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.