Inference of Essential Genes of the Parasite Haemonchus contortus via Machine Learning.

Over the years, comprehensive explorations of the model organisms Caenorhabditis elegans (elegant worm) and Drosophila melanogaster (vinegar fly) have contributed substantially to our understanding of complex biological processes and pathways in multicellular organisms generally. Extensive functional genomic-phenomic, genomic, transcriptomic, and proteomic data sets have enabled the discovery and characterisation of genes that are crucial for life, called 'essential genes'. Recently, we investigated the feasibility of inferring essential genes from such data sets using advanced bioinformatics and showed that a machine learning (ML)-based workflow could be used to extract or engineer features from DNA, RNA, protein, and/or cellular data/information to underpin the reliable prediction of essential genes both within and between C. elegans and D. melanogaster. As these are two distantly related species within the Ecdysozoa, we proposed that this ML approach would be particularly well suited for species that are within the same phylum or evolutionary clade. In the present study, we cross-predicted essential genes within the phylum Nematoda (evolutionary clade V)-between C. elegans and the pathogenic parasitic nematode H. contortus-and then ranked and prioritised H. contortus proteins encoded by these genes as intervention (e.g., drug) target candidates. Using strong, validated predictors, we inferred essential genes of H. contortus that are involved predominantly in crucial biological processes/pathways including ribosome biogenesis, translation, RNA binding/processing, and signalling and which are highly transcribed in the germline, somatic gonad precursors, sex myoblasts, vulva cell precursors, various nerve cells, glia, or hypodermis. The findings indicate that this in silico workflow provides a promising avenue to identify and prioritise panels/groups of drug target candidates in parasitic nematodes for experimental validation in vitro and/or in vivo.

Enhanced Genomic and Transcriptomic Resources for Trichinella pseudospiralis and T. spiralis to Underpin the Discovery of Molecular Differences between Stages and Species.

Nematodes of the genus Trichinella are important pathogens of humans and animals. This study aimed to enhance the genomic and transcriptomic resources for T. pseudospiralis (non-encapsulated phenotype) and T. spiralis (encapsulated phenotype) and to explore transcriptional profiles. First, we improved the assemblies of the genomes of T. pseudospiralis (code ISS13) and T. spiralis (code ISS534), achieving genome sizes of 56.6 Mb (320 scaffolds, and an N50 of 1.02 Mb) and 63.5 Mb (568 scaffolds, and an N50 value of 0.44 Mb), respectively. Then, for each species, we produced RNA sequence data for three key developmental stages (first-stage muscle larvae [L1s], adults, and newborn larvae [NBLs]; three replicates for each stage), analysed differential transcription between stages, and explored enriched pathways and processes between species. Stage-specific upregulation was linked to cellular processes, metabolism, and host-parasite interactions, and pathway enrichment analysis showed distinctive biological processes and cellular localisations between species. Indeed, the secreted molecules calmodulin, calreticulin, and calsyntenin-with possible roles in modulating host immune responses and facilitating parasite survival-were unique to T. pseudospiralis and not detected in T. spiralis. These insights into the molecular mechanisms of Trichinella-host interactions might offer possible avenues for developing new interventions against trichinellosis.

Analysis of Haemonchus embryos at single cell resolution identifies two eukaryotic elongation factors as intervention target candidates.

Advances in single cell technologies are allowing investigations of a wide range of biological processes and pathways in animals, such as the multicellular model organism Caenorhabditis elegans - a free-living nematode. However, there has been limited application of such technology to related parasitic nematodes which cause major diseases of humans and animals worldwide. With no vaccines against the vast majority of parasitic nematodes and treatment failures due to drug resistance or inefficacy, new intervention targets are urgently needed, preferably informed by a deep understanding of these nematodes' cellular and molecular biology - which is presently lacking for most worms. Here, we created the first single cell atlas for an early developmental stage of Haemonchus contortus - a highly pathogenic, C. elegans-related parasitic nematode. We obtained and curated RNA sequence (snRNA-seq) data from single nuclei from embryonating eggs of H. contortus (150,000 droplets), and selected high-quality transcriptomic data for > 14,000 single nuclei for analysis, and identified 19 distinct clusters of cells. Guided by comparative analyses with C. elegans, we were able to reproducibly assign seven cell clusters to body wall muscle, hypodermis, neuronal, intestinal or seam cells, and identified eight genes that were transcribed in all cell clusters/types, three of which were inferred to be essential in H. contortus. Two of these genes (i.e. Hc-eef-1A and Hc-eef1G), coding for eukaryotic elongation factors (called Hc-eEF1A and Hc-eEF1G), were also demonstrated to be transcribed and expressed in all key developmental stages of H. contortus. Together with these findings, sequence- and structure-based comparative analyses indicated the potential of Hc-eEF1A and/or Hc-eEF1G as intervention targets within the protein biosynthesis machinery of H. contortus. Future work will focus on single cell studies of all key developmental stages and tissues of H. contortus, and on evaluating the suitability of the two elongation factor proteins as drug targets in H. contortus and related nematodes, with a view to finding new nematocidal drug candidates.

Structure-activity relationship and target investigation of 2-aryl quinolines with nematocidal activity.

Within the context of our anthelmintic discovery program, we recently identified and evaluated a quinoline derivative, called ABX464 or obefazimod, as a nematocidal candidate; synthesised a series of analogues which were assessed for activity against the free-living nematode Caenorhabditis elegans; and predicted compound-target relationships by thermal proteome profiling (TPP) and in silico docking. Here, we logically extended this work and critically evaluated the anthelmintic activity of ABX464 analogues on Haemonchus contortus (barber's pole worm) - a highly pathogenic nematode of ruminant livestock. First, we tested a series of 44 analogues on H. contortus (larvae and adults) to investigate the nematocidal pharmacophore of ABX464, and identified one compound with greater potency than the parent compound and showed moderate activity against a select number of other parasitic nematodes (including Ancylostoma, Heligmosomoides and Strongyloides species). Using TPP and in silico modelling studies, we predicted protein HCON_00074590 (a predicted aldo-keto reductase) as a target candidate for ABX464 in H. contortus. Future work aims to optimise this compound as a nematocidal candidate and investigate its pharmacokinetic properties. Overall, this study presents a first step toward the development of a new nematocide.

Structure activity relationship and target prediction for ABX464 analogues in Caenorhabditis elegans.

Global challenges with treatment failures and/or widespread resistance in parasitic worms against commercially available anthelmintics lend impetus to the development of new anthelmintics with novel mechanism(s) of action. The free-living nematode Caenorhabditis elegans is an important model organism used for drug discovery, including the screening and structure-activity investigation of new compounds, and target deconvolution. Previously, we conducted a whole-organism phenotypic screen of the 'Pandemic Response Box' (from Medicines for Malaria Venture, MMV) and identified a hit compound, called ABX464, with activity against C. elegans and a related, parasitic nematode, Haemonchus contortus. Here, we tested a series of 44 synthesized analogues to explore the pharmacophore of activity on C. elegans and revealed five compounds whose potency was similar or greater than that of ABX464, but which were not toxic to human hepatoma (HepG2) cells. Subsequently, we employed thermal proteome profiling (TPP), protein structure prediction and an in silico-docking algorithm to predict ABX464-target candidates. Taken together, the findings from this study contribute significantly to the early-stage drug discovery of a new nematocide based on ABX464. Future work is aimed at validating the ABX464-protein interactions identified here, and at assessing ABX464 and associated analogues against a panel of parasitic nematodes, towards developing a new anthelmintic with a mechanism of action that is distinct from any of the compounds currently-available commercially.

'Bingo'-a large language model- and graph neural network-based workflow for the prediction of essential genes from protein data.

The identification and characterization of essential genes are central to our understanding of the core biological functions in eukaryotic organisms, and has important implications for the treatment of diseases caused by, for example, cancers and pathogens. Given the major constraints in testing the functions of genes of many organisms in the laboratory, due to the absence of in vitro cultures and/or gene perturbation assays for most metazoan species, there has been a need to develop in silico tools for the accurate prediction or inference of essential genes to underpin systems biological investigations. Major advances in machine learning approaches provide unprecedented opportunities to overcome these limitations and accelerate the discovery of essential genes on a genome-wide scale. Here, we developed and evaluated a large language model- and graph neural network (LLM-GNN)-based approach, called 'Bingo', to predict essential protein-coding genes in the metazoan model organisms Caenorhabditis elegans and Drosophila melanogaster as well as in Mus musculus and Homo sapiens (a HepG2 cell line) by integrating LLM and GNNs with adversarial training. Bingo predicts essential genes under two 'zero-shot' scenarios with transfer learning, showing promise to compensate for a lack of high-quality genomic and proteomic data for non-model organisms. In addition, the attention mechanisms and GNNExplainer were employed to manifest the functional sites and structural domain with most contribution to essentiality. In conclusion, Bingo provides the prospect of being able to accurately infer the essential genes of little- or under-studied organisms of interest, and provides a biological explanation for gene essentiality.

The Proteome and Lipidome of Extracellular Vesicles from Haemonchus contortus to Underpin Explorations of Host-Parasite Cross-Talk.

Many parasitic worms have a major adverse impact on human and animal populations worldwide due to the chronicity of their infections. There is a growing body of evidence indicating that extracellular vesicles (EVs) are intimately involved in modulating (suppressing) inflammatory/immune host responses and parasitism. As one of the most pathogenic nematodes of livestock animals, Haemonchus contortus is an ideal model system for EV exploration. Here, employing a multi-step enrichment process (in vitro culture, followed by ultracentrifugation, size exclusion and filtration), we enriched EVs from H. contortus and undertook the first comprehensive (qualitative and quantitative) multi-omic investigation of EV proteins and lipids using advanced liquid chromatography-mass spectrometry and informatics methods. We identified and quantified 561 proteins and 446 lipids in EVs and compared these molecules with those of adult worms. We identified unique molecules in EVs, such as proteins linked to lipid transportation and lipid species (i.e., sphingolipids) associated with signalling, indicating the involvement of these molecules in parasite-host cross-talk. This work provides a solid starting point to explore the functional roles of EV-specific proteins and lipids in modulating parasite-host cross-talk, and the prospect of finding ways of disrupting or interrupting this relationship to suppress or eliminate parasite infection.

Genome-wide exploration reveals distinctive northern and southern variants of Clonorchis sinensis in the Far East.

Clonorchis sinensis is a carcinogenic liver fluke that causes clonorchiasis-a neglected tropical disease (NTD) affecting ~35 million people worldwide. No vaccine is available, and chemotherapy relies on one anthelmintic, praziquantel. This parasite has a complex life history and is known to infect a range of species of intermediate (freshwater snails and fish) and definitive (piscivorous) hosts. Despite this biological complexity and the impact of this biocarcinogenic pathogen, there has been no previous study of molecular variation in this parasite on a genome-wide scale. Here, we conducted the first extensive nuclear genomic exploration of C. sinensis individuals (n = 152) representing five distinct populations from mainland China, and one from Far East Russia, and revealed marked genetic variation within this species between "northern" and "southern" geographical regions. The discovery of this variation indicates the existence of biologically distinct variants within C. sinensis, which may have distinct epidemiology, pathogenicity and/or chemotherapic responsiveness. The detection of high heterozygosity within C. sinensis specimens suggests that this parasite has developed mechanisms to readily adapt to changing environments and/or host species during its life history/evolution. From an applied perspective, the identification of invariable genes could assist in finding new intervention targets in this parasite, given the major clinical relevance of clonorchiasis. From a technical perspective, the genomic-informatic workflow established herein will be readily applicable to a wide range of other parasites that cause NTDs.

The redlegged earth mite draft genome provides new insights into pesticide resistance evolution and demography in its invasive Australian range.

Genomic data provide valuable insights into pest management issues such as resistance evolution, historical patterns of pest invasions and ongoing population dynamics. We assembled the first reference genome for the redlegged earth mite, Halotydeus destructor (Tucker, 1925), to investigate adaptation to pesticide pressures and demography in its invasive Australian range using whole-genome pool-seq data from regionally distributed populations. Our reference genome comprises 132 autosomal contigs, with a total length of 48.90 Mb. We observed a large complex of ace genes, which has presumably evolved from a long history of organophosphate selection in H. destructor and may contribute towards organophosphate resistance through copy number variation, target-site mutations and structural variants. In the putative ancestral H. destructor ace gene, we identified three target-site mutations (G119S, A201S and F331Y) segregating in organophosphate-resistant populations. Additionally, we identified two new para sodium channel gene mutations (L925I and F1020Y) that may contribute to pyrethroid resistance. Regional structuring observed in population genomic analyses indicates that gene flow in H. destructor does not homogenize populations across large geographic distances. However, our demographic analyses were equivocal on the magnitude of gene flow; the short invasion history of H. destructor makes it difficult to distinguish scenarios of complete isolation vs. ongoing migration. Nonetheless, we identified clear signatures of reduced genetic diversity and smaller inferred effective population sizes in eastern vs. western populations, which is consistent with the stepping-stone invasion pathway of this pest in Australia. These new insights will inform development of diagnostic genetic markers of resistance, further investigation into the multifaceted organophosphate resistance mechanism and predictive modelling of resistance evolution and spread.

Proteomic analysis of Sarcoptes scabiei reveals that proteins differentially expressed between eggs and female adult stages are involved predominantly in genetic information processing, metabolism and/or host-parasite interactions.

Presently, there is a dearth of proteomic data for parasitic mites and their relationship with the host animals. Here, using a high throughput LC-MS/MS-based approach, we undertook the first comprehensive, large-scale proteomic investigation of egg and adult female stages of the scabies mite, Sarcoptes scabiei-one of the most important parasitic mites of humans and other animals worldwide. In total, 1,761 S. scabiei proteins were identified and quantified with high confidence. Bioinformatic analyses revealed differentially expressed proteins to be involved predominantly in biological pathways or processes including genetic information processing, energy (oxidative phosphorylation), nucleotide, amino acid, carbohydrate and/or lipid metabolism, and some adaptive processes. Selected, constitutively and highly expressed proteins, such as peptidases, scabies mite inactivated protease paralogues (SMIPPs) and muscle proteins (myosin and troponin), are proposed to be involved in key biological processes within S. scabiei, host-parasite interactions and/or the pathogenesis of scabies. These proteomic data will enable future molecular, biochemical and physiological investigations of early developmental stages of S. scabiei and the discovery of novel interventions, targeting the egg stage, given its non-susceptibility to acaricides currently approved for the treatment of scabies in humans.

Thermal proteome profiling reveals Haemonchus orphan protein HCO_011565 as a target of the nematocidal small molecule UMW-868.

Parasitic roundworms (nematodes) cause destructive diseases, and immense suffering in humans and other animals around the world. The control of these parasites relies heavily on anthelmintic therapy, but treatment failures and resistance to these drugs are widespread. As efforts to develop vaccines against parasitic nematodes have been largely unsuccessful, there is an increased focus on discovering new anthelmintic entities to combat drug resistant worms. Here, we employed thermal proteome profiling (TPP) to explore hit pharmacology and to support optimisation of a hit compound (UMW-868), identified in a high-throughput whole-worm, phenotypic screen. Using advanced structural prediction and docking tools, we inferred an entirely novel, parasite-specific target (HCO_011565) of this anthelmintic small molecule in the highly pathogenic, blood-feeding barber's pole worm, and in other socioeconomically important parasitic nematodes. The "hit-to-target" workflow constructed here provides a unique prospect of accelerating the simultaneous discovery of novel anthelmintics and associated parasite-specific targets.

Evidence that Transcriptional Alterations in Sarcoptes scabiei Are under Tight Post-Transcriptional (microRNA) Control.

Here, we explored transcriptomic differences among early egg (Ee), late egg (Le) and adult female (Af) stages of the scabies mite, Sarcoptes scabiei, using an integrative bioinformatic approach. We recorded a high, negative correlation between miRNAs and genes with decreased mRNA transcription between the developmental stages, indicating substantial post-transcriptional repression; we also showed a positive correlation between miRNAs and genes with increased mRNA transcription, suggesting indirect post-transcriptional regulation. The alterations in mRNA transcription between the egg and adult female stages of S. scabiei were inferred to be linked to metabolism (including carbohydrate and lipid degradation, amino acid and energy metabolism), environmental information processing (e.g., signal transduction and signalling molecules), genetic information processing (e.g., transcription and translation) and/or organismal systems. Taken together, these results provide insight into the transcription of this socioeconomically important parasitic mite, with a particular focus on the egg stage. This work encourages further, detailed laboratory studies of miRNA regulation across all developmental stages of S. scabiei and might assist in discovering new intervention targets in the egg stage of S. scabiei.

Chromosome-scale Echinococcus granulosus (genotype G1) genome reveals the Eg95 gene family and conservation of the EG95-vaccine molecule.

Cystic echinococcosis is a socioeconomically important parasitic disease caused by the larval stage of the canid tapeworm Echinococcus granulosus, afflicting millions of humans and animals worldwide. The development of a vaccine (called EG95) has been the most notable translational advance in the fight against this disease in animals. However, almost nothing is known about the genomic organisation/location of the family of genes encoding EG95 and related molecules, the extent of their conservation or their functions. The lack of a complete reference genome for E. granulosus genotype G1 has been a major obstacle to addressing these areas. Here, we assembled a chromosomal-scale genome for this genotype by scaffolding to a high quality genome for the congener E. multilocularis, localised Eg95 gene family members in this genome, and evaluated the conservation of the EG95 vaccine molecule. These results have marked implications for future explorations of aspects such as developmentally-regulated gene transcription/expression (using replicate samples) for all E. granulosus stages; structural and functional roles of non-coding genome regions; molecular 'cross-talk' between oncosphere and the immune system; and defining the precise function(s) of EG95. Applied aspects should include developing improved tools for the diagnosis and chemotherapy of cystic echinococcosis of humans.

Nuclear genome of Bulinus truncatus, an intermediate host of the carcinogenic human blood fluke Schistosoma haematobium.

Some snails act as intermediate hosts (vectors) for parasitic flatworms (flukes) that cause neglected tropical diseases, such as schistosomiases. Schistosoma haematobium is a blood fluke that causes urogenital schistosomiasis and induces bladder cancer and increased risk of HIV infection. Understanding the molecular biology of the snail and its relationship with the parasite could guide development of an intervention approach that interrupts transmission. Here, we define the genome for a key intermediate host of S. haematobium-called Bulinus truncatus-and explore protein groups inferred to play an integral role in the snail's biology and its relationship with the schistosome parasite. Bu. truncatus shared many orthologous protein groups with Biomphalaria glabrata-the key snail vector for S. mansoni which causes hepatointestinal schistosomiasis in people. Conspicuous were expansions in signalling and membrane trafficking proteins, peptidases and their inhibitors as well as gene families linked to immune response regulation, such as a large repertoire of lectin-like molecules. This work provides a sound basis for further studies of snail-parasite interactions in the search for targets to block schistosomiasis transmission.

Chromosome-level genome of Schistosoma haematobium underpins genome-wide explorations of molecular variation.

Urogenital schistosomiasis is caused by the blood fluke Schistosoma haematobium and is one of the most neglected tropical diseases worldwide, afflicting > 100 million people. It is characterised by granulomata, fibrosis and calcification in urogenital tissues, and can lead to increased susceptibility to HIV/AIDS and squamous cell carcinoma of the bladder. To complement available treatment programs and break the transmission of disease, sound knowledge and understanding of the biology and ecology of S. haematobium is required. Hybridisation/introgression events and molecular variation among members of the S. haematobium-group might effect important biological and/or disease traits as well as the morbidity of disease and the effectiveness of control programs including mass drug administration. Here we report the first chromosome-contiguous genome for a well-defined laboratory line of this blood fluke. An exploration of this genome using transcriptomic data for all key developmental stages allowed us to refine gene models (including non-coding elements) and annotations, discover 'new' genes and transcription profiles for these stages, likely linked to development and/or pathogenesis. Molecular variation within S. haematobium among some geographical locations in Africa revealed unique genomic 'signatures' that matched species other than S. haematobium, indicating the occurrence of introgression events. The present reference genome (designated Shae.V3) and the findings from this study solidly underpin future functional genomic and molecular investigations of S. haematobium and accelerate systematic, large-scale population genomics investigations, with a focus on improved and sustained control of urogenital schistosomiasis.

"Escalibur"-A practical pipeline for the de novo analysis of nucleotide variation in nonmodel eukaryotes.

The revolution in genomics has enabled large-scale population genetic investigations of a wide range of organisms, but there has been a relatively limited focus on improving analytical pipelines. To efficiently analyse large data sets, highly integrated and automated software pipelines, which are easy to use, efficient, reliable, reproducible and run in multiple computational environments, are required. A number of software workflows have been developed to handle and process such data sets for population genetic analyses, but effective, specialized pipelines for genetic and statistical analyses of nonmodel organisms are lacking. For most species, resources for variomes (sets of genetic variations found in populations of species) are not available, and/or genome assemblies are often incomplete and fragmented, complicating the selection of the most suitable reference genome when multiple assemblies are available. Additionally, the biological samples used often contain extraneous DNA from sources other than the species under investigation (e.g., microbial contamination), which needs to be removed prior to genetic analyses. For these reasons, we established a new pipeline, called Escalibur, which includes: functionalities, such as data trimming and mapping; selection of a suitable reference genome; removal of contaminating read data; recalibration of base calls; and variant-calling. Escalibur uses a proven gatk variant caller and workflow description language (WDL), and is, therefore, a highly efficient and scalable pipeline for the genome-wide identification of nucleotide variation in eukaryotes. This pipeline is available at https://gitlab.unimelb.edu.au/bioscience/escalibur (version 0.3-beta) and is essentially applicable to any prokaryote or eukaryote.

An RNA Interference Tool to Silence Genes in Sarcoptes scabiei Eggs.

In a quest for new interventions against scabies-a highly significant skin disease of mammals, caused by a parasitic mite Sarcoptes scabiei-we are focusing on finding new intervention targets. RNA interference (RNAi) could be an efficient functional genomics approach to identify such targets. The RNAi pathway is present in S. scabiei and operational in the female adult mite, but other developmental stages have not been assessed. Identifying potential intervention targets in the egg stage is particularly important because current treatments do not kill this latter stage. Here, we established an RNAi tool to silence single-copy genes in S. scabiei eggs. Using sodium hypochlorite pre-treatment, we succeeded in rendering the eggshell permeable to dsRNA without affecting larval hatching. We optimised the treatment of eggs with gene-specific dsRNAs to three single-copy target genes (designated Ss-Cof, Ss-Ddp, and Ss-Nan) which significantly and repeatedly suppressed transcription by ~66.6%, 74.3%, and 84.1%, respectively. Although no phenotypic alterations were detected in dsRNA-treated eggs for Ss-Cof and Ss-Nan, the silencing of Ss-Ddp resulted in a 38% reduction of larval hatching. This RNAi method is expected to provide a useful tool for larger-scale functional genomic investigations for the identification of essential genes as potential drug targets.

Harnessing model organism genomics to underpin the machine learning-based prediction of essential genes in eukaryotes - Biotechnological implications.

The availability of high-quality genomes and advances in functional genomics have enabled large-scale studies of essential genes in model eukaryotes, including the 'elegant worm' (Caenorhabditis elegans; Nematoda) and the 'vinegar fly' (Drosophila melanogaster; Arthropoda). However, this is not the case for other, much less-studied organisms, such as socioeconomically important parasites, for which functional genomic platforms usually do not exist. Thus, there is a need to develop innovative techniques or approaches for the prediction, identification and investigation of essential genes. A key approach that could enable the prediction of such genes is machine learning (ML). Here, we undertake an historical review of experimental and computational approaches employed for the characterisation of essential genes in eukaryotes, with a particular focus on model ecdysozoans (C. elegans and D. melanogaster), and discuss the possible applicability of ML-approaches to organisms such as socioeconomically important parasites. We highlight some recent results showing that high-performance ML, combined with feature engineering, allows a reliable prediction of essential genes from extensive, publicly available 'omic data sets, with major potential to prioritise such genes (with statistical confidence) for subsequent functional genomic validation. These findings could 'open the door' to fundamental and applied research areas. Evidence of some commonality in the essential gene-complement between these two organisms indicates that an ML-engineering approach could find broader applicability to ecdysozoans such as parasitic nematodes or arthropods, provided that suitably large and informative data sets become/are available for proper feature engineering, and for the robust training and validation of algorithms. This area warrants detailed exploration to, for example, facilitate the identification and characterisation of essential molecules as novel targets for drugs and vaccines against parasitic diseases. This focus is particularly important, given the substantial impact that such diseases have worldwide, and the current challenges associated with their prevention and control and with drug resistance in parasite populations.

High-Throughput Phenotypic Assay to Screen for Anthelmintic Activity on Haemonchus contortus.

Parasitic worms cause very significant diseases in animals and humans worldwide, and their control is critical to enhance health, well-being and productivity. Due to widespread drug resistance in many parasitic worms of animals globally, there is a major, continuing demand for the discovery and development of anthelmintic drugs for use to control these worms. Here, we established a practical, cost-effective and semi-automated high throughput screening (HTS) assay, which relies on the measurement of motility of larvae of the barber's pole worm (Haemonchus contortus) using infrared light-interference. Using this assay, we screened 80,500 small molecules and achieved a hit rate of 0.05%. We identified three small molecules that reproducibly inhibited larval motility and/or development (IC50 values of ~4 to 41 µM). Future work will critically assess the potential of selected hits as candidates for subsequent optimisation or repurposing against parasitic nematodes. This HTS assay has a major advantage over most previous assays in that it achieves a ≥ 10-times higher throughput (i.e., 10,000 compounds per week), and is thus suited to the screening of libraries of tens of thousands to hundreds of thousands of compounds for subsequent hit-to-lead optimisation or effective repurposing and development. The current assay should be adaptable to many socioeconomically important parasitic nematodes, including those that cause neglected tropical diseases (NTDs). This aspect is of relevance, given the goals of the World Health Organization (WHO) Roadmap for NTDs 2021-2030, to develop more effective drugs and drug combinations to improve patient outcomes and circumvent the ineffectiveness of some current anthelmintic drugs and possible drug resistance.

Cross-Predicting Essential Genes between Two Model Eukaryotic Species Using Machine Learning.

Experimental studies of Caenorhabditis elegans and Drosophila melanogaster have contributed substantially to our understanding of molecular and cellular processes in metazoans at large. Since the publication of their genomes, functional genomic investigations have identified genes that are essential or non-essential for survival in each species. Recently, a range of features linked to gene essentiality have been inferred using a machine learning (ML)-based approach, allowing essentiality predictions within a species. Nevertheless, predictions between species are still elusive. Here, we undertake a comprehensive study using ML to discover and validate features of essential genes common to both C. elegans and D. melanogaster. We demonstrate that the cross-species prediction of gene essentiality is possible using a subset of features linked to nucleotide/protein sequences, protein orthology and subcellular localisation, single-cell RNA-seq, and histone methylation markers. Complementary analyses showed that essential genes are enriched for transcription and translation functions and are preferentially located away from heterochromatin regions of C. elegans and D. melanogaster chromosomes. The present work should enable the cross-prediction of essential genes between model and non-model metazoans.