New pathologies are causing dramatic declines and extinctions of multiple amphibian species. In 2013, we found fire salamanders with undescribed cysts at the throat level in one population in Northern Italy, which existence is not reported in amphibians yet. With the aim of describing this novel phenomenon, we performed repeated surveys to assess the frequency of affected salamanders from 2014 to 2020, and integrated morphological, histological and molecular analyses. Cysts affected up to 22 % of salamanders of the study population and started spreading to nearby populations. Cysts are formed by mucus surrounding cells about 10 μm long, characterized by numerous undulipodia. Morphological and genetic analyses did not yield a clear match with any described organism or salamander cell. The occurrence of these cysts calls for more studies on the origin and impact on wild populations.

A document by Aurélie Bonin. Click on the document to view its contents.

Clustering approaches are pivotal to handle the many sequence variants obtained in DNA metabarcoding datasets, therefore they have become a key step of metabarcoding analysis pipelines. Clustering often relies on a sequence similarity threshold to gather sequences in Molecular Operational Taxonomic Units (MOTUs), each of which ideally representing a homogeneous taxonomic entity, e.g. a species or a genus. However, the choice of the clustering threshold is rarely justified, and its impact on MOTU over-splitting or over-merging even less tested. Here, we evaluated clustering threshold values for several metabarcoding markers under different criteria: limitation of MOTU over-merging, limitation of MOTU over-splitting, and trade-off between over-merging and over-splitting. We extracted sequences from a public database for eigt markers, ranging from generalist markers targeting Bacteria or Eukaryota, to more specific markers targeting a class or a subclass (e.g. Insecta, Oligochaeta). Based on the distributions of pairwise sequence similarities within species and within genera, and on the rates of over-splitting and over-merging across different clustering thresholds, we were able to propose threshold values minimizing the risk of over-splitting, that of over-merging, or offering a trade-off between the two risks. For generalist markers, high similarity thresholds (0.96-0.99) are generally appropriate, while more specific markers require lower values (0.85-0.96). These results do not support the use of a fixed clustering threshold. Instead, we advocate a careful examination of the most appropriate threshold based on the research objectives, the potential costs of over-splitting and over-merging, and the features of the studied markers.