Matouskova, P. | bioRxiv Science

bioRxiv2026

Protein expression of short-chain dehydrogenases/reductases and their inducibility by flubendazole in Haemonchus contortus

Short-chain dehydrogenases/reductases (SDRs) constitute a large enzyme superfamily involved in endogenous metabolism and xenobiotic biotransformation. In the parasitic nematode Haemonchus contortus, SDRs may catalyze the carbonyl reduction of a benzimidazole anthelmintic flubendazole (FLU), whose increased reduction is associated with FLU resistance. This study thus investigated the constitutive expression of SDRs and their inducibility by FLU in drug-susceptible and benzimidazole-resistant strains of H. contortus. The expression of 23 sdr genes was analyzed by quantitative PCR, while targeted proteomic assays enabled the quantification of 15 SDR proteins. In adult nematodes, pronounced sex-dependent differences were detected at both transcript and protein levels. Resistance-associated alterations were less pronounced and were observed predominantly in males, with SDR9, SDR12, SDR15, and SDR20 displaying increased protein abundances in the resistant strain. Exposure to FLU induced only minimal transcriptional responses in juvenile stages, whereas adult nematodes exhibited marked sex- and strain-specific responses in the expression of SDRs. The strongest transcriptional effects were detected in resistant males, while significant protein-level changes following FLU treatment were observed exclusively in adults of the drug-susceptible strain. Notably, SDR9 and SDR20 combined resistance-associated expression patterns with responsiveness to FLU exposure. Taking together, the first targeted proteomic characterization of SDRs in H. contortus revealed several SDR isozymes with constitutive overexpression in resistant nematodes and/or inducibility by FLU, suggesting a potential role in adaptation to anthelmintic exposure.

molecular biology↗

bioRxiv2021

Image recognition based on deep learning in Haemonchus contortus motility assays

Poor efficacy of some anthelmintics and rising concerns about the widespread drug resistance have highlighted the need for new drug discovery. The parasitic nematode Haemonchus contortus is an important model organism widely used for studies of drug resistance and drug screening with the current gold standard being the motility assay. We applied a deep learning approach Mask R-CNN for analysing motility videos containing varying rates of motile worms and compared it to other commonly used algorithms with different levels of complexity, namely the Wiggle Index and the Wide Field-of-View Nematode Tracking Platform. Mask R-CNN consistently outperformed the other algorithms in terms of the detection of worms as well as the precision of motility forecasts, having a mean absolute percentage error of 7.6% and a mean absolute error of 5.6% for the detection and motility forecasts, respectively. Using Mask R-CNN for motility assays confirmed the common problem with algorithms that use non-maximum suppression in detecting overlapping objects, which negatively impacts the overall precision. The use of intersect over union as a measure of the classification of motile / non-motile instances had an overall accuracy of 89%, indicating that it is a viable alternative to previously used methods based on movement characteristics, such as body bends. In comparison to the existing methods evaluated here, Mask R-CNN performed better and we anticipate that this method will broaden the number of possible approaches to video analysis of worm motility.

bioinformatics↗