Overexpression profiling reveals cellular requirements in the context of genetic backgrounds and environments.

Overexpression can help life adapt to stressful environments, making an examination of overexpressed genes valuable for understanding stress tolerance mechanisms. However, a systematic study of genes whose overexpression is functionally adaptive (GOFAs) under stress has yet to be conducted. We developed a new overexpression profiling method and systematically identified GOFAs in Saccharomyces cerevisiae under stress (heat, salt, and oxidative). Our results show that adaptive overexpression compensates for deficiencies and increases fitness under stress, like calcium under salt stress. We also investigated the impact of different genetic backgrounds on GOFAs, which varied among three S. cerevisiae strains reflecting differing calcium and potassium requirements for salt stress tolerance. Our study of a knockout collection also suggested that calcium prevents mitochondrial outbursts under salt stress. Mitochondria-enhancing GOFAs were only adaptive when adequate calcium was available and non-adaptive when calcium was deficient, supporting this idea. Our findings indicate that adaptive overexpression meets the cell's needs for maximizing the organism's adaptive capacity in the given environment and genetic context.

BIONIC: biological network integration using convolutions.

Biological networks constructed from varied data can be used to map cellular function, but each data type has limitations. Network integration promises to address these limitations by combining and automatically weighting input information to obtain a more accurate and comprehensive representation of the underlying biology. We developed a deep learning-based network integration algorithm that incorporates a graph convolutional network framework. Our method, BIONIC (Biological Network Integration using Convolutions), learns features that contain substantially more functional information compared to existing approaches. BIONIC has unsupervised and semisupervised learning modes, making use of available gene function annotations. BIONIC is scalable in both size and quantity of the input networks, making it feasible to integrate numerous networks on the scale of the human genome. To demonstrate the use of BIONIC in identifying new biology, we predicted and experimentally validated essential gene chemical-genetic interactions from nonessential gene profiles in yeast.

Structure-activity relationship study of nitrogen signaling factors.

We have synthesized 10 analogs of oxylipins, which are nitrogen signaling factors (NSFs) that mediate cell-to-cell communication in the fission yeast Schizosaccharomyces pombe, and evaluated their structure-activity relationships with the aim of developing molecular probes for NSFs. We found that the OH or OAc group at C10 could be replaced with a compact amide (17) or carbamate (19). Introducing an alkyne as a detection tag at C10 led to decreased, though still sufficient, activity. Introducing an alkyne at the C18 position showed a similar trend, suggesting tolerance is relatively low even for compact functional groups such as alkynes. Although introduction of a diazirine moiety as a photoreactive group at the C5 position decreased the activity, we found that introducing diazirine at the C13 position was acceptable, and compound 38 exhibited potent NSF activity. These findings will be helpful in the development of molecular probes for NSFs.

Improving Measures of Chemical Structural Similarity Using Machine Learning on Chemical-Genetic Interactions.

A common strategy for identifying molecules likely to possess a desired biological activity is to search large databases of compounds for high structural similarity to a query molecule that demonstrates this activity, under the assumption that structural similarity is predictive of similar biological activity. However, efforts to systematically benchmark the diverse array of available molecular fingerprints and similarity coefficients have been limited by a lack of large-scale datasets that reflect biological similarities of compounds. To elucidate the relative performance of these alternatives, we systematically benchmarked 11 different molecular fingerprint encodings, each combined with 13 different similarity coefficients, using a large set of chemical-genetic interaction data from the yeast Saccharomyces cerevisiae as a systematic proxy for biological activity. We found that the performance of different molecular fingerprints and similarity coefficients varied substantially and that the all-shortest path fingerprints paired with the Braun-Blanquet similarity coefficient provided superior performance that was robust across several compound collections. We further proposed a machine learning pipeline based on support vector machines that offered a fivefold improvement relative to the best unsupervised approach. Our results generally suggest that using high-dimensional chemical-genetic data as a basis for refining molecular fingerprints can be a powerful approach for improving prediction of biological functions from chemical structures.

Publisher Correction: Integrating yeast chemical genomics and mammalian cell pathway analysis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Characterization of cytopathic factors through genome-wide analysis of the Zika viral proteins in fission yeast.

The Zika virus (ZIKV) causes microcephaly and the Guillain-Barré syndrome. Little is known about how ZIKV causes these conditions or which ZIKV viral protein(s) is responsible for the associated ZIKV-induced cytopathic effects, including cell hypertrophy, growth restriction, cell-cycle dysregulation, and cell death. We used fission yeast for the rapid, global functional analysis of the ZIKV genome. All 14 proteins or small peptides were produced under an inducible promoter, and we measured the intracellular localization and the specific effects on ZIKV-associated cytopathic activities of each protein. The subcellular localization of each ZIKV protein was in overall agreement with its predicted protein structure. Five structural and two nonstructural ZIKV proteins showed various levels of cytopathic effects. The expression of these ZIKV proteins restricted cell proliferation, induced hypertrophy, or triggered cellular oxidative stress leading to cell death. The expression of premembrane protein (prM) resulted in cell-cycle G1 accumulation, whereas membrane-anchored capsid (anaC), membrane protein (M), envelope protein (E), and nonstructural protein 4A (NS4A) caused cell-cycle G2/M accumulation. A mechanistic study revealed that NS4A-induced cellular hypertrophy and growth restriction were mediated specifically through the target of rapamycin (TOR) cellular stress pathway involving Tor1 and type 2A phosphatase activator Tip41. These findings should provide a reference for future research on the prevention and treatment of ZIKV diseases.

MOSAIC: a chemical-genetic interaction data repository and web resource for exploring chemical modes of action.

Summary: Chemical-genomic approaches that map interactions between small molecules and genetic perturbations offer a promising strategy for functional annotation of uncharacterized bioactive compounds. We recently developed a new high-throughput platform for mapping chemical-genetic (CG) interactions in yeast that can be scaled to screen large compound collections, and we applied this system to generate CG interaction profiles for more than 13 000 compounds. When integrated with the existing global yeast genetic interaction network, CG interaction profiles can enable mode-of-action prediction for previously uncharacterized compounds as well as discover unexpected secondary effects for known drugs. To facilitate future analysis of these valuable data, we developed a public database and web interface named MOSAIC. The website provides a convenient interface for querying compounds, bioprocesses (Gene Ontology terms) and genes for CG information including direct CG interactions, bioprocesses and gene-level target predictions. MOSAIC also provides access to chemical structure information of screened molecules, chemical-genomic profiles and the ability to search for compounds sharing structural and functional similarity. This resource will be of interest to chemical biologists for discovering new small molecule probes with specific modes-of-action as well as computational biologists interested in analysing CG interaction networks. Availability and implementation: MOSAIC is available at http://mosaic.cs.umn.edu. Contact: hisyo@riken.jp, yoshidam@riken.jp, charlie.boone@utoronto.ca or chadm@umn.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Functional annotation of chemical libraries across diverse biological processes.

Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

Errata: Functional annotation of chemical libraries across diverse biological processes.

This corrects the article DOI: 10.1038/nchembio.2436.

Errata: Functional annotation of chemical libraries across diverse biological processes.

This corrects the article DOI: 10.1038/nchembio.2436.

Intraspecies cell-cell communication in yeast.

Although yeasts are unicellular microorganisms that can live independently, they can also communicate with other cells, in order to adapt to the environment. Two yeast species, the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe, engage in various kinds of intraspecies cell-cell communication using peptides and chemical molecules that they produce, constituting a sort of 'language'. Cell-cell communication is a fundamental biological process, and its ultimate purpose is to promote survival by sexual reproduction and acquisition of nutrients from the environment. This review summarizes what is known about intraspecies cell-cell communication mediated by molecules including mating pheromones, volatile gases, aromatic alcohols and oxylipins in laboratory strains of S. cerevisiae and S. pombe.

Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interactions.

Chemical-genetic interactions-observed when the treatment of mutant cells with chemical compounds reveals unexpected phenotypes-contain rich functional information linking compounds to their cellular modes of action. To systematically identify these interactions, an array of mutants is challenged with a compound and monitored for fitness defects, generating a chemical-genetic interaction profile that provides a quantitative, unbiased description of the cellular function(s) perturbed by the compound. Genetic interactions, obtained from genome-wide double-mutant screens, provide a key for interpreting the functional information contained in chemical-genetic interaction profiles. Despite the utility of this approach, integrative analyses of genetic and chemical-genetic interaction networks have not been systematically evaluated. We developed a method, called CG-TARGET (Chemical Genetic Translation via A Reference Genetic nETwork), that integrates large-scale chemical-genetic interaction screening data with a genetic interaction network to predict the biological processes perturbed by compounds. In a recent publication, we applied CG-TARGET to a screen of nearly 14,000 chemical compounds in Saccharomyces cerevisiae, integrating this dataset with the global S. cerevisiae genetic interaction network to prioritize over 1500 compounds with high-confidence biological process predictions for further study. We present here a formal description and rigorous benchmarking of the CG-TARGET method, showing that, compared to alternative enrichment-based approaches, it achieves similar or better accuracy while substantially improving the ability to control the false discovery rate of biological process predictions. Additional investigation of the compatibility of chemical-genetic and genetic interaction profiles revealed that one-third of observed chemical-genetic interactions contributed to the highest-confidence biological process predictions and that negative chemical-genetic interactions overwhelmingly formed the basis of these predictions. We also present experimental validations of CG-TARGET-predicted tubulin polymerization and cell cycle progression inhibitors. Our approach successfully demonstrates the use of genetic interaction networks in the high-throughput functional annotation of compounds to biological processes.

Integrating yeast chemical genomics and mammalian cell pathway analysis.

Chemical genomics has been applied extensively to evaluate small molecules that modulate biological processes in Saccharomyces cerevisiae. Here, we use yeast as a surrogate system for studying compounds that are active against metazoan targets. Large-scale chemical-genetic profiling of thousands of synthetic and natural compounds from the Chinese National Compound Library identified those with high-confidence bioprocess target predictions. To discover compounds that have the potential to function like therapeutic agents with known targets, we also analyzed a reference library of approved drugs. Previously uncharacterized compounds with chemical-genetic profiles resembling existing drugs that modulate autophagy and Wnt/ß-catenin signal transduction were further examined in mammalian cells, and new modulators with specific modes of action were validated. This analysis exploits yeast as a general platform for predicting compound bioactivity in mammalian cells.

RK-287107, a potent and specific tankyrase inhibitor, blocks colorectal cancer cell growth in a preclinical model.

Aberrant activation of Wnt/ß-catenin signaling causes tumorigenesis and promotes the proliferation of colorectal cancer cells. Porcupine inhibitors, which block secretion of Wnt ligands, may have only limited clinical impact for the treatment of colorectal cancer, because most colorectal cancer is caused by loss-of-function mutations of the tumor suppressor adenomatous polyposis coli (APC) downstream of Wnt ligands. Tankyrase poly(ADP-ribosyl)ates (PARylates) Axin, a negative regulator of ß-catenin. This post-translational modification causes ubiquitin-dependent degradation of Axin, resulting in ß-catenin accumulation. Tankyrase inhibitors downregulate ß-catenin and suppress the growth of APC-mutated colorectal cancer cells. Herein, we report a novel tankyrase-specific inhibitor RK-287107, which inhibits tankyrase-1 and -2 four- and eight-fold more potently, respectively, than G007-LK, a tankyrase inhibitor that has been previously reported as effective in mouse xenograft models. RK-287107 causes Axin2 accumulation and downregulates ß-catenin, T-cell factor/lymphoid enhancer factor reporter activity and the target gene expression in colorectal cancer cells harboring the shortly truncated APC mutations. Consistently, RK-287107 inhibits the growth of APC-mutated (ß-catenin-dependent) colorectal cancer COLO-320DM and SW403 cells but not the APC-wild (ß-catenin-independent) colorectal cancer RKO cells. Intraperitoneal or oral administration of RK-287107 suppresses COLO-320DM tumor growth in NOD-SCID mice. Rates of tumor growth inhibition showed good correlation with the behavior of pharmacodynamic biomarkers, such as Axin2 accumulation and MYC downregulation. These observations indicate that RK-287107 exerts a proof-of-concept antitumor effect, and thus may have potential for tankyrase-directed molecular cancer therapy.

Brilacidin, a novel antifungal agent against Cryptococcus neoformans.

Cryptococcus neoformans causes cryptococcosis, one of the most prevalent fungal diseases, generally characterized by meningitis. There is a limited and not very effective number of drugs available to combat this disease. In this manuscript, we show the host defense peptide mimetic brilacidin (BRI) as a promising antifungal drug against C. neoformans. BRI can affect the organization of the cell membrane, increasing the fungal cell permeability. We also investigated the effects of BRI against the model system Saccharomyces cerevisiae by analyzing libraries of mutants grown in the presence of BRI. In S. cerevisiae, BRI also affects the cell membrane organization, but in addition the cell wall integrity pathway and calcium metabolism. In vivo experiments show BRI significantly reduces C. neoformans survival inside macrophages and partially clears C. neoformans lung infection in an immunocompetent murine model of invasive pulmonary cryptococcosis. We also observed that BRI interacts with caspofungin (CAS) and amphotericin (AmB), potentiating their mechanism of action against C. neoformans. BRI + CAS affects endocytic movement, calcineurin, and mitogen-activated protein kinases. Our results indicate that BRI is a novel antifungal drug against cryptococcosis. IMPORTANCE: Invasive fungal infections have a high mortality rate causing more deaths annually than tuberculosis or malaria. Cryptococcosis, one of the most prevalent fungal diseases, is generally characterized by meningitis and is mainly caused by two closely related species of basidiomycetous yeasts, Cryptococcus neoformans and Cryptococcus gattii. There are few therapeutic options for treating cryptococcosis, and searching for new antifungal agents against this disease is very important. Here, we present brilacidin (BRI) as a potential antifungal agent against C. neoformans. BRI is a small molecule host defense peptide mimetic that has previously exhibited broad-spectrum immunomodulatory/anti-inflammatory activity against bacteria and viruses. BRI alone was shown to inhibit the growth of C. neoformans, acting as a fungicidal drug, but surprisingly also potentiated the activity of caspofungin (CAS) against this species. We investigated the mechanism of action of BRI and BRI + CAS against C. neoformans. We propose BRI as a new antifungal agent against cryptococcosis.

The SAGA histone acetyltransferase complex regulates leucine uptake through the Agp3 permease in fission yeast.

Metabolic responses of unicellular organisms are mostly acute, transient, and cell-autonomous. Regulation of nutrient uptake in yeast is one such rapid response. High quality nitrogen sources such as NH(4)(+) inhibit uptake of poor nitrogen sources, such as amino acids. Both transcriptional and posttranscriptional mechanisms operate in nutrient uptake regulation; however, many components of this system remain uncharacterized in the fission yeast, Schizosaccharomyces pombe. Here, we demonstrate that the Spt-Ada-Gcn acetyltransferase (SAGA) complex modulates leucine uptake. Initially, we noticed that a branched-chain amino acid auxotroph exhibits a peculiar adaptive growth phenotype on solid minimal media containing certain nitrogen sources. In fact, the growth of many auxotrophic strains is inhibited by excess NH(4)Cl, possibly through nitrogen-mediated uptake inhibition of the corresponding nutrients. Surprisingly, DNA microarray analysis revealed that the transcriptional reprogramming during the adaptation of the branched-chain amino acid auxotroph was highly correlated with reprogramming observed in deletions of the SAGA histone acetyltransferase module genes. Deletion of gcn5(+) increased leucine uptake in the prototrophic background and rendered the leucine auxotroph resistant to NH(4)Cl. Deletion of tra1(+) caused the opposite phenotypes. The increase in leucine uptake in the gcn5Δ mutant was dependent on an amino acid permease gene, SPCC965.11c(+). The closest budding yeast homolog of this permease is a relatively nonspecific amino acid permease AGP3, which functions in poor nutrient conditions. Our analysis identified the regulation of nutrient uptake as a physiological function for the SAGA complex, providing a potential link between cellular metabolism and chromatin regulation.

Profilin is required for Ca2+ homeostasis and Ca2+-modulated bud formation in yeast.

A cls5-1 mutant of Saccharomyces cerevisiae is specifically sensitive to high concentrations of Ca2+, with elevated intracellular calcium content and altered cell morphology in the presence of 100 mM Ca2+. To reveal the mechanisms of the Ca2+-sensitive phenotype, we investigated the gene responsible and its interacting network. We demonstrated that CLS5 is identical to PFY1, encoding profilin. Involvement of profilin in the maintenance of intracellular Ca2+ homeostasis was supported by the fact that both exchangeable and non-exchangeable intracellular Ca2+ pools in the cls5-1 mutant are higher than those of the wild-type strain. Several mutations of the genes whose proteins physically interact with profilin resulted in the Ca2+-sensitive phenotype. Examination of the intracellular Ca2+ pools indicated that Bni1p, Bem1p, Rho1p, and Cla4p are also required for the maintenance of Ca2+ homeostasis. Quantitative morphological analysis revealed that the Ca2+-induced morphological changes in cls5-1 cells are similar to bem1 and cls4-1 cells. Common Ca2+-induced morphological changes were an increase in cell size and a decrease of the ratio of budded cells in the population. Since a mutation allele of cls4-1 is located in the CDC24 gene, we suggest that profilin, Bem1p, and Cdc24p are required for Ca2+-modulated bud formation. Thus, profilin is involved in Ca2+ regulation in two ways: the first is Ca2+ homeostasis by coordination with Bni1p, Bem1p, Rho1p, and Cla4p, and the second is the requirement of Ca2+ for bud formation by coordination with Bem1p and Cdc24p.

Argenteolides A and B, Glycosylated Polyketide-Peptide Hybrid Macrolides from an Actinomycete Streptomyces argenteolus.

Two novel glycosylated polyketide-peptide hybrid macrolides, argenteolides A (1) and B (2), were isolated from an actinomycete Streptomyces argenteolus. Argenteolide A (1) contains a unique 5/5/5 tricyclic system in a 20-membered macrocycle. Their structures were elucidated by extensive spectroscopic analysis, and their stereochemical configurations were established through the application of chemical derivatization, J-based configuration analysis, DP4+ calculation, and electronic circular dichroism calculation. The analysis of the genome sequence revealed a plausible biosynthesis mechanism, and isotope-labeled feeding studies suggested their biogenetic origins. Argenteolides A and B exhibited moderate cytotoxicities against A549, p388, and Hela human carcinoma cell lines as well as antibacterial activities against Staphylococcus aureus and Escherichia coli ATCC25922.

Identification of triazenyl indoles as inhibitors of fungal fatty acid biosynthesis with broad-spectrum activity.

Rising drug resistance among pathogenic fungi, paired with a limited antifungal arsenal, poses an increasing threat to human health. To identify antifungal compounds, we screened the RIKEN natural product depository against representative isolates of four major human fungal pathogens. This screen identified NPD6433, a triazenyl indole with broad-spectrum activity against all screening strains, as well as the filamentous mold Aspergillus fumigatus. Mechanistic studies indicated that NPD6433 targets the enoyl reductase domain of fatty acid synthase 1 (Fas1), covalently inhibiting its flavin mononucleotide-dependent NADPH-oxidation activity and arresting essential fatty acid biosynthesis. Robust Fas1 inhibition kills Candida albicans, while sublethal inhibition impairs diverse virulence traits. At well-tolerated exposures, NPD6433 extended the lifespan of nematodes infected with azole-resistant C. albicans. Overall, identification of NPD6433 provides a tool with which to explore lipid homeostasis as a therapeutic target in pathogenic fungi and reveals a mechanism by which Fas1 function can be inhibited.

FK506-binding protein, FKBP12, promotes serine utilization and negatively regulates threonine deaminase in fission yeast.

FK506-binding protein with a molecular weight of 12 kDa (FKBP12) is a receptor of the immunosuppressive drugs, FK506 and rapamycin. The physiological functions of FKBP12 remain ambiguous because of its nonessentiality and multifunctionality. Here, we show that FKBP12 promotes the utilization of serine as a nitrogen source and regulates the isoleucine biosynthetic pathway in fission yeast. In screening for small molecules that inhibit serine assimilation, we found that the growth of fission yeast cells in medium supplemented with serine as the sole nitrogen source, but not in glutamate-supplemented medium, was suppressed by FKBP12 inhibitors. Knockout of FKBP12 phenocopied the action of these compounds in serine-supplemented medium. Metabolome analyses and genetic screens identified the threonine deaminase, Tda1, to be regulated downstream of FKBP12. Genetic and biochemical analyses unveiled the negative regulation of Tda1 by FKBP12. Our findings reveal new roles of FKBP12 in amino acid biosynthesis and nitrogen metabolism homeostasis.