Segmenting the etiological agent of schistosomiasis for high-content screening

Real-time and automated monitoring of antischistosomal drug activity profiles for screening of compound libraries

Schistosomiasis is a neglected tropical disease that affects over 200 million people annually. As the antischistosomal drug pipeline is currently empty, repurposing of compound libraries has become a source for accelerating drug development, which demands the implementation of high-throughput and efficient screening strategies. Here, we present a parallelized impedance-based platform for continuous and automated viability evaluation of Schistosoma mansoni schistosomula in 128 microwells during 72 h to identify antischistosomal hits in vitro. By initially screening 57 repurposed compounds against larvae, five drugs are identified, which reduce parasite viability by more than 70%. The activity profiles of the selected drugs are then investigated via real-time dose-response monitoring, and four compounds reveal high potency and rapid action, which renders them suitable candidates for follow-up tests against adult parasites. The study shows that our device is a reliable tool for real-time drug screening analysis of libraries to identify new promising therapeutics against schistosomiasis.

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Scalable, plastic microwell chip with integrated platinum electrodes

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Automated impedance-based recording of 128 microwell units in parallel

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Continuous monitoring of in vitro drug library efficacy on schistosomula for 72 h

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Identification of four fast-acting antischistosomal drugs for in vivo testing

Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence

Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.

Algorithmic Mapping and Characterization of the Drug-Induced Phenotypic-Response Space of Parasites Causing Schistosomiasis

Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Amongst these, schistosomiasis (bilharzia or 'snail fever'), caused by blood flukes of the genus Schistosoma, ranks second only to malaria in terms of human impact: two hundred million people are infected and close to 800 million are at risk of infection. Drug screening against helminths poses unique challenges: the parasite cannot be cloned and is difficult to target using gene knockouts or RNAi. Consequently, both lead identification and validation involve phenotypic screening, where parasites are exposed to compounds whose effects are determined through the analysis of the ensuing phenotypic responses. The efficacy of leads thus identified derives from one or more or even unknown molecular mechanisms of action. The two most immediate and significant challenges that confront the state-of-the-art in this area are: the development of automated and quantitative phenotypic screening techniques and the mapping and quantitative characterization of the totality of phenotypic responses of the parasite. In this paper, we investigate and propose solutions for the latter problem in terms of the following: (1) mathematical formulation and algorithms that allow rigorous representation of the phenotypic response space of the parasite, (2) application of graph-theoretic and network analysis techniques for quantitative modeling and characterization of the phenotypic space, and (3) application of the aforementioned methodology to analyze the phenotypic space of S. mansoni - one of the etiological agents of schistosomiasis, induced by compounds that target its polo-like kinase 1 (PLK 1) gene - a recently validated drug target. In our approach, first, bio-image analysis algorithms are used to quantify the phenotypic responses of different drugs. Next, these responses are linearly mapped into a low- dimensional space using Principle Component Analysis (PCA). The phenotype space is modeled using neighborhood graphs which are used to represent the similarity amongst the phenotypes. These graphs are characterized and explored using network analysis algorithms. We present a number of results related to both the nature of the phenotypic space of the S. mansoni parasite as well as algorithmic issues encountered in constructing and analyzing the phenotypic-response space. In particular, the phenotype distribution of the parasite was found to have a distinct shape and topology. We have also quantitatively characterized the phenotypic space by varying critical model parameters. Finally, these maps of the phenotype space allows visualization and reasoning about complex relationships between putative drugs and their system-wide effects and can serve as a highly efficient paradigm for assimilating and unifying information from phenotypic screens both during lead identification and lead optimization.

Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle

Imaging at high resolution and subsequent image analysis with modified mobile phones have the potential to solve problems related to microscopy-based diagnostics of parasitic infections in many endemic regions. Diagnostics using the computing power of "smartphones" is not restricted by limited expertise or limitations set by visual perception of a microscopist. Thus diagnostics currently almost exclusively dependent on recognition of morphological features of pathogenic organisms could be based on additional properties, such as motility characteristics recognizable by computer vision. Of special interest are infectious larval stages and "micro swimmers" of e.g., the schistosome life cycle, which infect the intermediate and definitive hosts, respectively. The ciliated miracidium, emerges from the excreted egg upon its contact with water. This means that for diagnostics, recognition of a swimming miracidium is equivalent to recognition of an egg. The motility pattern of miracidia could be defined by computer vision and used as a diagnostic criterion. To develop motility pattern-based diagnostics of schistosomiasis using simple imaging devices, we analyzed Paramecium as a model for the schistosome miracidium. As a model for invasive nematodes, such as strongyloids and filaria, we examined a different type of motility in the apathogenic nematode Turbatrix, the "vinegar eel." The results of motion time and frequency analysis suggest that target motility may be expressed as specific spectrograms serving as "diagnostic fingerprints."

Modern approaches to accelerate discovery of new antischistosomal drugs

INTRODUCTION

The almost exclusive use of only praziquantel for the treatment of schistosomiasis has raised concerns about the possible emergence of drug-resistant schistosomes. Consequently, there is an urgent need for new antischistosomal drugs. The identification of leads and the generation of high quality data are crucial steps in the early stages of schistosome drug discovery projects.

AREAS COVERED

Herein, the authors focus on the current developments in antischistosomal lead discovery, specifically referring to the use of automated in vitro target-based and whole-organism screens and virtual screening of chemical databases. They highlight the strengths and pitfalls of each of the above-mentioned approaches, and suggest possible roadmaps towards the integration of several strategies, which may contribute for optimizing research outputs and led to more successful and cost-effective drug discovery endeavors.

EXPERT OPINION

Increasing partnerships and access to funding for drug discovery have strengthened the battle against schistosomiasis in recent years. However, the authors believe this battle also includes innovative strategies to overcome scientific challenges. In this context, significant advances of in vitro screening as well as computer-aided drug discovery have contributed to increase the success rate and reduce the costs of drug discovery campaigns. Although some of these approaches were already used in current antischistosomal lead discovery pipelines, the integration of these strategies in a solid workflow should allow the production of new treatments for schistosomiasis in the near future.

Structure-Bioactivity Relationship for Benzimidazole Thiophene Inhibitors of Polo-Like Kinase 1 (PLK1), a Potential Drug Target in Schistosoma mansoni

BACKGROUND

Schistosoma flatworm parasites cause schistosomiasis, a chronic and debilitating disease of poverty in developing countries. Praziquantel is employed for treatment and disease control. However, its efficacy spectrum is incomplete (less active or inactive against immature stages of the parasite) and there is a concern of drug resistance. Thus, there is a need to identify new drugs and drug targets.

METHODOLOGY/PRINCIPAL FINDINGS

We show that RNA interference (RNAi) of the Schistosoma mansoni ortholog of human polo-like kinase (huPLK)1 elicits a deleterious phenotypic alteration in post-infective larvae (schistosomula or somules). Phenotypic screening and analysis of schistosomula and adult S. mansoni with small molecule inhibitors of huPLK1 identified a number of potent anti-schistosomals. Among these was a GlaxoSmithKline (GSK) benzimidazole thiophene inhibitor that has completed Phase I clinical trials for treatment of solid tumor malignancies. We then obtained GSKs Published Kinase Inhibitor Sets (PKIS) 1 and 2, and phenotypically screened an expanded series of 38 benzimidazole thiophene PLK1 inhibitors. Computational analysis of controls and PLK1 inhibitor-treated populations of somules demonstrated a distinctive phenotype distribution. Using principal component analysis (PCA), the phenotypes exhibited by these populations were mapped, visualized and analyzed through projection to a low-dimensional space. The phenotype distribution was found to have a distinct shape and topology, which could be elicited using cluster analysis. A structure-activity relationship (SAR) was identified for the benzimidazole thiophenes that held for both somules and adult parasites. The most potent inhibitors produced marked phenotypic alterations at 1-2 μM within 1 h. Among these were compounds previously characterized as potent inhibitors of huPLK1 in cell assays.

CONCLUSIONS/SIGNIFICANCE

The reverse genetic and chemical SAR data support a continued investigation of SmPLK1 as a possible drug target and/or the prosecution of the benzimidazole thiophene chemotype as a source of novel anti-schistosomals.

Development and validation of a luminescence-based, medium-throughput assay for drug screening in Schistosoma mansoni

Background

Schistosomiasis, one of the world’s greatest neglected tropical diseases, is responsible for over 280,000 human deaths per annum. Praziquantel, developed in the 1970s, has high efficacy, excellent tolerability, few and transient side effects, simple administration procedures and competitive cost and it is currently the only recommended drug for treatment of human schistosomiasis. The use of a single drug to treat a population of over 200 million infected people appears particularly alarming when considering the threat of drug resistance. Quantitative, objective and validated methods for the screening of compound collections are needed for the discovery of novel anti-schistosomal drugs.

Methodology/Principal Findings

The present work describes the development and validation of a luminescence-based, medium-throughput assay for the detection of schistosomula viability through quantitation of ATP, a good indicator of metabolically active cells in culture. This validated method is demonstrated to be fast, highly reliable, sensitive and automation-friendly. The optimized assay was used for the screening of a small compound library on S. mansoni schistosomula, showing that the proposed method is suitable for a medium-throughput semi-automated screening. Interestingly, the pilot screening identified hits previously reported to have some anti-parasitic activity, further supporting the validity of this assay for anthelminthic drug discovery.

Conclusions

The developed and validated schistosomula viability luminescence-based assay was shown to be successful and suitable for the identification of novel compounds potentially exploitable in future schistosomiasis therapies.

Schistosomiasis, one of the world’s greatest human neglected tropical diseases, is caused by a parasitic flatworm trematode of the genus Schistosoma. Among human parasitic diseases, schistosomiasis ranks second behind malaria in terms of socio-economic and public health importance in tropical and subtropical areas. More than 200 million people are currently infected in 77 countries, 85% of whom live in sub-Saharian Africa. To date no vaccine is available against schistosomiasis. As chemotherapy relies on a single drug, praziquantel, many initiatives have been promoted aiming to search for novel anti-schistosomal drugs that can represent a valid alternative to the current treatment or could be used in case of emerging resistance. Quantitative, objective and validated methods for compound collections screening are needed for the discovery of novel anti-schistosomal drugs. Here, we report the development and validation of a medium-throughput, luminescence-based assay for assessing viability at the schistosomulum stage of the human parasite S. mansoni. Our methodology enables a simple, reproducible, highly sensitive and objective quantitation of parasite viability. It is also automation compatible and enables the screening of compound collections thus hopefully contributing to the discovery of novel therapeutic strategies against schistosomiasis.

Natural products as leads in schistosome drug discovery

Schistosomiasis is a neglected parasitic tropical disease that claims around 200,000 human lives every year. Praziquantel (PZQ), the only drug recommended by the World Health Organization for the treatment and control of human schistosomiasis, is now facing the threat of drug resistance, indicating the urgent need for new effective compounds to treat this disease. Therefore, globally, there is renewed interest in natural products (NPs) as a starting point for drug discovery and development for schistosomiasis. Recent advances in genomics, proteomics, bioinformatics, and cheminformatics have brought about unprecedented opportunities for the rapid and more cost-effective discovery of new bioactive compounds against neglected tropical diseases. This review highlights the main contributions that NP drug discovery and development have made in the treatment of schistosomiasis and it discusses how integration with virtual screening (VS) strategies may contribute to accelerating the development of new schistosomidal leads, especially through the identification of unexplored, biologically active chemical scaffolds and structural optimization of NPs with previously established activity.

The QDREC web server: determining dose-response characteristics of complex macroparasites in phenotypic drug screens

SUMMARY

Neglected tropical diseases (NTDs) caused by helminths constitute some of the most common infections of the world's poorest people. The etiological agents are complex and recalcitrant to standard techniques of molecular biology. Drug screening against helminths has often been phenotypic and typically involves manual description of drug effect and efficacy. A key challenge is to develop automated, quantitative approaches to drug screening against helminth diseases. The quantal dose-response calculator (QDREC) constitutes a significant step in this direction. It can be used to automatically determine quantitative dose-response characteristics and half-maximal effective concentration (EC50) values using image-based readouts from phenotypic screens, thereby allowing rigorous comparisons of the efficacies of drug compounds. QDREC has been developed and validated in the context of drug screening for schistosomiasis, one of the most important NTDs. However, it is equally applicable to general phenotypic screening involving helminths and other complex parasites.

AVAILABILITY AND IMPLEMENTATION

QDREC is publically available at: http://haddock4.sfsu.edu/qdrec2/. Source code and datasets are at: http://tintin.sfsu.edu/projects/phenotypicAssays.html.

CONTACT

rahul@sfsu.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Chemical and genetic validation of the statin drug target to treat the helminth disease, schistosomiasis

The mevalonate pathway is essential in eukaryotes and responsible for a diversity of fundamental synthetic activities. 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is the rate-limiting enzyme in the pathway and is targeted by the ubiquitous statin drugs to treat hypercholesterolemia. Independent reports have indicated the cidal effects of statins against the flatworm parasite, S. mansoni, and the possibility that SmHMGR is a useful drug target to develop new statin-based anti-schistosome therapies. For six commercially available statins, we demonstrate concentration- and time-dependent killing of immature (somule) and adult S. mansoni in vitro at sub-micromolar and micromolar concentrations, respectively. Cidal activity trends with statin lipophilicity whereby simvastatin and pravastatin are the most and least active, respectively. Worm death is preventable by excess mevalonate, the product of HMGR. Statin activity against somules was quantified both manually and automatically using a new, machine learning-based automated algorithm with congruent results. In addition, to chemical targeting, RNA interference (RNAi) of HMGR also kills somules in vitro and, again, lethality is blocked by excess mevalonate. Further, RNAi of HMGR of somules in vitro subsequently limits parasite survival in a mouse model of infection by up to 80%. Parasite death, either via statins or specific RNAi of HMGR, is associated with activation of apoptotic caspase activity. Together, our genetic and chemical data confirm that S. mansoni HMGR is an essential gene and the relevant target of statin drugs. We discuss our findings in context of a potential drug development program and the desired product profile for a new schistosomiasis drug.