Metabolomics reveal alterations in arachidonic acid metabolism in Schistosoma mekongi after exposure to praziquantel

Anti-fibrotic Effect of Oral Versus Intraperitoneal Administration of Gold Nanoparticles in Hepatic Schistosoma mansoni-Infected Mice

BACKGROUND

Schistosomiasis significantly impacts public health, as it causes severe morbidity. Infections caused by Schistosoma mansoni (S. mansoni) can be treated with gold nanoparticles (AuNPs). This study aims to determine the most effective route of AuNPs administration and the magnitude of its anti-fibrotic effect.

METHODS

In the five groups' in vivo assay design, AuNPs were administered intraperitoneally (1 mg/kg) and orally (1 mg/100 g) to S. mansoni-infected mice. Biochemical parameters (serum levels of albumin and liver enzymes alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were measured. The histological changes of the liver in distinct groups were evaluated using Hematoxylin and Eosin, Masson's trichrome, and immunohistochemical stains.

RESULTS

Infection with S. mansoni was associated with substantial changes in the histological architecture of liver tissue and abnormal levels of hepatic function tests (albumin, AST, and ALT). Schistosoma infected hepatocytes exhibited an abnormal microscopic morphology, granuloma formation and aggressive fibrosis. AuNPs restored the liver histological architecture with a highly significant anti-fibrotic effect and significantly corrected hepatic function test levels. Intraperitoneal administration of AuNPs resulted in the most significant anti-fibrotic effect against hepatic S. mansoni infection as observed in all histological sections with Masson's trichrome being the best stain to represent this fact.

CONCLUSION

For treating S. mansoni-induced chronic liver fibrosis, intraperitoneal administration of AuNPs is a successful and effective route of administration that can be recommended.

Harnessing Schistosoma-associated metabolite changes in the human host to identify biomarkers of infection and morbidity: Where are we and what should we do next?

Schistosomiasis is the second most widespread parasitic disease affecting humans. A key component of today's infection control measures is the diagnosis and monitoring of infection, informing individual- and community-level treatment. However, newly acquired infections and/or low parasite burden are still difficult to diagnose reliably. Furthermore, even though the pathological consequence of schistosome egg sequestration in host tissues is well described, the evidence linking egg burden to morbidity is increasingly challenged, making it inadequate for pathology monitoring. In the last decades, omics-based instruments and methods have been developed, adjusted, and applied in parasitic research. In particular, the profiling of the most reliable determinants of phenotypes, metabolites by metabolomics, emerged as a powerful boost in the understanding of basic interactions within the human host during infection. As such, the fine detection of host metabolites produced upon exposure to parasites such as Schistosoma spp. and the ensuing progression of the disease are believed to enable the identification of Schistosoma spp. potential biomarkers of infection and associated pathology. However, attempts to provide such a comprehensive understanding of the alterations of the human metabolome during schistosomiasis are rare, limited in their design when performed, and mostly inconclusive. In this review, we aimed to briefly summarize the most robust advances in knowledge on the changes in host metabolic profile during Schistosoma infections and provide recommendations for approaches to optimize the identification of metabolomic signatures of human schistosomiasis.

Metagenomic Analysis Reveals Variations in Gut Microbiomes of the Schistosoma mansoni-Transmitting Snails Biomphalaria straminea and Biomphalaria glabrata

Biomphalaria snails play a crucial role in the transmission of the human blood fluke Schistosoma mansoni. The gut microbiota of intermediate hosts is known to influence their physiological functions, but little is known about its composition and role in Biomphalaria snails. To gain insights into the biological characteristics of these freshwater intermediate hosts, we conducted metagenomic sequencing on Biomphalaria straminea and B. glabrata to investigate variations in their gut microbiota. This study revealed that the dominant members of the gut microbiota in B. glabrata belong to the phyla Bacteroidetes and Proteobacteria, which were also found to be the top two most abundant gut bacteria in B. straminea. We identified Firmicutes, Acidovorax and Bosea as distinctive gut microbes in B. straminea, while Aeromonas, Cloacibacterium and Chryseobacterium were found to be dependent features of the B. glabrata gut microbiota. We observed significant differences in the community structures and bacterial functions of the gut microbiota between the two host species. Notably, we found a distinctive richness of antibiotic resistance genes (ARGs) associated with various classes of antibiotics, including bacitracin, chloramphenicol, tetracycline, sulfonamide, penicillin, cephalosporin_ii and cephalosporin_i, fluoroquinolone, aminoglycoside, beta-lactam, multidrug and trimethoprim, in the digestive tracts of the snails. Furthermore, this study revealed the potential correlations between snail gut microbiota and the infection rate of S. mansoni using Spearman correlation analysis. Through metagenomic analysis, our study provided new insights into the gut microbiota of Biomphalaria snails and how it is influenced by host species, thereby enhancing our understanding of variant patterns of gut microbial communities in intermediate hosts. Our findings may contribute to future studies on gastropod-microbe interactions and may provide valuable knowledge for developing snail control strategies to combat schistosomiasis in the future.

Discovery of Schistosoma mekongi circulating proteins and antigens in infected mouse sera

Schistosomiasis is a neglected tropical disease caused by an infection of the parasitic flatworms schistosomes. Schistosoma mekongi is a restricted Schistosoma species found near the Mekong River, mainly in southern Laos and northern Cambodia. Because there is no vaccine or effective early diagnosis available for S. mekongi, additional biomarkers are required. In this study, serum biomarkers associated with S. mekongi-infected mice were identified at 14-, 28-, 42-, and 56-days post-infection. Circulating proteins and antigens of S. mekongi in mouse sera were analyzed using mass spectrometry-based proteomics. Serine protease inhibitors and macrophage erythroblast attacher were down-regulated in mouse sera at all infection timepoints. In addition, 54 circulating proteins and 55 antigens of S. mekongi were identified. Notable circulating proteins included kyphoscoliosis peptidase and putative tuberin, and antigens were detected at all four infection timepoints, particularly in the early stages (12 days). The putative tuberin sequence of S. mekongi was highly similar to homologs found in other members of the genus Schistosoma and less similar to human and murine sequences. Our study provided the identity of promising diagnostic biomarkers that could be applicable in early schistosomiasis diagnosis and vaccine development.

Untargeted serum metabolomic profiling for early detection of Schistosoma mekongi infection in mouse model

Mekong schistosomiasis is a parasitic disease caused by blood flukes in the Lao People’s Democratic Republic and in Cambodia. The standard method for diagnosis of schistosomiasis is detection of parasite eggs from patient samples. However, this method is not sufficient to detect asymptomatic patients, low egg numbers, or early infection. Therefore, diagnostic methods with higher sensitivity at the early stage of the disease are needed to fill this gap. The aim of this study was to identify potential biomarkers of early schistosomiasis using an untargeted metabolomics approach. Serum of uninfected and S. mekongi-infected mice was collected at 2, 4, and 8 weeks post-infection. Samples were extracted for metabolites and analyzed with a liquid chromatography-tandem mass spectrometer. Metabolites were annotated with the MS-DIAL platform and analyzed with Metaboanalyst bioinformatic tools. Multivariate analysis distinguished between metabolites from the different experimental conditions. Biomarker screening was performed using three methods: correlation coefficient analysis; feature important detection with a random forest algorithm; and receiver operating characteristic (ROC) curve analysis. Three compounds were identified as potential biomarkers at the early stage of the disease: heptadecanoyl ethanolamide; picrotin; and theophylline. The levels of these three compounds changed significantly during early-stage infection, and therefore these molecules may be promising schistosomiasis markers. These findings may help to improve early diagnosis of schistosomiasis, thus reducing the burden on patients and limiting spread of the disease in endemic areas.