Schistosome species, parasite development, and co-infection combinations determine microbiome dynamics in the snail Biomphalaria glabrata

Rafal Tekreeti
4 days ago
4 min read

By: Ruben Schols, Cyril Hammoud, Karen Bisschop, Isabel Vanoverberghe, Tine Huyse & Ellen Decaestecker

Why did we do this study?

Schistosomiasis is a snail-borne parasitic disease that affects more than 200 million people worldwide. Despite sustained control efforts and effective diagnostic tools, the disease remains widespread - particularly in tropical and subtropical regions – and is now expanding into Southern Europe. Currently, no effective vaccine exists against schistosomiasis, and control efforts mainly depend on preventive chemotherapy and snail control, highlighting the need for novel and sustainable control measures.

Recent evidence suggests that bacteria may play a key role in shaping host susceptibility and transmission dynamics, as links between microbial communities, disease resistance, and vector competence have been established in other host–parasite systems. To better understand the complex interactions driving snail–schistosome compatibility, microbial communities must be examined across different parasite exposure conditions and developmental stages.

What did we do?

Snail samples (Biomphalaria glabrata) were obtained from exposure experiments involving three schistosome populations (two Schistosoma mansoni and one S. rodhaini). The (co-)infection status of each snail was determined via diagnostic PCRs and metabarcoding. This experimental setup allowed us to explore microbial aspects of the snail-schistosome interaction in unprecedented detail.

By characterizing the bacterial component of the microbiome based on partial 16S rRNA gene sequencing we discovered that uninfected snails had a significantly higher alpha diversity compared to infected snails but only 30 days after parasite exposure, which coincides with the release of parasites into the environment (i.e., cercarial shedding) (Fig. 1). The drop in diversity could stem from tissue damage and biochemical stress associated with cercarial emergence, from shifts in microbial load relative to increasing parasite DNA, or parasite induced changes necessary for the onset of cercarial shedding. However, no clear signs of dysbiosis were detected at this stage, and bacterial load reductions were not significant. These findings suggest that the microbiome responds subtly but specifically to the transition from parasite maturation to cercarial release, reflecting a complex snail–parasite–microbiome interaction.

Figure 1: The alpha diversity of infected vs uninfected samples across various days post S. mansoni population BRE miracidium exposure (i.e., daysPE). Faith’s phylogenetic diversity metric (FaithsPD), based on mean values with error bars representing a single standard deviation. Circles indicate infected samples, squares uninfected samples. Significance: <0.05=‘*’. — Figure 1: The alpha diversity of infected vs uninfected samples across various days post *S. mansoni* population BRE miracidium exposure (i.e., daysPE). Faith’s phylogenetic diversity metric (FaithsPD), based on mean values with error bars representing a single standard deviation. Circles indicate infected samples, squares uninfected samples. Significance: <0.05=‘*’.

We observed dysbiosis in snails infected with S. mansoni but not in those infected by S. rodhaini (Fig. 2). The difference is likely driven by species-specific developmental patterns and adaptations to their natural snail hosts, since S. mansoni naturally infects B. glabrata. Our results suggest that host adaptation determines the extent of microbiome disruption, indicating that disrupting the host microbiome could offer benefits to the parasite.

Figure 2: The bacterial aspect of the microbiome for snails 40 days post exposure to S. mansoni population BRE, S. mansoni population LE, and S. rodhaini. Uninfected samples from all exposure experiments are combined under “Uninfected” as selected by the model. The within-group Bray–Curtis dissimilarity for the different diagnosed infections, which we use as a measure for dysbiosis. Significance: <0.0001=‘****’. — Figure 2: The bacterial aspect of the microbiome for snails 40 days post exposure to *S. mansoni* population BRE, *S. mansoni* population LE, and *S. rodhaini*. Uninfected samples from all exposure experiments are combined under “Uninfected” as selected by the model. The within-group Bray–Curtis dissimilarity for the different diagnosed infections, which we use as a measure for dysbiosis. Significance: <0.0001=‘****’.

Furthermore, co-infection experiments showed that one of the two S. mansoni populations (LE) generally outcompeted both the other S. mansoni population (BRE) and S. rodhaini. However, its impact on the microbiome varied depending on the co-infecting species (Fig. 3). Specifically, we hypothesize that S. rodhaini may exert a moderating influence on microbiome structure, potentially mitigating the dysbiotic effects of more virulent S. mansoni strains. The findings also suggest that even outcompeted or dormant parasite populations can shape microbiome dynamics through indirect interactions.

Figure 3: The bacterial aspect of the microbiome during the two co-infection experiments (S. mansoni population LE & S. mansoni population BRE, and S. mansoni population LE & S. rodhaini; as indicated by the color code) across 2, 10, and 40 daysPE (irrespective of final infection outcome). The alpha diversity as calculated through the faith’s phylogenetic diversity metric, based on mean values with error bars representing a single standard deviation. The line represents the pairwise comparison between 10 and 40 daysPE for the co-exposure of S. mansoni population LE - S. mansoni population BRE. Significance: <0.05=‘*’. — Figure 3: The bacterial aspect of the microbiome during the two co-infection experiments (*S. mansoni* population LE & *S. mansoni* population BRE, and *S. mansoni* population LE & *S. rodhaini*; as indicated by the color code) across 2, 10, and 40 daysPE (irrespective of final infection outcome). The alpha diversity as calculated through the faith’s phylogenetic diversity metric, based on mean values with error bars representing a single standard deviation. The line represents the pairwise comparison between 10 and 40 daysPE for the co-exposure of *S. mansoni* population LE - *S. mansoni* population BRE. Significance: <0.05=‘*’.

The data presented here expand the limited knowledge of the tripartite interaction among snails, parasites, and their microbiomes. They provide a foundation for targeted microbiome manipulation and transplant experiments aimed at resolving causal relationships between microbiome composition and parasite resistance in medically relevant snail hosts. We emphasize that infection status, parasite identity, and prior parasite exposure shape bacterial community structure, underscoring the importance of precise infection diagnostics in future microbiome–parasite studies.

“High-performance computing resources provided by the Flemish Supercomputer Center (VSC) were essential for processing and analyzing these large-scale 16S rRNA gene sequencing datasets. The computational power enabled efficient data cleaning and exportation of files for further analyses in R, while freeing up my personal laptop for other work.”

Read the full publication in Springer Nature here

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