Non-Invasive Sampling of Schistosomes from Humans Requires Correcting for Family Structure

For ethical and logistical reasons, population-genetic studies of parasites often rely on the non-invasive sampling of offspring shed from their definitive hosts. However, if the sampled offspring are naturally derived from a small number of parents, then the strong family structure can result in biased population-level estimates of genetic parameters, particularly if reproductive output is skewed. Here, we document and correct for the strong family structure present within schistosome offspring (miracidia) that were collected non-invasively from humans in western Kenya. By genotyping 2,424 miracidia from 12 patients at 12 microsatellite loci and using a sibship clustering program, we found that the samples contained large numbers of siblings. Furthermore, reproductive success of the breeding schistosomes was skewed, creating differential representation of each family in the offspring pool. After removing the family structure with an iterative jacknifing procedure, we demonstrated that the presence of relatives led to inflated estimates of genetic differentiation and linkage disequilibrium, and downwardly-biased estimates of inbreeding coefficients (F[subscript IS]). For example, correcting for family structure yielded estimates of F[[subscript ST] among patients that were 27 times lower than estimates from the uncorrected samples. These biased estimates would cause one to draw false conclusions regarding these parameters in the adult population. We also found from our analyses that estimates of the number of full sibling families and other genetic parameters of samples of miracidia were highly intercorrelated but are not correlated with estimates of worm burden obtained via egg counting (Kato-Katz). Whether genetic methods or the traditional Kato-Katz estimator provide a better estimate of actual number of adult worms remains to be seen. This study illustrates that family structure must be explicitly accounted for when using offspring samples to estimate the genetic parameters of adult parasite populations

Two-year longitudinal survey reveals high genetic diversity of Schistosoma mansoni with adult worms surviving praziquantel treatment at the start of mass drug administration in Uganda

Background: A key component of schistosomiasis control is mass drug administration with praziquantel. While control interventions have been successful in several endemic regions, mass drug administration has been less effective in others. Here we focus on the impact of repeated praziquantel treatment on the population structure and genetic diversity of Schistosoma mansoni. Methods: We examined S. mansoni epidemiology, population genetics, and variation in praziquantel susceptibility in parasites isolated from children across three primary schools in a high endemicity region at the onset of the Ugandan National Control Programme. Children were sampled at 11 timepoints over two years, including one week and four weeks post-praziquantel treatment to evaluate short-term impacts on clearance and evidence of natural variation in susceptibility to praziquantel. Results: Prevalence of S. mansoni was 85% at baseline. A total of 3576 miracidia larval parasites, isolated from 203 individual children, were genotyped at seven loci. Overall, genetic diversity was high and there was low genetic differentiation, indicating high rates of parasite gene flow. Schistosome siblings were found both pre-treatment and four weeks post-treatment, demonstrating adult worms surviving treatment and natural praziquantel susceptibility variation in these populations at the beginning of mass drug administration. However, we did not find evidence for selection on these parasites. While genetic diversity decreased in the short-term (four weeks post-treatment), diversity did not decrease over the entire period despite four rounds of mass treatment. Furthermore, within-host genetic diversity was affected by host age, host sex, infection intensity and recent praziquantel treatment. Conclusions: Our findings suggest that praziquantel treatments have short-term impacts on these parasite populations but impacts were transient and no long-term reduction in genetic diversity was observed. High gene flow reduces the likelihood of local adaptation, so even though parasites surviving treatment were observed, these were likely to be diluted at the beginning of the Ugandan National Control Programme. Together, these results suggest that MDA in isolation may be insufficient to reduce schistosome populations in regions with high genetic diversity and gene flow

Praziquantel sensitivity of Kenyan Schistosoma mansoni isolates and the generation of a laboratory strain with reduced susceptibility to the drug

Schistosomiasis is a neglected tropical disease caused by blood-dwelling flukes of the genus Schistosoma. While the disease may affect as many as 249 million people, treatment largely relies on a single drug, praziquantel. The near exclusive use of this drug for such a prevalent disease has led to concerns regarding the potential for drug resistance to arise and the effect this would have on affected populations. In this study, we use an in vitro assay of drug sensitivity to test the effect of praziquantel on miracidia hatched from eggs obtained from fecal samples of Kenyan adult car washers and sand harvesters as well as school children. Whereas in a previous study we found the car washers and sand harvesters to harbor Schistosoma mansoni with reduced praziquantel sensitivity, we found no evidence for the presence of such strains in any of the groups tested here. Using miracidia derived from seven car washers to infect snails, we used the shed cercariae to establish a strain of S. mansoni with significantly reduced praziquantel sensitivity in mice. This was achieved within 5 generations by administering increasing doses of praziquantel to the infected mice until the parasites could withstand a normally lethal dose. This result indicates that while the threat of praziquantel resistance may have diminished in the Kenyan populations tested here, there is a strong likelihood it could return if sufficient praziquantel pressure is applied

Non-Invasive Sampling of Schistosomes from Humans Requires Correcting for Family Structure

<div><p>For ethical and logistical reasons, population-genetic studies of parasites often rely on the non-invasive sampling of offspring shed from their definitive hosts. However, if the sampled offspring are naturally derived from a small number of parents, then the strong family structure can result in biased population-level estimates of genetic parameters, particularly if reproductive output is skewed. Here, we document and correct for the strong family structure present within schistosome offspring (miracidia) that were collected non-invasively from humans in western Kenya. By genotyping 2,424 miracidia from 12 patients at 12 microsatellite loci and using a sibship clustering program, we found that the samples contained large numbers of siblings. Furthermore, reproductive success of the breeding schistosomes was skewed, creating differential representation of each family in the offspring pool. After removing the family structure with an iterative jacknifing procedure, we demonstrated that the presence of relatives led to inflated estimates of genetic differentiation and linkage disequilibrium, and downwardly-biased estimates of inbreeding coefficients (F_IS). For example, correcting for family structure yielded estimates of F_ST among patients that were 27 times lower than estimates from the uncorrected samples. These biased estimates would cause one to draw false conclusions regarding these parameters in the adult population. We also found from our analyses that estimates of the number of full sibling families and other genetic parameters of samples of miracidia were highly intercorrelated but are not correlated with estimates of worm burden obtained via egg counting (Kato-Katz). Whether genetic methods or the traditional Kato-Katz estimator provide a better estimate of actual number of adult worms remains to be seen. This study illustrates that family structure must be explicitly accounted for when using offspring samples to estimate the genetic parameters of adult parasite populations.</p></div

Relationships between A. allelic richness and the standardized number of full sibling families estimated by kinship analysis, B. the standardized number of full sibling families and the effective number of breeders estimated by the sibling assignment method (SA) and the linkage disequilibrium method (LDNE), C. allelic richness and the effective number of breeders.

<p>Relationships between A. allelic richness and the standardized number of full sibling families estimated by kinship analysis, B. the standardized number of full sibling families and the effective number of breeders estimated by the sibling assignment method (SA) and the linkage disequilibrium method (LDNE), C. allelic richness and the effective number of breeders.</p

Descriptive statistics for 12 infrapopulations of <i>Schistosoma mansoni</i> derived from human patients in Kenya.

<p>+ = HIV positive, n = number of miracidia sampled, OPF n = number of miracidia sampled in the one-per-family correction, AR = allelic richness rarified, VMR = variance to mean ratio of family size, FSF = number of full sibling families, % = the percent of miracidia belonging to a family of 4 or greater, N_bSA = effective number of breeders N_b estimated by the sibling assignment method, N_bLDNe = effective number of breeders N_b estimated by LDNe.</p

Calculations of pairwise F_ST between A. simulated and B. empirical schistosome infrapopulations of 12 human patients as measured by sampling schistosome offspring rather than adults.

<p>Both plots show the pairwise comparisons of the raw, uncorrected samples (blue) and those of the same samples corrected using the one-per-family method described in the manuscript (green). Pairwise comparisons are ordered by F_ST value on the X-axis. Note that in both plots, the F_ST values of the corrected dataset are lower (or equal to) the F_ST values from the raw samples showing the predicted inflation caused by family structure in the raw samples. Also note the mean F_ST indicated by the dashed line is slightly greater than 0 for the empirical samples, which suggests that a small amount of residual F_ST was not removed by the correction. Whether this represents true F_ST among patients or a failure of COLONY to accurately identify all sibship is unknown.</p

Relationship between the amount of family structure as quantified by the variance to mean ratio of family size (VMR) in samples of <i>Schistosoma mansoni</i> offspring collected from 12 patients and A. the estimation of the number of full sibling families (corrected for sample size) as determined by sibship analysis and B. The effective number of breeders N_b calculated using the sibling assignment method (SA) or the linkage disequilibrium method (LDNE).

<p>Relationship between the amount of family structure as quantified by the variance to mean ratio of family size (VMR) in samples of <i>Schistosoma mansoni</i> offspring collected from 12 patients and A. the estimation of the number of full sibling families (corrected for sample size) as determined by sibship analysis and B. The effective number of breeders N_b calculated using the sibling assignment method (SA) or the linkage disequilibrium method (LDNE).</p

Linkage disequilibrium (LD) between pairs of microsatellite loci within samples of schistosome offspring collected from 12 human patients compared to the amount of family structure present in each dataset.

<p>Amount of LD is represented by the proportion of locus pairs in disequilibrium (see text for statistical tests). Family structure is represented by the log-transformed variance to mean ratio of family size (VMR), but plotted on their actual values. LD is shown for each raw dataset (orange), samples corrected for family structure using the one-per-family approach (see text) (green), and the raw samples that were resampled to equal the sample size of the corrected samples (blue). Note the positive relationship between LD and VMR in the raw samples and the near-complete reduction in the corrected samples.</p