Comparative analyses of parasites with a comprehensive database of genome-scale metabolic models

Host cell CRISPR genomics and modelling reveal shared metabolic vulnerabilities in the intracellular development of Plasmodium falciparum and related hemoparasites

Parasitic diseases, particularly malaria (caused by Plasmodium falciparum) and theileriosis (caused by Theileria spp.), profoundly impact global health and the socioeconomic well-being of lower-income countries. Despite recent advances, identifying host metabolic proteins essential for these auxotrophic pathogens remains challenging. Here, we generate a novel metabolic model of human hepatocytes infected with P. falciparum and integrate it with a genome-wide CRISPR knockout screen targeting Theileria-infected cells to pinpoint shared vulnerabilities. We identify key host metabolic enzymes critical for the intracellular survival of both of these lethal hemoparasites. Remarkably, among the metabolic proteins identified by our synergistic approach, we find that host purine and heme biosynthetic enzymes are essential for the intracellular survival of P. falciparum and Theileria, while other host enzymes are only essential under certain metabolic conditions, highlighting P. falciparum's adaptability and ability to scavenge nutrients selectively. Unexpectedly, host porphyrins emerge as being essential for both parasites. The shared vulnerabilities open new avenues for developing more effective therapies against these debilitating diseases, with the potential for broader applicability in combating apicomplexan infections.

Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review

The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ensure safe application on living organisms. Artificial intelligence (AI) and machine learning (MI) can be used to analyze and interpret large amounts of data in the field of toxicology, such as data from toxicological databases and high-content image-based screening data. Physiologically based pharmacokinetic (PBPK) models and nano-quantitative structure-activity relationship (QSAR) models can be used to predict the behavior and toxic effects of nanomaterials, respectively. PBPK and Nano-QSAR are prominent ML tool for harmful event analysis that is used to understand the mechanisms by which chemical compounds can cause toxic effects, while toxicogenomics is the study of the genetic basis of toxic responses in living organisms. Despite the potential of these methods, there are still many challenges and uncertainties that need to be addressed in the field. In this review, we provide an overview of artificial intelligence (AI) and machine learning (ML) techniques in nanomedicine and nanotoxicology to better understand the potential toxic effects of these materials at the nanoscale.

Comprehensive genome-scale metabolic model of the human pathogen Cryptococcus neoformans: A platform for understanding pathogen metabolism and identifying new drug targets

Introduction: The fungal priority pathogen Cryptococcus neoformans causes cryptococcal meningoencephalitis in immunocompromised individuals and leads to hundreds of thousands of deaths per year. The undesirable side effects of existing treatments, the need for long application times to prevent the disease from recurring, the lack of resources for these treatment methods to spread over all continents necessitate the search for new treatment methods. Methods: Genome-scale models have been shown to be valuable in studying the metabolism of many organisms. Here we present the first genome-scale metabolic model for C. neoformans, iCryptococcus. This comprehensive model consists of 1,270 reactions, 1,143 metabolites, 649 genes, and eight compartments. The model was validated, proving accurate when predicting the capability of utilizing different carbon and nitrogen sources and growth rate in comparison to experimental data. Results and Discussion: The compatibility of the in silico Cryptococcus metabolism under infection conditions was assessed. The steroid and amino acid metabolisms found in the essentiality analyses have the potential to be drug targets for the therapeutic strategies to be developed against Cryptococcus species. iCryptococcus model can be applied to explore new targets for antifungal drugs along with essential gene, metabolite and reaction analyses and provides a promising platform for elucidation of pathogen metabolism.

Ring stage classification of Babesia microti and Plasmodium falciparum using optical diffraction 3D tomographic technique

Background

Babesia is an intraerythrocytic parasite often misdiagnosed as a malaria parasite, leading to inappropriate treatment of the disease especially in co-endemic areas. In recent years, optical diffraction tomography (ODT) has shown great potential in the field of pathogen detection by quantification of three-dimensional (3D) imaging tomograms. The 3D imaging of biological cells is crucial to investigate and provide valuable information about the mechanisms behind the pathophysiology of cells and tissues.

Methods

The early ring stage of P. falciparum were obtained from stored stock of infected RBCs and of B. microti were obtained from infected patients during diagnosis. The ODT technique was applied to analyze and characterize detailed differences between P. falciparum and B. microti ring stage at the single cell level. Based on 3D quantitative information, accurate measurement was performed of morphological, biochemical, and biophysical parameters.

Results

Accurate measurements of morphological parameters indicated that the host cell surface area at the ring stage in B. microti was significantly smaller (140.2 ± 17.1 µm2) than that in P. falciparum (159.0 ± 15.2 µm2), and sphericities showed higher levels in B. microti-parasitized cells (0.66 ± 0.05) than in P. falciparum (0.60 ± 0.04). Based on biochemical parameters, host cell hemoglobin level was significantly higher and membrane fluctuations were respectively more active in P. falciparum-infected cells (30.25 ± 2.96 pg; 141.3 ± 24.68 nm) than in B. microti (27.28 ± 3.52 pg; 110.1 ± 38.83 nm). The result indicates that P. falciparum more actively altered host RBCs than B. microti.

Conclusion

Although P. falciparum and B. microti often show confusable characteristics under the microscope, and the actual three-dimensional properties are different. These differences could be used in differential clinical diagnosis of erythrocytes infected with B. microti and P. falciparum.

Graphical Abstract

Host-dependent impairment of parasite development and reproduction in the acanthocephalan model

BACKGROUND

A central question in parasitology is why parasites mature and reproduce in some host species but not in others. Yet, a better understanding of the inability of parasites to complete their life cycles in less suitable hosts may hold clues for their control. To shed light on the molecular basis of parasite (non-)maturation, we analyzed transcriptomes of thorny-headed worms (Acanthocephala: Pomphorhynchus laevis), and compared developmentally arrested worms excised from European eel (Anguilla anguilla) to developmentally unrestricted worms from barbel (Barbus barbus).

RESULTS

Based on 20 RNA-Seq datasets, we demonstrate that transcriptomic profiles are more similar between P. laevis males and females from eel than between their counterparts from barbel. Impairment of sexual phenotype development was reflected in gene ontology enrichment analyses of genes having differential transcript abundances. Genes having reproduction- and energy-related annotations were found to be affected by parasitizing either eel or barbel. According to this, the molecular machinery of male and female acanthocephalans from the eel is less tailored to reproduction and more to coping with the less suitable environment provided by this host. The pattern was reversed in their counterparts from the definitive host, barbel.

CONCLUSIONS

Comparative analysis of transcriptomes of developmentally arrested and reproducing parasites elucidates the challenges parasites encounter in hosts which are unsuitable for maturation and reproduction. By studying a gonochoric species, we were also able to highlight sex-specific traits. In fact, transcriptomic evidence for energy shortage in female acanthocephalans associates with their larger body size. Thus, energy metabolism and glycolysis should be promising targets for the treatment of acanthocephaliasis. Although inherently enabling a higher resolution in heterosexuals, the comparison of parasites from definitive hosts and less suitable hosts, in which the parasites merely survive, should be applicable to hermaphroditic helminths. This may open new perspectives in the control of other helminth pathogens of humans and livestock.