Functional genomics to uncover drug mechanism of action

Application of Omics Technologies for Evaluation of Antibacterial Mechanisms of Action of Plant-Derived Products

In the face of increasing bacterial resistance to antibiotics currently in use, the search for new antimicrobial agents has received a boost in recent years, with natural products playing an important role in this field. In fact, several methods have been proposed to investigate the antibacterial activities of natural products. However, given that the ultimate aim is future therapeutic use as novel drugs, it is extremely necessary to elucidate their modes of action, stating the molecular effects in detail, and identifying their targets in the bacterial cell. This review analyzes the application of “omics technologies” to understand the antibacterial mechanisms of bioactive natural products, to stimulate research interest in this area and promote scientific collaborations. Some studies have been specifically highlighted herein by examining their procedures and results (targeted proteins and metabolic pathways). These approaches have the potential to provide new insights into our comprehension of antimicrobial resistance/susceptibility, creating new perspectives for the struggle against bacteria, and leading to the development of novel products in the future.

Gain- and Loss-of-Function Mutations in the Breast Cancer Gene GATA3 Result in Differential Drug Sensitivity

Patterns of somatic mutations in cancer genes provide information about their functional role in tumourigenesis, and thus indicate their potential for therapeutic exploitation. Yet, the classical distinction between oncogene and tumour suppressor may not always apply. For instance, TP53 has been simultaneously associated with tumour suppressing and promoting activities. Here, we uncover a similar phenomenon for GATA3, a frequently mutated, yet poorly understood, breast cancer gene. We identify two functional classes of frameshift mutations that are associated with distinct expression profiles in tumours, differential disease-free patient survival and gain- and loss-of-function activities in a cell line model. Furthermore, we find an estrogen receptor-independent synthetic lethal interaction between a GATA3 frameshift mutant with an extended C-terminus and the histone methyltransferases G9A and GLP, indicating perturbed epigenetic regulation. Our findings reveal important insights into mutant GATA3 function and breast cancer, provide the first potential therapeutic strategy and suggest that dual tumour suppressive and oncogenic activities are more widespread than previously appreciated.

Cancer is a disease caused by genetic mutations. Mutation patterns are often indicative of a gene’s function as either tumour promoting or tumour suppressive. Here we describe the frequently mutated, but poorly studied, breast cancer gene GATA3 as a rare exception: We discover that two different functional classes of mutations in this gene can lead to either gain- or loss-of-function activities. The most common type of mutations, resulting in an unusually extended protein, is associated with differential gene expression and decreased disease-free survival. This mutant, in contrast to other mutations or the non-mutated protein, renders cells specifically vulnerable to inhibitors of two chromatin-modifying enzymes, the histone methyltransferases G9A and GLP. Our findings shed light on the functional consequences of frequent GATA3 mutations in breast cancer and represent a first lead toward personalised therapy for a large subgroup of breast cancer patients.

The anticancer natural product ophiobolin A induces cytotoxicity by covalent modification of phosphatidylethanolamine

Phenotypic screens allow the identification of small molecules with promising anticancer activity, but the difficulty in characterizing the mechanism of action of these compounds in human cells often undermines their value as drug leads. Here, we used a loss-of-function genetic screen in human haploid KBM7 cells to discover the mechanism of action of the anticancer natural product ophiobolin A (OPA). We found that genetic inactivation of de novo synthesis of phosphatidylethanolamine (PE) mitigates OPA cytotoxicity by reducing cellular PE levels. OPA reacts with the ethanolamine head group of PE in human cells to form pyrrole-containing covalent cytotoxic adducts and these adducts lead to lipid bilayer destabilization. Our characterization of this unusual cytotoxicity mechanism, made possible by unbiased genetic screening in human cells, suggests that the selective antitumor activity displayed by OPA may be due to altered membrane PE levels in cancer cells.

DOI:http://dx.doi.org/10.7554/eLife.14601.001

Many of the medications that are available to treat cancer are either collected from natural sources or inspired by molecules existing in nature. While it is often challenging to understand how these natural compounds selectively kill cancer cells, characterizing these mechanisms is essential if researchers are to develop new anticancer drugs and treatments based on these compounds.

Ophiobolin A is a compound naturally made by a fungus in order to attack plant cells. It is also able to potently kill cancer cells from humans. In particular, ophiobolin A is a promising candidate for treatment of a type of brain tumor called glioblastomas, which are notoriously difficult to treat with existing medications.

Using a newly developed method, Chidley et al. have now tested which components of human cancer cells are important for ophiobolin A to exert its killing effect. The method revealed that ophiobolin A was less able to kill cancer cells if the cells had lower levels of a molecule called phosphatidylethanolamine in their surface membranes. This observation led Chidley et al. to show that ophiobolin A enters the membrane of human cancer cells and combines chemically with phosphatidylethanolamine to form a new composite molecule. Further experiments showed that the formation of this composite molecule disrupted a model membrane, which suggests that ophiobolin A kills cancer cells by breaking their membranes.

The next challenge is to understand exactly how the composite molecule kills cancer cells via membrane disruption. It also remains unclear if the anticancer activity of ophiobolin A results from cancer cells having a membrane composition that is different from normal cells, and why this difference arises in the first place.

DOI:http://dx.doi.org/10.7554/eLife.14601.002

Identifying antimalarial compounds targeting dihydrofolate reductase-thymidylate synthase (DHFR-TS) by chemogenomic profiling

The mode of action of many antimalarial drugs is unknown. Chemogenomic profiling is a powerful method to address this issue. This experimental approach entails disruption of gene function and phenotypic screening for changes in sensitivity to bioactive compounds. Here, we describe the application of reverse genetics for chemogenomic profiling in Plasmodium. Plasmodium falciparum parasites harbouring a transgenic insertion of the glmS ribozyme downstream of the dihydrofolate reductase-thymidylate synthase (DHFR-TS) gene were used for chemogenomic profiling of antimalarial compounds to identify those which target DHFR-TS. DHFR-TS expression can be attenuated by exposing parasites to glucosamine. Parasites with attenuated DHFR-TS expression were significantly more sensitive to antifolate drugs known to target DHFR-TS. In contrast, no change in sensitivity to other antimalarial drugs with different modes of action was observed. Chemogenomic profiling was performed using the Medicines for Malaria Venture (Switzerland) Malaria Box compound library, and two compounds were identified as novel DHFR-TS inhibitors. We also tested the glmS ribozyme in Plasmodium berghei, a rodent malaria parasite. The expression of reporter genes with downstream glmS ribozyme could be attenuated in transgenic parasites comparable with that obtained in P. falciparum. The chemogenomic profiling method was applied in a P. berghei line expressing a pyrimethamine-resistant Toxoplasma gondii DHFR-TS reporter gene under glmS ribozyme control. Parasites with attenuated expression of this gene were significantly sensitised to antifolates targeting DHFR-TS, but not other drugs with different modes of action. In conclusion, these data show that the glmS ribozyme reverse genetic tool can be applied for identifying primary targets of antimalarial compounds in human and rodent malaria parasites.

The development of high-content screening (HCS) technology and its importance to drug discovery

INTRODUCTION

High-content screening (HCS) was introduced about twenty years ago as a promising analytical approach to facilitate some critical aspects of drug discovery. Its application has spread progressively within the pharmaceutical industry and academia to the point that it today represents a fundamental tool in supporting drug discovery and development.

AREAS COVERED

Here, the authors review some of significant progress in the HCS field in terms of biological models and assay readouts. They highlight the importance of high-content screening in drug discovery, as testified by its numerous applications in a variety of therapeutic areas: oncology, infective diseases, cardiovascular and neurodegenerative diseases. They also dissect the role of HCS technology in different phases of the drug discovery pipeline: target identification, primary compound screening, secondary assays, mechanism of action studies and in vitro toxicology.

EXPERT OPINION

Recent advances in cellular assay technologies, such as the introduction of three-dimensional (3D) cultures, induced pluripotent stem cells (iPSCs) and genome editing technologies (e.g., CRISPR/Cas9), have tremendously expanded the potential of high-content assays to contribute to the drug discovery process. Increasingly predictive cellular models and readouts, together with the development of more sophisticated and affordable HCS readers, will further consolidate the role of HCS technology in drug discovery.

Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning

The structure of genetic interaction networks predicts that, analogous to synthetic lethal interactions between non-essential genes, combinations of compounds with latent activities may exhibit potent synergism. To test this hypothesis, we generated a chemical-genetic matrix of 195 diverse yeast deletion strains treated with 4,915 compounds. This approach uncovered 1,221 genotype-specific inhibitors, which we termed cryptagens. Synergism between 8,128 structurally disparate cryptagen pairs was assessed experimentally and used to benchmark predictive algorithms. A model based on the chemical-genetic matrix and the genetic interaction network failed to accurately predict synergism. However, a combined random forest and Naive Bayesian learner that associated chemical structural features with genotype-specific growth inhibition had strong predictive power. This approach identified previously unknown compound combinations that exhibited species-selective toxicity toward human fungal pathogens. This work demonstrates that machine learning methods trained on unbiased chemical-genetic interaction data may be widely applicable for the discovery of synergistic combinations in different species.