Unique genetic structure of the human tapeworm Dibothriocephalus latus from the Alpine lakes region – a successful adaptation?

Abstract

Dibothriocephalus latus is the most frequent causative agent of fish-borne zoonosis (diphyllobothriosis) in Europe, where it is currently circulating mainly in the Alpine lakes region (ALR) and Russia. Three mitochondrial genes (cox1, cob and nad3) and 6 microsatellite loci were analysed to determine how is the recently detected triploidy/parthenogenesis in tapeworms from ALR displayed at the DNA level. A geographically distant population from the Krasnoyarsk Reservoir in Russia (RU-KR) was analysed as a comparative population. One or 2 alleles of each microsatellite locus was detected in plerocercoids from RU-KR, corresponding to the microsatellite pattern of a diploid organism. In contrast, 1–3 alleles were observed in tapeworms from ALR, in accordance with their triploidy. The high diversity of mitochondrial haplotypes in D. latus from RU-KR implied an original and relatively stable population, but the identical structure of mitochondrial genes of tapeworms from ALR was probably a consequence of a bottleneck typical of introduced populations. These results indicated that the diploid/sexually reproducing population from RU-KR was ancestral, located within the centre of the distribution of the species, and the triploid/parthenogenetically reproducing subalpine population was at the margin of the distribution. The current study revealed the allelic structure of the microsatellite loci in the triploid tapeworm for the first time.

Testing the efficacy of different molecular tools for parasite conservation genetics: a case study using horsehair worms (Phylum Nematomorpha)

“…In our datasets, sampling bias for some taxa was present and can influence the results. For possible future studies on the conservation genetics of parasites, we give three suggestions that can help with evaluating a parasite’s conservation status: consider the target species’ ecologies, given that they can highly influence their population structure (Van Schaik et al ., 2015; Radac□ovská et al , 2022), Ne estimates (Criscione and Blouin, 2005; Criscione et al , 2005; Criscione, 2013, 2016; Strobel et al , 2019; Doña and Johnson, 2020) as well as the sampling strategy, given that some parasites have life cycles that can influence when and how to collect them (e.g., Van Schaik et al , 2015); try to get the geographically broadest and biggest sample size possible; for example, in this study a small sample size in the ddRADseq dataset did not allow us to estimate enough recent trends for two taxa, while the COXI dataset for A. taiwanensis was too biased to one area, which did not allow us to properly estimate the diversity of the species; define the molecular and bioinformatic tools used; a direct estimate of Ne for parasites can be tricky to calculate (Criscione, 2013; Strobel et al , 2019; Carlson et al , 2020). Given this, we suggest focusing on trends instead of raw numbers.…”

“…consider the target species’ ecologies, given that they can highly influence their population structure (Van Schaik et al ., 2015; Radac□ovská et al , 2022), Ne estimates (Criscione and Blouin, 2005; Criscione et al , 2005; Criscione, 2013, 2016; Strobel et al , 2019; Doña and Johnson, 2020) as well as the sampling strategy, given that some parasites have life cycles that can influence when and how to collect them (e.g., Van Schaik et al , 2015);…”

Testing the efficacy of different molecular tools for parasite conservation genetics: a case study using horsehair worms (Phylum: Nematomorpha)

“…In our datasets, sampling bias for some taxa was present and can influence the results. For possible future studies on the conservation genetics of parasites, we give 3 suggestions that can help with evaluating a parasite's conservation status: consider the target species' ecologies, given that they can highly influence their population genetic structure (van Schaik et al ., 2015 ; Radačovská et al ., 2022 ), Ne estimates (Criscione et al ., 2005 ; Strobel et al ., 2019 ) as well as the sampling strategy, given that some parasites have life cycles that can influence when and how to collect them (e.g. van Schaik et al ., 2015 ); try to get the geographically broadest and biggest sample size possible; for example, in this study a small sample size in the ddRADseq dataset did not allow us to estimate enough recent trends for 2 taxa, while the COXI dataset for A. taiwanensis was too biased to one area, which did not allow us to properly estimate the diversity of the species; define the molecular and bioinformatic tools used; a direct estimate of Ne for parasites can be tricky to calculate (e.g.…”

“…However, single-locus data are often the kinds of data that are the most available for parasites (Selbach et al ., 2019 ). Therefore, if budget and resources are limited, Sanger sequencing can be pursued (but see Radačovská et al ., 2022 for caveats with mitochondrial sequences in polyploid species). The use of depositories such as GenBank can be useful for retrieving previously released sequences and therefore increase both sample size and loci used while utilizing software such as BEAST2 that can use such data.…”

“…genetic diversity and trends of effective population size ( Ne ); Criscione et al ., 2005 ; Selbach et al ., 2019 ; Strobel et al ., 2019 ; Carlson et al ., 2020 ]. Genetic diversity may be linked to local adaption or life history, and its estimation may help to understand ecological traits or even infer potential population bottlenecks (van Schaik et al ., 2015 ; Tobias et al ., 2017 ; Radačovská et al ., 2022 ). Ne is known to greatly influence the genetic diversity and viability of populations (Criscione et al ., 2005 ; Pérez-Pereira et al ., 2022 ), but estimating it in parasites may come with some caveats depending on the studied system (Criscione et al ., 2005 ; Strobel et al ., 2019 ).…”