Metabarcoding proof
The MiniB18S_81 mini-barcode provided high quality sequences. On average, 66% of forward/reverse sequences combined showed less than one expected error. Moreover, on average, 80.4% of reads were assigned to an OTU with 97% identity. Taking as a reference dataset the Silva 18S v123 dataset and RDP 16S v16 training dataset combined, the MiniB18S_81 mini-barcode served to identify 1367 of 1384 OTUs recovered as eukaryotic organisms with certainty, whereas no Bacteria or Archaea were thus identified.
Our metabarcoding analysis results were also consistent with the data obtained through ”in silico” PCR. As ”in silico” (Table 2), the MiniB18S_81 mini-barcode showed an excellent taxonomic resolution capacity at the order level for Apicomplexa, Arthropoda, Nematoda and Platyhelminthes, while for plants it only showed good resolution at the class level (Table 3). In the Apicomplexa phylum, this mini-barcode also offered good resolution capacity at the family and genus levels (Table 3). However, no results were obtained at the family and genus levels for various phyla, due to the lack of information in the reference dataset regarding these taxonomic levels and phyla (Table 3). We did not include the Annelida and Mollusca phyla in Table 3 as only two OTUs of each were detected in this analysis. Nevertheless, this mini-barcode also showed good taxonomic resolution at the class level in Ascomycota and Basidiomycota (Table 3). In contrast, its taxonomic resolution of the Vertebrata phylum was poor, as expected considering the results of the ”in silico” approach. In addition, this barcode was capable of unambiguously identifying some genera. Among these, we should highlightCryptosporidium spp. and Blastocystis spp., as two groups of organisms generating much interest because of their impacts on human health.
In addition, the use of this mini-barcode rendered a percentage of reads of each taxon in relation to the total reads obtained for each sample (Figure 3). We were also able to estimate the percentage of reads of a specific taxon associated with diet in relation to the total reads of the taxon component of the diet, or the percentage of reads of one protozoan parasite in relation to the total reads of protozoans in the gut microbiota. This type of information gives an idea of the contribution of each taxon to the gut microbiota, diet or parasite community.