Biology subjects

Chaparro, C.

Publications and source records attributed to Chaparro, C..

3 recordsLinked to original sources

bioRxiv2018

Whole genome sequencing and morphological analysis of the human-infecting schistosome emerging in Europe reveals a complex admixture between Schistosoma haematobium and Schistosoma bovis parasites.

Schistosomes cause schistosomiasis, the worlds second most important parasitic disease after malaria. A peculiar feature of schistosomes is their ability to produce viable and fertile hybrids. Originally only present in the tropics, schistosomiasis is now also endemic in Europe. Based on two genetic markers the European species had been identified as a hybrid between the ruminant-infective Schistosoma bovis and the human-infective Schistosoma haematobium.\n\nHere we describe for the first time the genomic composition of the European schistosome hybrid (77% of S. haematobium and 23% of S. bovis origins), its morphometric parameters and its compatibility with the European vector snail and intermediate host Compatibility is a key parameter for the parasites life cycle progression. We also show that egg morphology (a classical diagnostic parameter) does not allow for differential diagnosis while genetic tests do so. Additionally, we performed genome assembly improvement and annotation of S. bovis, the parental species for which no satisfactory genome assembly was available.\n\nFor the first time since the discovery of hybrid schistosomes, these results reveal at the whole genomic level a complex admixture of parental genomes highlighting (i) the high permeability of schistosomes to other species alleles, and (ii) the importance of hybrid formation for pushing species boundaries not only conceptionally but also geographically.

genomics↗

bioRxiv2018

Sympatric and allopatric evolutionary contexts shape differential immune response in Biomphalaria / Schistosoma interaction

Selective pressures between hosts and their parasites can result in reciprocal evolution or adaptation of specific life history traits. Local adaptation of resident hosts and parasites should lead to host-parasite systems performing better in sympatry when compared to allopatry. Between-population variations in parasite infectivity/virulence and host defence/resistance, referred to as compatibility phenotype, were often the proxy used to analyse sympatric or allopatric adaptation. Nevertheless, some reported cases exist where allopatric host-parasite systems demonstrate compatibility phenotypes similar or greater than the one observed in sympatry. In these cases, the role of local adaptation is worth considering. Here, we study the interaction between Schistosoma and its vector snail Biomphalaria in which such a discrepancy in local versus foreign compatibility phenotype has been observed. Herein, we developed an integrative approach to investigate sympatric and allopatric interaction processes and link the underlying molecular mechanisms to the resulting phenotypes. Using comparative \"omics\" approaches joined to analysis of life history traits (immune cellular response, mortality, prevalence and compatibility) we tried to bridge the gap of knowledge that exists for connecting local adaptation observations to molecular phenotypes in Schistosoma/Biomphalaria interactions.\n\nWe found that despite displaying similar prevalence phenotypes, parasite infection triggered an immune suppression in snails living in sympatry, while it activated an immune response for those living in allopatry. Dual-comparative molecular analyses revealed that parasite infection causes immune suppression in sympatry. miRNAs were used to hijack the hosts immune response, allowing sympatric parasites to initiate their developmental program earlier and more efficiently.\n\nWe show that despite having similar prevalence phenotypes, sympatric and allopatric snail-Schistosoma interactions displayed a strongly different immunobiological molecular dialogue. The ability of allopatric pathogens to adapt rapidly and efficiently to new hosts could have critical consequences on disease emergence and risk of schistosomiasis outbreaks. These observations would have important consequences in term of schistosomiasis disease control.

immunology↗

bioRxiv2017

Notos - a Galaxy tool to analyze CpN observed expected ratios for inferring DNA methylation types

BackgroundDNA methylation patterns store epigenetic information in the vast majority of eukaryotic species. The relatively high costs and technical challenges associated with the detection of DNA methylation however have created a bias in the number of methylation studies towards model organisms. Consequently, it remains challenging to infer kingdom-wide general rules about the functions and evolutionary conservation of DNA methylation. Methylated cytosine is often found in specific CpN dinucleotides, and the frequency distributions of, for instance, CpG observed/expected (CpG o/e) ratios have been used to infer DNA methylation types based on higher mutability of methylated CpG.\n\nResultsPredominantly model-based approaches essentially founded on mixtures of Gaussian distributions are currently used to investigate questions related to the number and position of modes of CpG o/e ratios. These approaches require the selection of an appropriate criterion for determining the best model and will fail if empirical distributions are complex or even merely moderately skewed. We use a kernel density estimation (KDE) based technique for robust and precise characterization of complex CpN o/e distributions without a priori assumptions about the underlying distributions.\n\nConclusionsWe show that KDE delivers robust descriptions of CpN o/e distributions. For straightforward processing, we have developed a Galaxy tool, called Notos and available at the ToolShed, that calculates these ratios of input FASTA files and fits a density to their empirical distribution. Based on the estimated density the number and shape of modes of the distribution is determined, providing a rational for the prediction of the number and the types of different methylation classes. Notos is written in R and Perl.

bioinformatics↗