Two-hybrid arrays

The two-hybrid system is a genetic method for detecting protein-protein interactions. The assay can be applied to random libraries or arrays of colonies that express defined pairs of proteins. Arrays enable the testing of all possible protein pairs for interactions in a systematic fashion. The array format makes a large number of individual assays comparable and thus greatly simplifies the identification of false positives. Two-hybrid arrays have been used to study interactions among the proteins of yeast, hepatitis C virus, vaccinia virus, Drosophila, Caenorhabditis elegans, mouse and other species, and have already identified thousands of interactions.     

High-Throughput 1,536-Well Fluorescence Polarization Assays for α1-Acid Glycoprotein and Human Serum Albumin Binding

Two major plasma proteins in humans are primarily responsible for drug binding, the α₁-acid-glycoprotein (AGP) and human serum albumin (HSA). The availability of at least a semiquantitative high-throughput assay for assessment of protein binding is expected to aid in bridging the current gap between high-throughput screening and early lead discovery, where cell-based and biochemical assays are deployed routinely to test up to several million compounds rapidly, as opposed to the late-stage candidate drug profiling methods which test at most dozens of compounds at a time. Here, we describe the miniaturization of a pair of assays based on the binding- and displacement-induced changes in fluorescence polarization (FP) of fluorescent small molecule probes known to specifically target the drug-binding sites of these two proteins. A robust and reproducible assay performance was achieved in ≤4 µL assay volume in 1,536-well format. The assays were tested against a validation set of 10 known protein binders, and the results compared favorably with data obtained using protein-coated beads with high-performance liquid chromatography analysis. The miniaturized assays were taken to a high-throughput level in a screen of the LOPAC¹²⁸⁰ collection of 1,280 pharmacologically active compounds. The adaptation of the AGP and HSA FP assays to a 1,536-well format should allow their use in early-stage profiling of large-size compound sets.     

A homogeneous 384-well high-throughput binding assay for a TNF receptor using alphascreen technology

To take advantage of the growing knowledge of cellular signaling pathways, modern-day drug discovery faces an increasing challenge to develop assays to screen for compounds that modulate protein-protein interactions. One bottleneck in achieving this goal is a lack of suitable and robust assay technologies amenable to a high-throughput format. In this report, we describe how we utilized Alphascreen trade mark technology to develop a high-throughput assay to monitor ligand binding to a member of the tumor necrosis factor receptor superfamily. We expressed a fusion protein consisting of the extracellular domain of the OX40 receptor with the constant domains of human IgG. In the presence of OX40 ligand, we determined a binding affinity constant consistent with reported values and optimized the protocol to develop a simple, homogeneous, and sensitive binding assay in a 384-well format. Finally, we assessed if this system could identify small peptides capable of inhibiting the OX40 receptor and ligand interaction. The results showed that the assay was able to detect such peptides and could be used to launch a high-throughput screening campaign for small molecules able to prevent OX40 receptor activation.     

The art and design of genetic screens: RNA interference

The remarkable gene knockdown technique of RNAi has opened exciting new avenues for genetic screens in model organisms and human cells. Here we describe the current state of the art for RNAi screening, and stress the importance of well-designed assays and of analytical approaches for large-scale screening experiments, from high-throughput screens using simplified homogenous assays to microscopy and whole-animal experiments. Like classical genetic screens in the past, the success of large-scale RNAi surveys depends on a careful development of phenotypic assays and their interpretation in a relevant biological context.     

Gene-environment interactions in atherosclerosis

The importance of environment and genetics working together to shape an individual's risk for atherosclerosis seems intuitively obvious. However, it is only recently that research strategies have begun to evolve that attempt to answer questions related to apportionment of risk that is due to specific environmental and genetic factors. These factors may impact upon risk either singly or, more likely, through a complex interaction that affects the metabolic history of the whole organism. Because the genetic bases of lipid and lipoprotein metabolism have been well-studied, and because of the epidemiologic and pathobiochemical associations between genetic disorders of lipid metabolism and atherosclerosis, researchers have searched for gene-environment interactions within animal and human systems in which the phenotype is defined by some index of lipoprotein metabolism. From work done in the lipoprotein area to this point a clear case can be made for: 1) the genetic influence over the phenotypic response to an environmental stimulus; 2) the environmental modulation of the phenotypic expression of severe genetic defects. In the realm of gene-environment interactions that affect lipoprotein phenotype, diet is the best-studied environmental factor.     

An optimized ATP/PP(i)-exchange assay in 96-well format for screening of adenylation domains for applications in combinatorial biosynthesis

We report a new format for measuring ATP/[(32)P]pyrophosphate exchange in a higher throughput assay of adenylation domains (A-domains) of non-ribosomal peptide synthetases. These enzymes are key specificity determinants in the assembly line biosynthesis of non-ribosomal peptides, an important class of natural products with an activity spectrum ranging from antibiotic to antitumor activities. Our assay in 96-well format allows the rapid measurement of approximately 1000 data points per week as a basis for precise assessment of the kinetics of A-domains. The assay also allows quantitative high-throughput screening of the substrate specificity of A-domains identifying alternative, promiscuous substrates. We show that our assay is able to give high quality data for the T278A mutant of the A-domain of the tyrocidine synthetase module TycA with a 330-fold lower k(cat)/K(M). The large dynamic range of this assay will be useful for the screening of libraries of mutant A-domains. Finally we describe and evaluate a procedure for the high-throughput purification of A-domains in 96-well format for the latter purpose. Our approach will be of utility for mechanistic analysis, substrate profiling and directed evolution of the A-domains, to ultimately enable the combinatorial biosynthesis of non-natural analogues of non-ribosomal peptides that may have potential as alternative drug candidates.     

A dual luciferase multiplexed high-throughput screening platform for protein-protein interactions

To study the biology of regulators of G-protein signaling (RGS) proteins and to facilitate the identification of small molecule modulators of RGS proteins, the authors recently developed an advanced yeast 2-hybrid (YTH) assay format for GalphaZ and RGS-Z1. Moreover, they describe the development of a multiplexed luciferase-based assay that has been successfully adapted to screen large numbers of small molecule modulators of protein-protein interactions. They generated and evaluated 2 different luciferase reporter gene systems for YTH interactions, a Gal4 responsive firefly luciferase reporter gene and a Gal4 responsive Renilla luciferase reporter gene. Both the firefly and Renilla luciferase reporter genes demonstrated a 40- to 50-fold increase in luminescence in strains expressing interacting YTH fusion proteins versus negative control strains. Because the firefly and Renilla luciferase proteins have different substrate specificity, the assays were multiplexed. The multiplexed luciferase-based YTH platform adds speed, sensitivity, simplicity, quantification, and efficiency to YTH high-throughput applications and therefore greatly facilitates the identification of small molecule modulators of protein-protein interactions as tools or potential leads for drug discovery efforts.     

Development and optimization of high-throughput in vitro protein phosphatase screening assays

We describe here detailed protocols to design, optimize and validate in vitro phosphatase assays that we have utilized to conduct high-throughput screens for inhibitors of dual-specificity phosphatases: CDC25B, mitogen-activated protein kinase phosphatase (MKP)-1 and MKP-3. We provide details of the critical steps that are needed to effectively miniaturize the assay into a 384-well, high-throughput format that is both reproducible and cost effective. In vitro phosphatase assays that are optimized according to these protocols should satisfy the assay performance criteria required for a robust high-throughput assay with Z-factors >0.5, and with low intra-plate, inter-plate and day-to-day variability (CV <20%). Assuming the availability of sufficient active phosphatase enzyme and access to appropriate liquid handling automation and detection instruments, a single investigator should be able to develop a 384-well format high-throughput assay in a period of 3-4 weeks.     

Development and validation of a high-throughput whole cell assay to investigate Staphylococcus aureus adhesion to host ligands

Staphylococcus aureus adhesion to the host''s skin and mucosae enables asymptomatic colonization and the establishment of infection. This process is facilitated by cell wall-anchored adhesins that bind to host ligands. Therapeutics targeting this process could provide significant clinical benefits; however, the development of anti-adhesives requires an in-depth knowledge of adhesion-associated factors and an assay amenable to high-throughput applications. Here, we describe the development of a sensitive and robust whole cell assay to enable the large-scale profiling of S. aureus adhesion to host ligands. To validate the assay, and to gain insight into cellular factors contributing to adhesion, we profiled a sequence-defined S. aureus transposon mutant library, identifying mutants with attenuated adhesion to human-derived fibronectin, keratin, and fibrinogen. Our screening approach was validated by the identification of known adhesion-related proteins, such as the housekeeping sortase responsible for covalently linking adhesins to the cell wall. In addition, we also identified genetic loci that could represent undescribed anti-adhesive targets. To compare and contrast the genetic requirements of adhesion to each host ligand, we generated a S. aureus Genetic Adhesion Network, which identified a core gene set involved in adhesion to all three host ligands, and unique genetic signatures. In summary, this assay will enable high-throughput chemical screens to identify anti-adhesives and our findings provide insight into the target space of such an approach.     

Gene-environment interactions in human diseases

Studies of gene-environment interactions aim to describe how genetic and environmental factors jointly influence the risk of developing a human disease. Gene-environment interactions can be described by using several models, which take into account the various ways in which genetic effects can be modified by environmental exposures, the number of levels of these exposures and the model on which the genetic effects are based. Choice of study design, sample size and genotyping technology influence the analysis and interpretation of observed gene-environment interactions. Current systems for reporting epidemiological studies make it difficult to assess whether the observed interactions are reproducible, so suggestions are made for improvements in this area.     

Integrating a functional proteomic approach into the target discovery process

Functional proteomics is a promising technique for the rational identification of novel therapeutic targets by elucidation of the function of newly identified proteins in disease-relevant cellular pathways. Of the recently described high-throughput approaches for analyzing protein-protein interactions, the yeast two-hybrid (Y2H) system has turned out to be one of the most suitable for genome-wide analysis. However, this system presents a challenging technical problem: the high prevalence of false positives and false negatives in datasets due to intrinsic limitations of the technology and the use of a high-throughput, genetic assay. We discuss here the different experimental strategies applied to Y2H assays, their general limitations and advantages. We also address the issue of the contribution of protein interaction mapping to functional biology, especially when combined with complementary genomic and proteomic analyses. Finally, we illustrate how the combination of protein interaction maps with relevant functional assays can provide biological support to large-scale protein interaction datasets and contribute to the identification and validation of potential therapeutic targets.     

A high-throughput system for two-hybrid screening based on growth curve analysis in microtiter plates

The yeast two-hybrid system is a powerful tool for identifying novel protein-protein interactions. In general, biochemical marker genes such as lacZ are exploited for indirect quantification of the interaction, and commonly involve the conduct of rather laborious beta-galactosidase assays. This paper describes a simple alternative method based on growth curve analysis of yeast cultures that is amenable to microtiter plate format, and therefore allows the quantification of large numbers of yeast two-hybrid combinations. The analyzed results of yeast cultures grown in microtiter plates were compared with those obtained from the classical beta-galactosidase assay. We conclude that the method presented here is reproducible, of equal or greater sensitivity than the beta-galactosidase assay, and can be further adapted for application to the conduct of large-scale, automated yeast two-hybrid experiments.     

Mutual Information for Testing Gene-Environment Interaction

Despite current enthusiasm for investigation of gene-gene interactions and gene-environment interactions, the essential issue of how to define and detect gene-environment interactions remains unresolved. In this report, we define gene-environment interactions as a stochastic dependence in the context of the effects of the genetic and environmental risk factors on the cause of phenotypic variation among individuals. We use mutual information that is widely used in communication and complex system analysis to measure gene-environment interactions. We investigate how gene-environment interactions generate the large difference in the information measure of gene-environment interactions between the general population and a diseased population, which motives us to develop mutual information-based statistics for testing gene-environment interactions. We validated the null distribution and calculated the type 1 error rates for the mutual information-based statistics to test gene-environment interactions using extensive simulation studies. We found that the new test statistics were more powerful than the traditional logistic regression under several disease models. Finally, in order to further evaluate the performance of our new method, we applied the mutual information-based statistics to three real examples. Our results showed that P-values for the mutual information-based statistics were much smaller than that obtained by other approaches including logistic regression models.     

Systematic profiling of cellular phenotypes with spotted cell microarrays reveals mating-pheromone response genes

We have developed spotted cell microarrays for measuring cellular phenotypes on a large scale. Collections of cells are printed, stained for subcellular features, then imaged via automated, high-throughput microscopy, allowing systematic phenotypic characterization. We used this technology to identify genes involved in the response of yeast to mating pheromone. Besides morphology assays, cell microarrays should be valuable for high-throughput in situ hybridization and immunoassays, enabling new classes of genetic assays based on cell imaging.     

A comprehensive strategy enabling high-resolution functional analysis of the yeast genome

Functional genomic studies in Saccharomyces cerevisiae have contributed enormously to our understanding of cellular processes. Their full potential, however, has been hampered by the limited availability of reagents to systematically study essential genes and the inability to quantify the small effects of most gene deletions on growth. Here we describe the construction of a library of hypomorphic alleles of essential genes and a high-throughput growth competition assay to measure fitness with unprecedented sensitivity. These tools dramatically increase the breadth and precision with which quantitative genetic analysis can be performed in yeast. We illustrate the value of these approaches by using genetic interactions to reveal new relationships between chromatin-modifying factors and to create a functional map of the proteasome. Finally, by measuring the fitness of strains in the yeast deletion library, we addressed an enigma regarding the apparent prevalence of gene dispensability and found that most genes do contribute to growth.