Integration of chemical-genetic and genetic interaction data links bioactive compounds to cellular target pathways

Bioactive compounds can be valuable research tools and drug leads, but it is often difficult to identify their mechanism of action or cellular target. Here we investigate the potential for integration of chemical-genetic and genetic interaction data to reveal information about the pathways and targets of inhibitory compounds. Taking advantage of the existing complete set of yeast haploid deletion mutants, we generated drug-hypersensitivity (chemical-genetic) profiles for 12 compounds. In addition to a set of compound-specific interactions, the chemical-genetic profiles identified a large group of genes required for multidrug resistance. In particular, yeast mutants lacking a functional vacuolar H(+)-ATPase show multidrug sensitivity, a phenomenon that may be conserved in mammalian cells. By filtering chemical-genetic profiles for the multidrug-resistant genes and then clustering the compound-specific profiles with a compendium of large-scale genetic interaction profiles, we were able to identify target pathways or proteins. This method thus provides a powerful means for inferring mechanism of action.     

Multiplexed and microparticle-based analyses: quantitative tools for the large-scale analysis of biological systems.

While the term flow cytometry refers to the measurement of cells, the approach of making sensitive multiparameter optical measurements in a flowing sample stream is a very general analytical approach. The past few years have seen an explosion in the application of flow cytometry technology for molecular analysis and measurements using microparticles as solid supports. While microsphere-based molecular analyses using flow cytometry date back three decades, the need for highly parallel quantitative molecular measurements that has arisen from various genomic and proteomic advances has driven the development in particle encoding technology to enable highly multiplexed assays. Multiplexed particle-based immunoassays are now common place, and new assays to study genes, protein function, and molecular assembly. Numerous efforts are underway to extend the multiplexing capabilities of microparticle-based assays through new approaches to particle encoding and analyte reporting. The impact of these developments will be seen in the basic research and clinical laboratories, as well as in drug development.     

High‐resolution time‐resolved imaging of in vitro Arabidopsis rosette growth

Although quantitative characterization of growth phenotypes is of key importance for the understanding of essential networks driving plant growth, the majority of growth‐related genes are still being identified based on qualitative visual observations and/or single‐endpoint quantitative measurements. We developed an in vitro growth imaging system (IGIS) to perform time‐resolved analysis of rosette growth. In this system, Arabidopsis plants are grown in Petri dishes mounted on a rotating disk, and images of each plate are taken on an hourly basis. Automated image analysis was developed in order to obtain several growth‐related parameters, such as projected rosette area, rosette relative growth rate, compactness and stockiness, over time. To illustrate the use of the platform and the resulting data, we present the results for the growth response of Col–0 plants subjected to three mild stress conditions. Although the reduction in rosette area was relatively similar at 19 days after stratification, the time‐lapse analysis demonstrated that plants react differently to salt, osmotic and oxidative stress. The rosette area was altered at various time points during development, and leaf movement and shape parameters were also affected differently. We also used the IGIS to analyze in detail the growth behavior of mutants with enhanced leaf size. Analysis of several growth‐related parameters over time in these mutants revealed several specificities in growth behavior, underlining the high complexity of leaf growth coordination. These results demonstrate that time‐resolved imaging of in vitro rosette growth generates a better understanding of growth phenotypes than endpoint measurements.     

Inference of protein complex activities from chemical-genetic profile and its applications: predicting drug-target pathways

The chemical-genetic profile can be defined as quantitative values of deletion strains' growth defects under exposure to chemicals. In yeast, the compendium of chemical-genetic profiles of genomewide deletion strains under many different chemicals has been used for identifying direct target proteins and a common mode-of-action of those chemicals. In the previous study, valuable biological information such as protein-protein and genetic interactions has not been fully utilized. In our study, we integrated this compendium and biological interactions into the comprehensive collection of approximately 490 protein complexes of yeast for model-based prediction of a drug's target proteins and similar drugs. We assumed that those protein complexes (PCs) were functional units for yeast cell growth and regarded them as hidden factors and developed the PC-based Bayesian factor model that relates the chemical-genetic profile at the level of organism phenotypes to the hidden activities of PCs at the molecular level. The inferred PC activities provided the predictive power of a common mode-of-action of drugs as well as grouping of PCs with similar functions. In addition, our PC-based model allowed us to develop a new effective method to predict a drug's target pathway, by which we were able to highlight the target-protein, TOR1, of rapamycin. Our study is the first approach to model phenotypes of systematic deletion strains in terms of protein complexes. We believe that our PC-based approach can provide an appropriate framework for combining and modeling several types of chemical-genetic profiles including interspecies. Such efforts will contribute to predicting more precisely relevant pathways including target proteins that interact directly with bioactive compounds.     

Orthogonal chemical genetic approaches for unraveling signaling pathways

While chemical genetic approach uses small molecules to probe protein functions in cells or organisms, orthogonal chemical genetics refers to strategies that utilize reengineered protein-small molecule interfaces, to alter specificities, in order to probe their functions. The advantage of orthogonal chemical genetics is that the changes at the interfaces are generally so minute that it goes undetected by natural processes, and thus depicts a true physiological picture of biological phenomenon. This review highlights the recent advances in the area of orthogonal chemical genetics, especially those designed to probe signaling processes. Dynamic protein-protein and enzyme-substrate interactions following stimuli form the foundation of signal transduction. These processes not only break spatial and temporal boundaries between interacting proteins, but also impart distinct regulatory properties by creating functional diversity at the interfaces. Functional and temporal modulation of these dynamic interactions by specific chemical probes provides extremely powerful tools to initiate, ablate, decouple and deconvolute different components of a signaling pathway at multiple stages. Not surprisingly, multiple receptor-ligand reengineering approaches have been developed in the last decade to selectively manipulate these transient interactions with the aim of unraveling signaling events. However, given the diversity of protein-protein interactions and novel chemical genetic probes developed to perturb these processes, a short review cannot do adequate justice to all aspects of signaling. For this reason, this review focuses on some orthogonal chemical-genetic strategies that are developed to study signaling processes involving enzyme-substrate interactions.     

A novel genomics approach for the identification of drug targets in pathogens, with special reference to Pseudomonas aeruginosa

Complete genome sequences of several pathogenic bacteria have been determined, and many more such projects are currently under way. While these data potentially contain all the determinants of host-pathogen interactions and possible drug targets, computational tools for selecting suitable candidates for further experimental analyses are currently limited. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug targets. We have used three-way genome comparisons to identify essential genes from Pseudomonas aeruginosa. Our approach identified 306 essential genes that may be considered as potential drug targets. The resultant analyses are in good agreement with the results of systematic gene deletion experiments. This approach enables rapid potential drug target identification, thereby greatly facilitating the search for new antibiotics. These results underscore the utility of large genomic databases for in silico systematic drug target identification in the post-genomic era.     

Navigating the chaperone network: an integrative map of physical and genetic interactions mediated by the hsp90 chaperone

Physical, genetic, and chemical-genetic interactions centered on the conserved chaperone Hsp90 were mapped at high resolution in yeast using systematic proteomic and genomic methods. Physical interactions were identified using genome-wide two hybrid screens combined with large-scale affinity purification of Hsp90-containing protein complexes. Genetic interactions were uncovered using synthetic genetic array technology and by a microarray-based chemical-genetic screen of a set of about 4700 viable yeast gene deletion mutants for hypersensitivity to the Hsp90 inhibitor geldanamycin. An extended network, consisting of 198 putative physical interactions and 451 putative genetic and chemical-genetic interactions, was found to connect Hsp90 to cofactors and substrates involved in a wide range of cellular functions. Two novel Hsp90 cofactors, Tah1 (YCR060W) and Pih1 (YHR034C), were also identified. These cofactors interact physically and functionally with the conserved AAA(+)-type DNA helicases Rvb1/Rvb2, which are key components of several chromatin remodeling factors, thereby linking Hsp90 to epigenetic gene regulation.     

Genome-wide fitness test and mechanism-of-action studies of inhibitory compounds in Candida albicans

Candida albicans is a prevalent fungal pathogen amongst the immunocompromised population, causing both superficial and life-threatening infections. Since C. albicans is diploid, classical transmission genetics can not be performed to study specific aspects of its biology and pathogenesis. Here, we exploit the diploid status of C. albicans by constructing a library of 2,868 heterozygous deletion mutants and screening this collection using 35 known or novel compounds to survey chemically induced haploinsufficiency in the pathogen. In this reverse genetic assay termed the fitness test, genes related to the mechanism of action of the probe compounds are clearly identified, supporting their functional roles and genetic interactions. In this report, chemical-genetic relationships are provided for multiple FDA-approved antifungal drugs (fluconazole, voriconazole, caspofungin, 5-fluorocytosine, and amphotericin B) as well as additional compounds targeting ergosterol, fatty acid and sphingolipid biosynthesis, microtubules, actin, secretion, rRNA processing, translation, glycosylation, and protein folding mechanisms. We also demonstrate how chemically induced haploinsufficiency profiles can be used to identify the mechanism of action of novel antifungal agents, thereby illustrating the potential utility of this approach to antifungal drug discovery.     

Diverse cellular functions of the Hsp90 molecular chaperone uncovered using systems approaches

A comprehensive understanding of the cellular functions of the Hsp90 molecular chaperone has remained elusive. Although Hsp90 is essential, highly abundant under normal conditions, and further induced by environmental stress, only a limited number of Hsp90 "clients" have been identified. To define Hsp90 function, a panel of genome-wide chemical-genetic screens in Saccharomyces cerevisiae were combined with bioinformatic analyses. This approach identified several unanticipated functions of Hsp90 under normal conditions and in response to stress. Under normal growth conditions, Hsp90 plays a major role in various aspects of the secretory pathway and cellular transport; during environmental stress, Hsp90 is required for the cell cycle, meiosis, and cytokinesis. Importantly, biochemical and cell biological analyses validated several of these Hsp90-dependent functions, highlighting the potential of our integrated global approach to uncover chaperone functions in the cell.     

Differential genome analyses of metabolic enzymes in Pseudomonas aeruginosa for drug target identification

Complete genome sequences of several pathogenic bacteria have been determined, and many more such projects are currently under way. While these data potentially contain all the determinants of host-pathogen interactions and possible drug targets, computational tools for selecting suitable candidates for further experimental analyses are currently limited. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug targets. We used a differential pathway analyses approach (based on KEGG data) to identify essential genes from Pseudomonas aeruginosa. Our approach identified 214 unique enzymes in P. aeruginosa that may be potential drug targets and can be considered for rational drug design. About 40% of these putative targets have been reported as essential by transposon mutagenesis data elsewhere. Homology model for one of the proteins (LpxC) is presented as a case study and can be explored for in silico docking with suitable inhibitors. This approach is a step towards facilitating the search for new antibiotics.     

Global investigation of protein-protein interactions in yeast Saccharomyces cerevisiae using re-occurring short polypeptide sequences

Protein-protein interaction (PPI) maps provide insight into cellular biology and have received considerable attention in the post-genomic era. While large-scale experimental approaches have generated large collections of experimentally determined PPIs, technical limitations preclude certain PPIs from detection. Recently, we demonstrated that yeast PPIs can be computationally predicted using re-occurring short polypeptide sequences between known interacting protein pairs. However, the computational requirements and low specificity made this method unsuitable for large-scale investigations. Here, we report an improved approach, which exhibits a specificity of approximately 99.95% and executes 16,000 times faster. Importantly, we report the first all-to-all sequence-based computational screen of PPIs in yeast, Saccharomyces cerevisiae in which we identify 29,589 high confidence interactions of approximately 2 x 10(7) possible pairs. Of these, 14,438 PPIs have not been previously reported and may represent novel interactions. In particular, these results reveal a richer set of membrane protein interactions, not readily amenable to experimental investigations. From the novel PPIs, a novel putative protein complex comprised largely of membrane proteins was revealed. In addition, two novel gene functions were predicted and experimentally confirmed to affect the efficiency of non-homologous end-joining, providing further support for the usefulness of the identified PPIs in biological investigations.     

Rapid quantitative analysis using a single molecule counting approach

Single molecule detection of target molecules specifically bound by paired fluorescently labeled probes has shown great potential for sensitive quantitation of biomolecules. To date, no reports have rigorously evaluated the analytical capabilities of a single molecule detection platform employing this dual-probe approach or the performance of its data analysis methodology. In this paper, we describe a rapid, automated, and sensitive multicolor single molecule detection apparatus and a novel extension of coincident event counting based on detection of fluorescent probes. The approach estimates the number of dual-labeled molecules of interest from the total number of coincident fluorescent events observed by correcting for unbound probes that randomly pass through the interrogation zone simultaneously. Event counting was evaluated on three combinations of distinct fluorescence channels and was demonstrated to outperform conventional spatial cross-correlation in generating a wider linear dynamic response to target molecules. Furthermore, this approach succeeded in detecting subpicomolar concentrations of a model RNA target to which fluorescently labeled oligonucleotide probes were hybridized in a complex background of RNA. These results illustrate that the fluorescent event counting approach described represents a general tool for rapid sensitive quantitative analysis of any sample analyte, including nucleic acids and proteins, for which pairs of specific probes can be developed.     

Mechanistic approach to the problem of hybridization efficiency in fluorescent in situ hybridization

In fluorescent in situ hybridization (FISH), the efficiency of hybridization between the DNA probe and the rRNA has been related to the accessibility of the rRNA when ribosome content and cell permeability are not limiting. Published rRNA accessibility maps show that probe brightness is sensitive to the organism being hybridized and the exact location of the target site and, hence, it is highly unpredictable based on accessibility only. In this study, a model of FISH based on the thermodynamics of nucleic acid hybridization was developed. The model provides a mechanistic approach to calculate the affinity of the probe to the target site, which is defined as the overall Gibbs free energy change (DeltaG degrees overall) for a reaction scheme involving the DNA-rRNA and intramolecular DNA and rRNA interactions that take place during FISH. Probe data sets for the published accessibility maps and experiments targeting localized regions in the 16S rRNA of Escherichia coli were used to demonstrate that DeltaG degrees overall is a strong predictor of hybridization efficiency and superior to conventional estimates based on the dissociation temperature of the DNA/rRNA duplex. The use of the proposed model also allowed the development of mechanistic approaches to increase probe brightness, even in seemingly inaccessible regions of the 16S rRNA. Finally, a threshold DeltaG degrees overall of -13.0 kcal/mol was proposed as a goal in the design of FISH probes to maximize hybridization efficiency without compromising specificity.     

Molecular biology of the blood-brain barrier

Molecular biological investigations into the brain capillary endothelium and microvasculature, which forms the blood-brain barrier (BBB) in vivo, can provide the platform for the discovery and the molecular cloning of BBB-specific genes. Novel BBB genes can be discovered with either a genomics-based approach such as subtractive suppressive hybridization, or a proteomics approach using subtractive antibody expression cloning. BBB-specific genes are disproportionately transporter genes encoding either for carrier-mediated transporters, active efflux transporters, or receptor-mediated transporters. The discovery of new BBB transporters can lead to the development of new approaches to brain drug delivery using endogenous brain endothelial transporters.     

From immunoglobulin gene fingerprinting to motif-specific hybridization: advances in the analysis of B lymphoid clonality in rheumatic diseases

In rheumatic diseases, autoantibody-producing cells of interest are often hidden in a polyclonal B-lymphocyte population. Immunoglobulin gene fingerprinting is a useful approach to screen for expanding clones and to detect recirculation between different locations. The gene fingerprinting approach and the Southern blot technique have been amalgamated, using electrophoretic transfer of a PCR product from an acrylamide gel onto a nylon membrane followed by hybridization with specific oligonucleotide probes. In contrast to conventional fingerprinting, the authenticity of immunoglobulin genes can be confirmed, individual genes can be detected and handling radionucleotides can be avoided. Also, the membrane may be reused for further investigations.