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. 2025 Apr 22:7:100262.
doi: 10.1016/j.crpvbd.2025.100262. eCollection 2025.

Unveiling the hemolymphatic miRNome composition of the schistosomiasis vector snail Biomphalaria glabrata

Sarah Dametto  1 , Benjamin Gourbal  1 , Cristian Chaparro  1 , Silvain Pinaud  2 , David Duval  1
Affiliations

Unveiling the hemolymphatic miRNome composition of the schistosomiasis vector snail Biomphalaria glabrata

Sarah Dametto et al. Curr Res Parasitol Vector Borne Dis. .

Abstract

MiRNAs are single-stranded short noncoding sequences which display crucial roles on gene transcription regulation in many biological processes especially such as embryonic development, cell proliferation or apoptosis. Also, they are recognized for triggering the host's internal defence mechanisms and immune cell responses thereby playing crucial role in host-parasite interactions. In the present study, a snap-shot of miRNAs, referred to as the miRNome, is described from the hemolymph, the main immune-related compartment of Biomphalaria glabrata snails, one of the intermediate hosts of the trematode parasite Schistosoma mansoni, the causative agent of schistosomiasis. A high throughput sequencing approach of small RNAs has revealed the presence of 63 miRNAs in the hemolymphatic compartment. Mollusc-specific miRNAs including bgl-miR-1985-5p and bgl-miR-1984-5p were identified, along with 25 novel miRNAs. Bioinformatic predictions, thanks to multiple software tools, helped us to identify more than 6000 potential miRNA target gene candidates. Among them is BgTEP1, a complement-like factor involved in parasite clearance. Interestingly, this factor appeared to be targeted by a newly identified miRNA, named bgl-miR-22707-5p. Our study underscores the inherent diversity of miRNAs in the hemolymph of B. glabrata and discusses their potential role in the regulation of the snail's innate immune response.

Keywords: Biomphalaria glabrata; Hemocytes; Host-parasite interaction; Small RNAs; miRNA.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Distribution of count reads (blue histograms - left axis) and unique occurrence (orange points - right axis) for mature miRNAs by size.
Fig. 2
Fig. 2
Venn diagram of miRNAs predicted by ShortStack (green) and MirDeep2 (blue). A Known miRNAs. B. New miRNAs.
Fig. 3
Fig. 3
Venn diagram of miRNAs predicted hits on mRNA target. One hit corresponds to the mapping of one miRNA for one mRNA predicted target. The software tools MiRanda (green), PITA (yellow), RNA22 (blue) and RNAhybrid (orange) were used. A Target’s predictions on 3′UTR. B Target’s predictions on 5′UTR. C Target’s predictions on Protein Coding Gene (PCG).
Fig. 4
Fig. 4
Venn diagram of occurrence of gene targeted by miRNAs on three localisations: 3′UTR (green); 5′UTR (orange); and Protein Coding Gene (PCG) (blue).
See this image and copyright information in PMC

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