Snail juvenile growth rate as a rapid predictor of the transmission potential of parasitizing human schistosomes

Abstract

Host and parasite traits that are sensitive to environmental perturbations merit special attention in the mitigation of diseases. While life table experiments allow a practical evaluation of variability of these traits with environmental change, they are cost and resource intensive. Here, we use a model snail host-trematode parasite system to test the efficacy of an expeditious alternative. Rapidly changing host traits (such as juvenile growth rate) can be used as effective predictors of parasite transmission potential across a range of environmental factors. This approach can be applied to anticipate epidemiological changes under diverse environmental scenarios.

Keywords: Biomphalaria glabrata; Growth assay; Juvenile growth; Life table experiment; Parasite transmission; Schistosoma mansoni.

Figure 1:

Linear relationship between juvenile growth rate and fitness (intrinsic rate of increase, r) of uninfected B. glabrata snails. Juvenile growth rates (change in shell diameter cubed) were calculated over three timespans from the start of the experiment, (A) one week, (B) two weeks, and (C) three weeks, and averaged within treatment. Intrinsic growth rate (r, a product of snail survival and reproduction) was calculated for each treatment. Linear regressions are fitted for each experiment (in colors) and for all experiments combined (in black). Model fit outputs (R², AIC and p values) are calculated with the inclusion of experiment (n=6) as a random intercept.

Figure 2:

Linear relationship between juvenile growth rate of uninfected B. glabrata snails and S. mansoni parasite reproduction (cercarial production) of infected snails. Juvenile growth rates (change in shell diameter cubed) were calculated over three timespans from the start of the experiment, (A) one week, (B) two weeks, and (C) three weeks, and averaged within treatment. Weekly parasite reproduction (schistosome cercariae produced within 24 hours) was averaged for each treatment. Linear regressions are fitted for each experiment (in colors) and for all experiments combined (in black). Model fit outputs (R², AIC and p values) are calculated with the inclusion of experiment (n=8) as a random intercept and juvenile growth within the particular timespan (one, two or three week) as a random slope.