inhibitors are properly recapitulated. In a three-hybrid setup, KISS was able to map interactions between small molecules and proteins. Taken together, we established KISS as a sensitive approach for in situ analysis of protein interactions and their modulation in a changing cellular context or in response to pharmacological challenges.

A mesoscale abscisic acid hormone interactome reveals a dynamic signaling landscape in Arabidopsis

The sesquiterpenoid abscisic acid (ABA) mediates an assortment of responses across a variety of kingdoms including both higher plants and animals. In plants, where most is known, a linear core ABA signaling pathway has been identified. However, the complexity of ABA-dependent gene expression suggests that ABA functions through an intricate network. Here, using systems biology approaches that focused on genes transcriptionally regulated by ABA, we defined an ABA signaling network of over 500 interactions among 138 proteins. This map greatly expanded ABA core signaling but was still manageable for systematic analysis. For example, functional analysis was used to identify an ABA module centered on two sucrose nonfermenting (SNF)-like kinases. We also used coexpression analysis of interacting partners within the network to uncover dynamic subnetwork structures in response to different abiotic stresses. This comprehensive ABA resource allows for application of approaches to understanding ABA functions in higher plants.

Chromosome segregation proteins of Vibrio cholerae as transcription regulators

ABSTRACT Bacterial ParA and ParB proteins are best known for their contribution to plasmid and chromosome segregation, but they may also contribute to other cell functions. In segregation, ParA interacts with ParB, which binds to parS centromere-analogous sites. In transcription, plasmid Par proteins can serve as repressors by specifically binding to their own promoters and, additionally, in the case of ParB, by spreading from a parS site to nearby promoters. Here, we have asked whether chromosomal Par proteins can likewise control transcription. Analysis of genome-wide ParB1 binding in Vibrio cholerae revealed preferential binding to the three known parS1 sites and limited spreading of ParB1 beyond the parS1 sites. Comparison of wild-type transcriptomes with those of ΔparA1, ΔparB1, and ΔparAB1 mutants revealed that two out of 20 genes (VC0067 and VC0069) covered by ParB1 spreading are repressed by both ParB1 and ParA1. A third gene (VC0076) at the outskirts of the spreading area and a few genes further away were also repressed, particularly the gene for an outer membrane protein, ompU (VC0633). Since ParA1 or ParB1 binding was not evident near VC0076 and ompU genes, the repression may require participation of additional factors. Indeed, both ParA1 and ParB1 proteins were found to interact with several V. cholerae proteins in bacterial and yeast two-hybrid screens. These studies demonstrate that chromosomal Par proteins can repress genes unlinked to parS and can do so without direct binding to the cognate promoter DNA. IMPORTANCE Directed segregation of chromosomes is essential for their maintenance in dividing cells. Many bacteria have genes (par) that were thought to be dedicated to segregation based on analogy to their roles in plasmid maintenance. It is becoming clear that chromosomal par genes are pleiotropic and that they contribute to diverse processes such as DNA replication, cell division, cell growth, and motility. One way to explain the pleiotropy is to suggest that Par proteins serve as or control other transcription factors. We tested this model by determining how Par proteins affect genome-wide transcription activity. We found that genes implicated in drug resistance, stress response, and pathogenesis were repressed by Par. Unexpectedly, the repression did not involve direct Par binding to cognate promoter DNA, indicating that the repression may involve Par interactions with other regulators. This pleiotropy highlights the degree of integration of chromosomal Par proteins into cellular control circuitries.

Proteomic strategies for the discovery of novel diagnostic and therapeutic targets for infectious diseases

Viruses have developed numerous and elegant strategies to manipulate the host cell machinery to establish a productive infectious cycle. The interaction of viral proteins with host proteins plays an important role in infection and pathogenesis, often bypassing traditional host defenses such as the interferon response and apoptosis. Host–viral protein interactions can be studied using a variety of proteomic approaches ranging from genetic and biochemical to large‐scale high‐throughput technologies. Protein interactions between host and viral proteins are greatly influenced by host signal transduction pathways. In this review, we will focus on comparing proteomic information obtained through differing technologies and how their integration can be used to determine the functional aspect of the host response to infection. We will briefly review and evaluate techniques employed to elucidate viral–host interactions with a primary focus on Protein Microarrays (PMA) and Mass Spectrometry (MS) as potential tools in the discovery of novel therapeutic targets. As many potential molecular markers and targets are proteins, proteomic profiling is expected to yield both clearer and more direct answers to functional and pharmacologic questions.

A second-generation protein-protein interaction network of Helicobacter pylori

Helicobacter pylori infections cause gastric ulcers and play a major role in the development of gastric cancer. In 2001, the first protein interactome was published for this species, revealing over 1500 binary protein interactions resulting from 261 yeast two-hybrid screens. Here we roughly double the number of previously published interactions using an ORFeome-based, proteome-wide yeast two-hybrid screening strategy. We identified a total of 1515 protein-protein interactions, of which 1461 are new. The integration of all the interactions reported in H. pylori results in 3004 unique interactions that connect about 70% of its proteome. Excluding interactions of promiscuous proteins we derived from our new data a core network consisting of 908 interactions. We compared our data set to several other bacterial interactomes and experimentally benchmarked the conservation of interactions using 365 protein pairs (interologs) of E. coli of which one third turned out to be conserved in both species.

The binary protein-protein interaction landscape of Escherichia coli

Efforts to map the Escherichia coli interactome have identified several hundred macromolecular complexes, but direct binary protein-protein interactions (PPIs) have not been surveyed on a large scale. Here we performed yeast two-hybrid screens of 3,305 baits against 3,606 preys (∼70% of the E. coli proteome) in duplicate to generate a map of 2,234 interactions, which approximately doubles the number of known binary PPIs in E. coli. Integration of binary PPI and genetic-interaction data revealed functional dependencies among components involved in cellular processes, including envelope integrity, flagellum assembly and protein quality control. Many of the binary interactions that we could map in multiprotein complexes were informative regarding internal topology of complexes and indicated that interactions in complexes are substantially more conserved than those interactions connecting different complexes. This resource will be useful for inferring bacterial gene function and provides a draft reference of the basic physical wiring network of this evolutionarily important model microbe.

The protein interaction network of bacteriophage lambda with its host, Escherichia coli

Although most of the 73 open reading frames (ORFs) in bacteriophage λ have been investigated intensively, the function of many genes in host-phage interactions remains poorly understood. Using yeast two-hybrid screens of all lambda ORFs for interactions with its host Escherichia coli, we determined a raw data set of 631 host-phage interactions resulting in a set of 62 high-confidence interactions after multiple rounds of retesting. These links suggest novel regulatory interactions between the E. coli transcriptional network and lambda proteins. Targeted host proteins and genes required for lambda infection are enriched among highly connected proteins, suggesting that bacteriophages resemble interaction patterns of human viruses. Lambda tail proteins interact with both bacterial fimbrial proteins and E. coli proteins homologous to other phage proteins. Lambda appears to dramatically differ from other phages, such as T7, because of its unusually large number of modified and processed proteins, which reduces the number of host-virus interactions detectable by yeast two-hybrid screens.