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Trematode genetic patterns at host individual and population scales provide insights about infection mechanisms

Published online by Cambridge University Press:  20 October 2023

Simão Correia*
Affiliation:
Department of Biology, CESAM, University of Aveiro, 3810-193 Aveiro, Portugal Aquatic and Animal Health Group, CIIMAR, University of Porto, 4450-208 Matosinhos, Portugal Department of Zoology, Genetics and Physical Anthropology, Campus Terra, University of Santiago de Compostela, 27002 Lugo, Spain Department of Zoology, University of Otago, 9054 Dunedin, New Zealand
Sergio Fernández-Boo
Affiliation:
Aquatic and Animal Health Group, CIIMAR, University of Porto, 4450-208 Matosinhos, Portugal
Luísa Magalhães
Affiliation:
Department of Biology, CESAM, University of Aveiro, 3810-193 Aveiro, Portugal
Xavier de Montaudouin
Affiliation:
CNRS, UMR EPOC, Station Marine, University of Bordeaux, F-33120 Arcachon, France
Guillemine Daffe
Affiliation:
Université de Bordeaux, CNRS, Observatoire Aquitain des Sciences de l'Univers, F-33615 Pessac, France
Robert Poulin
Affiliation:
Department of Zoology, University of Otago, 9054 Dunedin, New Zealand
Manuel Vera*
Affiliation:
Department of Zoology, Genetics and Physical Anthropology, Campus Terra, University of Santiago de Compostela, 27002 Lugo, Spain
*
Corresponding authors: Simão Correia; Email: simaocorreia@ua.pt; simaopedro.correia@usc.es; Manuel Vera; Email: manuel.vera@usc.es
Corresponding authors: Simão Correia; Email: simaocorreia@ua.pt; simaopedro.correia@usc.es; Manuel Vera; Email: manuel.vera@usc.es

Abstract

Multiple parasites can infect a single host, creating a dynamic environment where each parasite must compete over host resources. Such interactions can cause greater harm to the host than single infections and can also have negative consequences for the parasites themselves. In their first intermediate hosts, trematodes multiply asexually and can eventually reach up to 20% of the host's biomass. In most species, it is unclear whether this biomass results from a single infection or co-infection by 2 or more infective stages (miracidia), the latter being more likely a priori in areas where prevalence of infection is high. Using as model system the trematode Bucephalus minimus and its first intermediate host cockles, we examined the genetic diversity of the cytochrome c oxidase subunit I region in B. minimus from 3 distinct geographical areas and performed a phylogeographic study of B. minimus populations along the Northeast Atlantic coast. Within localities, the high genetic variability found across trematodes infecting different individual cockles, compared to the absence of variability within the same host, suggests that infections could be generally originating from a single miracidium. On a large spatial scale, we uncovered significant population structure of B. minimus, specifically between the north and south of Bay of Biscay. Although other explanations are possible, we suggest this pattern may be driven by the population structure of the final host.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press
Figure 0

Figure 1. Geographical location of the Cerastoderma edule cockle beds sampled for the study of Bucephalus minimus genetic variability at host level (Aveiro, Baiona and Arcachon [in italics]) and for phylogeographic analysis. *Cockle beds sampled for the first time in this study.

Figure 1

Table 1. Accession number for B. minimus COI gene DNA sequences downloaded (with reference) and deposited (in bold) in GenBank

Figure 2

Table 2. Coordinates of each cockle bed, the number of analysed cockles (Ncockles), number of parasites sequenced (NB. minimus), prevalence of B. minimus, number of haplotypes (k), number of polymorphic sites (PS) and haplotype composition (between parentheses the number of individuals bearing the same haplotype when different from one)

Figure 3

Figure 2. Haplotype network of Bucephalus minimus samples from Aveiro (Portugal), Baiona (Spain) and Arcachon (France) based on genetic distance (number of base pair differences) of cytochrome c oxidase subunit 1 (COI) gene sequences. Different haplotypes with respective names are represented by circles, with circle size proportional to observed frequency. Inferred mutation steps are shown by black dots. Colours depict samples taken from the same cockle.

Figure 4

Table 3. Haplotype frequency for B. minimus COI gene per cockle bed including haplotype diversity (h ± standard deviation) and nucleotide diversity (π ± standard deviation)

Figure 5

Figure 3. Haplotype network of Bucephalus minimus based on genetic distance (number of base pair differences) of cytochrome c oxidase subunit 1 (COI) gene sequences across 11 beds of Cerastoderma edule where Bucephalus minimus specimens were collected. Different haplotypes with respective names are represented by circles, with circle size proportional to observed frequency. Inferred mutation steps are shown by black dots. Colours depict sample location.

Figure 6

Figure 4. Maximum likelihood phylogenetic tree based on cytochrome c oxidase subunit I (COI) gene sequences of Bucephalus minimus haplotypes from this study and retrieved from GenBank database. Rhipodocotyle sp. and Himasthla quissetensis haplotypes were used as outgroups. Numbers at nodes represent the percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) using neighbour-joining and maximum likelihood methods (NJ/ML). The scale bar indicates the distances in substitutions per nucleotide.

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