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Coherence-gated dynamic light scattering captures cellular dynamics through ultra-low-frequency (0.005–5 Hz) speckle fluctuations and Doppler shifts that encode a broad range of cellular and subcellular motions. The dynamic physiological response of tissues to applied drugs is the basis for a new type of phenotypic profiling for drug screening on multicellular tumor spheroids. Volumetrically resolved tissue-response fluctuation spectrograms act as fingerprints that are segmented through feature masks into high-dimensional feature vectors. Drug-response clustering is achieved through multidimensional scaling with simulated annealing to construct phenotypic drug profiles that cluster drugs with similar responses. Hypoxic vs. normoxic tissue responses present two distinct phenotypes with differentiated responses to environmental perturbations and to pharmacological doses.

To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac) interfered with establishment of cell polarity, cyproheptadine (Periactin) targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil) interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril) had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol) and pimozide (Orap). Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes.

Author Summary

Neuropsychiatric disorders such as depression and psychosis affect one-quarter of all individuals during their lifetime, and despite efforts to improve the selectivity of psychoactive drugs, all are associated with side effects. Drug efficacy and tolerance are known to be linked to an individual's genetic profile, but little is known about the nature of this correlation due, in part, to the current emphasis on screening compounds against targets in vitro. Here we present a comprehensive, genome-wide effort to understand drug effects on the cellular level using an unbiased genome-wide assay to determine the importance of every yeast gene for tolerance to 81 psychoactive drugs. We found that these medications perturbed many evolutionarily conserved genes and cellular pathways, such as those required for vesicle transport, establishment of cell polarity, and chromosome biology. The 500,000 drug–gene measurements obtained in this study increase our understanding of the mechanism of action of psychoactive drugs. Specifically, this study provides a framework to assess the next generation of psychoactive agents and to guide personalized medicine approaches that associate genotype and phenotype.

Recent progress in reconstructing gene regulatory networks has established a framework for a quantitative description of the dynamics of many important cellular processes. Such a description will require novel experimental techniques that enable the generation of time-series data for the governing regulatory proteins in a large number of individual living cells. Here, we utilize microfabrication to construct a Tesla microchemostat that permits single-cell fluorescence imaging of gene expression over many cellular generations. The device is used to capture and constrain asymmetrically dividing or motile cells within a trapping region and to deliver nutrients and regulate the cellular population within this region. We illustrate the operation of the microchemostat with Saccharomyces cerevisiae and explore the evolution of single-cell gene expression and cycle time as a function of generation. Our findings highlight the importance of novel assays for quantifying the dynamics of gene expression and cellular growth, and establish a methodology for exploring the effects of gene expression on long-term processes such as cellular aging.

The conserved target of rapamycin (TOR) kinases regulate many aspects of cellular physiology. They exist in two distinct complexes, termed TOR complex 1 (TORC1) and TOR complex 2 (TORC2), that posses both overlapping and distinct components. TORC1 and TORC2 respond differently to the drug rapamycin and have different cellular functions: whereas the rapamycin-sensitive TORC1 controls many aspects of cell growth and has been characterized in great detail, the TOR complex 2 is less understood and regulates actin polymerization, cell polarity, and ceramide metabolism. How signaling specificity and discrimination between different input signals for the two kinase complexes is achieved is not understood. Here, we show that TORC1 and TORC2 have different localizations in Saccharomyces cerevisiae. TORC1 is localized exclusively to the vacuolar membrane, whereas TORC2 is localized dynamically in a previously unrecognized plasma membrane domain, which we term membrane compartment containing TORC2 (MCT). We find that plasma membrane localization of TORC2 is essential for viability and mediated by lipid binding of the C-terminal domain of the Avo1 subunit. From these data, we suggest that the TOR complexes are spatially separated to determine downstream signaling specificity and their responsiveness to different inputs.

Background

High-throughput screens comparing growth rates of arrays of distinct micro-organism cultures on solid agar are useful, rapid methods of quantifying genetic interactions. Growth rate is an informative phenotype which can be estimated by measuring cell densities at one or more times after inoculation. Precise estimates can be made by inoculating cultures onto agar and capturing cell density frequently by plate-scanning or photography, especially throughout the exponential growth phase, and summarising growth with a simple dynamic model (e.g. the logistic growth model). In order to parametrize such a model, a robust image analysis tool capable of capturing a wide range of cell densities from plate photographs is required.

Results

Colonyzer is a collection of image analysis algorithms for automatic quantification of the size, granularity, colour and location of micro-organism cultures grown on solid agar. Colonyzer is uniquely sensitive to extremely low cell densities photographed after dilute liquid culture inoculation (spotting) due to image segmentation using a mixed Gaussian model for plate-wide thresholding based on pixel intensity. Colonyzer is robust to slight experimental imperfections and corrects for lighting gradients which would otherwise introduce spatial bias to cell density estimates without the need for imaging dummy plates. Colonyzer is general enough to quantify cultures growing in any rectangular array format, either growing after pinning with a dense inoculum or growing with the irregular morphology characteristic of spotted cultures. Colonyzer was developed using the open source packages: Python, RPy and the Python Imaging Library and its source code and documentation are available on SourceForge under GNU General Public License. Colonyzer is adaptable to suit specific requirements: e.g. automatic detection of cultures at irregular locations on streaked plates for robotic picking, or decreasing analysis time by disabling components such as lighting correction or colour measures.

Conclusion

Colonyzer can automatically quantify culture growth from large batches of captured images of microbial cultures grown during genome-wide scans over the wide range of cell densities observable after highly dilute liquid spot inoculation, as well as after more concentrated pinning inoculation. Colonyzer is open-source, allowing users to assess it, adapt it to particular research requirements and to contribute to its development.

The many virtues that made the yeast Saccharomyces cerevisiae a dominant model organism for genetics and molecular biology, are now establishing its role in chemical genetics. Its experimental tractability (i.e., rapid doubling time, simple culture conditions) and the availability of powerful tools for drug-target identification, make yeast an ideal organism for high-throughput phenotypic screening. It may be especially applicable for the discovery of chemical probes targeting highly conserved cellular processes, such as metabolism and bioenergetics, because these probes would likely inhibit the same processes in higher eukaryotes (including man). Importantly, changes in normal cellular metabolism are associated with a variety of diseased states (including neurological disorders and cancer), and exploiting these changes for therapeutic purposes has accordingly gained considerable attention. Here, we review progress and challenges associated with forward chemical genetic screening in yeast. We also discuss evidence supporting these screens as a useful strategy for discovery of new chemical probes and new druggable targets related to cellular metabolism.

Traditional systems of medicines need more evidence-based studies on both crude drugs and purified phytomolecules. Utilization of natural products as pharmacological tools could lead to a number of new major therapeutically active metabolites. Lead molecules are further screened for their potential in terms of quality control, safety assessments, and studies about molecular pharmacology and their related properties. Identification, and quality and safety evaluation of natural products, is a fundamental requirement of industry and other organizations dealing with natural health products (NHPs). Marker analysis, based on chemo-profiling and development of characteristic fingerprints for individual plants, could help to develop uniform standardization tools. Beside such evaluations of clinical parameters, safety profiles as well as drug–herb and herb–herb interactions are the most important parameters for assessment and promotion. With the steady growth of the NHPs, advanced analytical- and mechanism-based screening should be considered for their promotion and value addition in every way for the betterment of healthcare. Thus, there is an urgent need for the development of international co-ordination to promote and develop NHPs, including their assessment, perspectives, pharmacovigilance, and potential harmonization of regulation, quality control and clinical uses.

Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

Author Summary

A major challenge for living organisms is the regulation of cellular growth in a fluctuating environment. Sudden changes in nutrient availability or the presence of stress factors typically require rapid adjustments of cellular growth. The misregulation of growth control in higher organisms is a major factor in the development of cancer. A statistical characterization of cellular growth based on gene expression levels provides a quantitative perspective to understand the regulatory network that controls growth. We develop a model of cellular growth in the yeast Saccharomyces cerevisiae, grounded in the expression levels of a small set of genes. The model is able to predict the growth rate of new cellular cultures from expression data and is robust to changing biological conditions, experimental methods, and technological platforms. The predictions are informative about changes in growth at very short time scales, which direct experimental methods cannot generally access. The model also predicts growth rates in Saccharomyces bayanus and in Schizosaccharomyces pombe, a yeast diverged by approximately a billion years of evolution. Our findings suggest that the model describes fundamental characteristics of the unicellular eukaryotic growth regulatory program. A case study explores the role of nutrient sensing in the yeast growth regulatory system.

Drugs currently available for leishmaniasis treatment often show parasite resistance, highly toxic side effects and prohibitive costs commonly incompatible with patients from the tropical endemic countries. In this sense, there is an urgent need for new drugs as a treatment solution for this neglected disease. Here we show the development and implementation of an automated high-throughput viability screening assay for the discovery of new drugs against Leishmania. Assay validation was done with Leishmania promastigote forms, including the screening of 4,000 compounds with known pharmacological properties. In an attempt to find new compounds with leishmanicidal properties, 26,500 structurally diverse chemical compounds were screened. A cut-off of 70% growth inhibition in the primary screening led to the identification of 567 active compounds. Cellular toxicity and selectivity were responsible for the exclusion of 78% of the pre-selected compounds. The activity of the remaining 124 compounds was confirmed against the intramacrophagic amastigote form of the parasite. In vitro microsomal stability and cytochrome P450 (CYP) inhibition of the two most active compounds from this screening effort were assessed to obtain preliminary information on their metabolism in the host. The HTS approach employed here resulted in the discovery of two new antileishmanial compounds, bringing promising candidates to the leishmaniasis drug discovery pipeline.

Author Summary

Every year, more than 2 million people worldwide suffer from leishmaniasis, a neglected tropical disease present in 88 countries. The disease is caused by the single-celled protozoan parasite species of the genus Leishmania, which is transmitted to humans by the bite of the sandfly. The disease manifests itself in a broad range of symptoms, and its most virulent form, named visceral leishmaniasis, is lethal if not treated. Most of the few available treatments for leishmaniasis were developed decades ago and are often toxic, sometimes even leading to the patient's death. Furthermore, the parasite is developing resistance to available drugs, making the discovery and development of new antileishmanials an urgent need. To tackle this problem, the authors of this study employed the use of high-throughput technologies to screen a large library of small, synthetic molecules for their ability to interfere with the viability of Leishmania parasites. This study resulted in the discovery of two novel compounds with leishmanicidal properties and promising drug-like properties, bringing new candidates to the leishmaniasis drug discovery pipeline.

Background

Characterization of cellular growth is central to understanding living systems. Here, we applied a three-factor design to study the relationship between specific growth rate and genome-wide gene expression in 36 steady-state chemostat cultures of Saccharomyces cerevisiae. The three factors we considered were specific growth rate, nutrient limitation, and oxygen availability.

Results

We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which mRNA expression changes are significantly associated. Among key metabolic pathways, this analysis revealed de novo synthesis of pyrimidine ribonucleotides and ATP producing and consuming reactions at fast cellular growth. By scoring the significance of overlap between growth rate dependent genes and known transcription factor target sets, transcription factors that coordinate balanced growth were also identified. Our analysis shows that Fhl1, Rap1, and Sfp1, regulating protein biosynthesis, have significantly enriched target sets for genes up-regulated with increasing growth rate. Cell cycle regulators, such as Ace2 and Swi6, and stress response regulators, such as Yap1, were also shown to have significantly enriched target sets.

Conclusion

Our work, which is the first genome-wide gene expression study to investigate specific growth rate and consider the impact of oxygen availability, provides a more conservative estimate of growth rate dependent genes than previously reported. We also provide a global view of how a small set of transcription factors, 13 in total, contribute to control of cellular growth rate. We anticipate that multi-factorial designs will play an increasing role in elucidating cellular regulation.

SUMMARY

Cell-based screening can facilitate rapid identification of compounds inducing complex cellular phenotypes. Advancing a compound toward the clinic, however, generally requires identification of precise mechanisms of action. We previously found that epidermal growth factor receptor (EGFR) inhibitors induce acute myeloid leukemia (AML) differentiation via a non-EGFR mechanism. In this report, we integrated proteomic and RNAi-based strategies to identify their off-target anti-AML mechanism. These orthogonal approaches identified Syk as a target in AML. Genetic and pharmacological inactivation of Syk with a drug in clinical trial for other indications promoted differentiation of AML cells and attenuated leukemia growth in vivo. These results demonstrate the power of integrating diverse chemical, proteomic, and genomic screening approaches to identify therapeutic strategies for cancer.

The protease encoded by the human cytomegalovirus (HCMV) is an attractive target for antiviral drug development because of its essential function in viral replication. We describe here a cellular assay in the yeast Saccharomyces cerevisiae for the identification of small molecule inhibitors of HCMV protease by conditional growth in selective medium. In this system, the protease cleavage sequence is inserted into the N-(5′-phosphoribosyl)anthranilate isomerase (Trp1p), a yeast protein essential for cell proliferation in the absence of tryptophan. Coexpression of HCMV protease with the engineered Trp1p substrate in yeast cells results in site-specific cleavage and functional inactivation of the Trp1p enzyme, thereby leading to an arrest of cell proliferation. This growth arrest can be suppressed by the addition of validated HCMV protease inhibitors. The growth selection system presented here provides the basis for a high-throughput screen to identify HCMV protease inhibitors that are active in eukaryotic cells.

The growth inhibition and the lysis of Saccharomyces cerevisiae caused by 2-deoxy-d-glucose (2-DG) were shown to be a consequence of unbalanced cellular growth and division. The lysis, but not the repression of growth and osmotic fragility of cells, could be suppressed by the addition of mannitol as an osmotic stabilizer. This result, as well as the morphological changes observed in the cells and changes in the chemical composition of the cell walls, showed that S. cerevisiae grown in the presence of 2-DG formed weakened cell walls responsible for the osmotic fragility. Evidence is presented for the first time demonstrating the incorporation of 2-DG into yeast cell wall material. Other data suggest that the inhibition of yeast growth by 2-DG results from an interference of phosphorylated metabolites of 2-DG with metabolic processes of glucose and mannose involved in the synthesis of structural cell wall polysaccharides.

Images

To gain insight on the interrelationships of the cellular environment, the properties of growth, and cell cycle progression, we analyzed the dynamic reactions of individual Saccharomyces cerevisiae cells to changes and manipulations of their surroundings. We used a new flow cytometric approach which allows, in asynchronous growing S. cerevisiae populations, tagging of both the cell age and the cell protein content of cells belonging to the different cell cycle set points. Since the cell protein content is a good estimation of the cell size, it is possible to follow the kinetics of the cell size increase during cell cycle progression. The analysis of the findings obtained indicates that both during a nutritional shift-up (from ethanol to glucose) and following the addition of cyclic AMP (cAMP), two important delays are induced. The preexisting cells that at the moment of the nutritional shift-up were cycling before the Start phase delay their entrance into S phase, while cells that were cycling after Start are delayed in their exit from the cycle. The combined effects of the two delays allow the cellular population that preexisted the shift-up to quickly adjust to the new growth condition. The effects of a nutritional shift-down were also determined.

The macrolide heptaene amphotericin B (AmB) induced concentration-dependent effects on Saccharomyces cerevisiae which were separable into two distinct stages. At low concentrations the drug inhibited the growth of the yeast and reversible changed cell permeability to Na+ and K+. At high levels it was lethal. The intracellular K+ concentration of cells with reversible damage (stage I) could be increased by addition of K+ to the medium, but cells irreversibly damaged (stage II) were not able to retain K+. The addition of K+ to the medium did not influence the growth-inhibitory or killing action of AmB. Addition of Mg2+ to cultures increased S. cerevisiae resistance to the killing effects of AmB. At low concentrations of AmB, growth inhibition was also decreased by extracellular Mg2+, but at higher concentration of AmB, growth inhibition was increased, probably because the prevention by Mg2+ of the lethal effect allowed expression of the inhibitory effect in a greater range. Simultaneous addition of K+ and Mg2+ markedly decreased both the inhibitory and lethal action of AmB at all concentrations. Filipin, a pentaene macrolide, had only lethal effects, which were unaffected when K+ was added to the medium but were diminished when medium was supplemented with Mg2+.

A screen of the Saccharomyces cerevisiae genome for fragments conferring a growth-impairment phenotype identified 714 fragments in about 84,000 clones tested.

We have screened the genome of Saccharomyces cerevisiae for fragments that confer a growth-retardation phenotype when overexpressed in a multicopy plasmid with a tetracycline-regulatable (Tet-off) promoter. We selected 714 such fragments with a mean size of 700 base-pairs out of around 84,000 clones tested. These include 493 in-frame open reading frame fragments corresponding to 454 distinct genes (of which 91 are of unknown function), and 162 out-of-frame, antisense and intergenic genomic fragments, representing the largest collection of toxic inserts published so far in yeast.

A phenotypic array method, developed for quantifying cell growth, was applied to the haploid and homozygous diploid yeast deletion strain sets. A growth index was developed to screen for non-additive interacting effects between gene deletion and induced perturbations.

A phenotypic array method, developed for quantifying cell growth, was applied to the haploid and homozygous diploid yeast deletion strain sets. A growth index was developed to screen for non-additive interacting effects between gene deletion and induced perturbations. From a genome screen for hydroxyurea (HU) chemical-genetic interactions, 298 haploid deletion strains were selected for further analysis. The strength of interactions was quantified using a wide range of HU concentrations affecting reference strain growth. The selectivity of interaction was determined by comparison with drugs targeting other cellular processes. Bio-modules were defined as gene clusters with shared strength and selectivity of interaction profiles. The functions and connectivity of modules involved in processes such as DNA repair, protein secretion and metabolic control were inferred from their respective gene composition. The work provides an example of, and a general experimental framework for, quantitative analysis of gene interaction networks that buffer cell growth.

The molecular chaperone Hsp90 regulates the folding of diverse signal transducers in all eukaryotes, profoundly affecting cellular circuitry. In fungi, Hsp90 influences development, drug resistance, and evolution. Hsp90 interacts with ∼10% of the proteome in the model yeast Saccharomyces cerevisiae, while only two interactions have been identified in Candida albicans, the leading fungal pathogen of humans. Utilizing a chemical genomic approach, we mapped the C. albicans Hsp90 interaction network under diverse stress conditions. The chaperone network is environmentally contingent, and most of the 226 genetic interactors are important for growth only under specific conditions, suggesting that they operate downstream of Hsp90, as with the MAPK Hog1. Few interactors are important for growth in many environments, and these are poised to operate upstream of Hsp90, as with the protein kinase CK2 and the transcription factor Ahr1. We establish environmental contingency in the first chaperone network of a fungal pathogen, novel effectors upstream and downstream of Hsp90, and network rewiring over evolutionary time.

Author Summary

Hsp90 is an essential and conserved molecular chaperone in eukaryotes that assists with folding diverse proteins, especially regulators of cellular signaling. By activating signaling in response to environmental cues, Hsp90 has a profound impact on myriad aspects of biology. In fungi, Hsp90 influences development, drug resistance, and evolution. In the model yeast Saccharomyces cerevisiae, Hsp90 interacts with ∼10% of proteins. In the leading human fungal pathogen, Candida albicans, only two interactions have been identified. We conducted a chemical genetic screen to elucidate the C. albicans Hsp90 interaction network under diverse stress conditions. The majority of the 226 genetic interactors are important for growth under specific conditions, suggesting that they act downstream of Hsp90 and that the network is environmentally contingent. For example, the kinase Hog1 depends upon Hsp90 for activation. Only a few interactors are important for growth in many conditions, suggesting that they act upstream of Hsp90. For example, the protein kinase CK2 regulates function of the Hsp90 chaperone machine and the transcription factor Ahr1 governs HSP90 expression. Thus, we identify novel effectors upstream and downstream of Hsp90, and establish the first chaperone network of a fungal pathogen, with evidence for environmental contingency and network rewiring over evolutionary time.

Epigenetic pathways help control the expression of genes. In cancer and other diseases, aberrant silencing or overexpression of genes, such as those that control cell growth, can greatly contribute to pathogenesis. Access to these genes by the transcriptional machinery is largely mediated by chemical modifications of DNA or histones, which are controlled by epigenetic enzymes, making these enzymes attractive targets for drug discovery. Here we describe the characterization of a locus derepression assay, a fluorescence-based mammalian cellular system which was used to screen the NCI structural diversity library for novel epigenetic modulators using an automated imaging platform. Four structurally unique compounds were uncovered that, when further investigated, showed distinct activities. These compounds block the viability of lung cancer and melanoma cells, prevent cell cycle progression, and/or inhibit histone deacetylase activity, altering levels of cellular histone acetylation.

Large-scale chemical genetics screens (chemogenomics) in yeast have been widely used to find drug targets, understand the mechanism-of-action of compounds, and unravel the biochemistry of drug resistance. Chemogenomics is based on the comparison of growth of gene deletants in the presence and absence of a chemical substance. Such studies showed that more than 90% of the yeast genes are required for growth in the presence of at least one chemical. Analysis of these data, using computational approaches, has revealed non-trivial features of the natural chemical tolerance systems. As a result two non-overlapping sets of genes are seen to respectively impart robustness and evolvability in the context of natural chemical resistance. The former is composed of multidrug-resistance genes, whereas the latter comprises genes sharing chemical genetic profiles with many others. Recent publications showing the potential applications chemogenomics in studying the pharmacological basis of various drugs are discussed, as well as the expansion of chemogenomics to other organisms. Finally, integration of chemogenomics with sensitive sequence analysis and ubiquitination/phosphorylation data led to the discovery of a new conserved domain and important post-translational modification pathways involved in stress resistance.

SUMMARY

Regulatory conflicts occur when two signals which individually trigger opposite cellular responses are present simultaneously. Here, we investigate regulatory conflicts in the bacterial response to antibiotic combinations. We use an Escherichia coli promoter-GFP library to study the transcriptional response of many promoters to either additive or antagonistic drug pairs at fine two-dimensional resolution of drug concentration. Surprisingly, we find that this dataset can be characterized as a linear sum of only two principal components. Component one, accounting for over 70% of the response, represents the response to growth inhibition by the drugs. Component two describes how regulatory conflicts are resolved. For the additive drug pair, conflicts are resolved by linearly interpolating the single drug responses, while for the antagonistic drug pair, the growth-limiting drug dominates the response. Importantly, for a given drug pair, the same conflict resolution strategy applies to almost all genes. These results provide a recipe for predicting gene expression responses to antibiotic combinations.

Understanding the actions of drugs and toxins in a cell is of critical importance to medicine, yet many of the molecular events involved in chemical resistance are relatively uncharacterized. In order to identify the cellular processes and pathways targeted by chemicals, we took advantage of the haploid Saccharomyces cerevisiae deletion strains (Winzeler et al., 1999). Although ~4800 of the strains are viable, the loss of a gene in a pathway affected by a drug can lead to a synthetic lethal effect in which the combination of a deletion and a normally sublethal dose of a chemical results in loss of viability. WE carried out genome-wide screens to determine quantitative sensitivities of the deletion set to four chemicals: hydrogen peroxide, menadione, ibuprofen and mefloquine. Hydrogen peroxide and menadione induce oxidative stress in the cell, whereas ibuprofen and mefloquine are toxic to yeast by unknown mechanisms. Here we report the sensitivities of 659 deletion strains that are sensitive to one or more of these four compounds, including 163 multichemicalsensitive strains, 394 strains specific to hydrogen peroxide and/or menadione, 47 specific to ibuprofen and 55 specific to mefloquine.We correlate these results with data from other large-scale studies to yield novel insights into cellular function.

Background

Disruption of cellular antioxidation systems should be an effective method for control of fungal pathogens. Such disruption can be achieved with redox-active compounds. Natural phenolic compounds can serve as potent redox cyclers that inhibit microbial growth through destabilization of cellular redox homeostasis and/or antioxidation systems. The aim of this study was to identify benzaldehydes that disrupt the fungal antioxidation system. These compounds could then function as chemosensitizing agents in concert with conventional drugs or fungicides to improve antifungal efficacy.

Methods

Benzaldehydes were tested as natural antifungal agents against strains of Aspergillus fumigatus, A. flavus, A. terreus and Penicillium expansum, fungi that are causative agents of human invasive aspergillosis and/or are mycotoxigenic. The yeast Saccharomyces cerevisiae was also used as a model system for identifying gene targets of benzaldehydes. The efficacy of screened compounds as effective chemosensitizers or as antifungal agents in formulations was tested with methods outlined by the Clinical Laboratory Standards Institute (CLSI).

Results

Several benzaldehydes are identified having potent antifungal activity. Structure-activity analysis reveals that antifungal activity increases by the presence of an ortho-hydroxyl group in the aromatic ring. Use of deletion mutants in the oxidative stress-response pathway of S. cerevisiae (sod1Δ, sod2Δ, glr1Δ) and two mitogen-activated protein kinase (MAPK) mutants of A. fumigatus (sakAΔ, mpkCΔ), indicates antifungal activity of the benzaldehydes is through disruption of cellular antioxidation. Certain benzaldehydes, in combination with phenylpyrroles, overcome tolerance of A. fumigatus MAPK mutants to this agent and/or increase sensitivity of fungal pathogens to mitochondrial respiration inhibitory agents. Synergistic chemosensitization greatly lowers minimum inhibitory (MIC) or fungicidal (MFC) concentrations. Effective inhibition of fungal growth can also be achieved using combinations of these benzaldehydes.

Conclusions

Natural benzaldehydes targeting cellular antioxidation components of fungi, such as superoxide dismutases, glutathione reductase, etc., effectively inhibit fungal growth. They possess antifungal or chemosensitizing capacity to enhance efficacy of conventional antifungal agents. Chemosensitization can reduce costs, abate resistance, and alleviate negative side effects associated with current antifungal treatments.

Regulation of polarised cell growth is essential for many cellular processes including spatial coordination of cell morphology changes during the division cycle. We present a mathematical model of the core mechanism responsible for the regulation of polarised growth dynamics during the fission yeast cell cycle. The model is based on the competition of growth zones localised at the cell tips for a common substrate distributed uniformly in the cytosol. We analyse the bifurcations in this model as the cell length increases, and show that the growth activation dynamics provides an explanation for the new-end take-off (NETO) as a saddle-node bifurcation at which the cell sharply switches from monopolar to bipolar growth. We study the parameter sensitivity of the bifurcation diagram and relate qualitative changes of the growth pattern, e.g. delayed or absent NETO, to previously observed mutant phenotypes. We investigate the effects of imperfect asymmetric cell division, and show that this leads to distinct growth patterns that provide experimentally testable predictions for validating the presented competitive growth zone activation model. Finally we discuss extension of the model for describing mutant cells with more than two growth zones.

Most cells can dynamically shift their relative reliance on glycolytic versus oxidative metabolism in response to nutrient availability, during development, and in disease. Studies in model systems have shown that re-directing energy metabolism from respiration to glycolysis can suppress oxidative damage and cell death in ischemic injury. At present we have a limited set of drugs that safely toggle energy metabolism in humans. Here, we introduce a quantitative, nutrient sensitized screening strategy that can identify such compounds based on their ability to selectively impair growth and viability of cells grown in galactose versus glucose. We identify several FDA approved agents never before linked to energy metabolism, including meclizine, which blunts cellular respiration via a mechanism distinct from canonical inhibitors. We further show that meclizine pretreatment confers cardioprotection and neuroprotection against ischemia-reperfusion injury in murine models. Nutrient-sensitized screening may offer a useful framework for understanding gene function and drug action within the context of energy metabolism.