New Insights Into Nematode DNA-metabarcoding as Revealed by the Characterization of Artificial and Spiked Nematode Communities

Abstract

Nematodes are ideal biological indicators to monitor soil biodiversity and ecosystem functioning. For this reason, they have been receiving increasing attention from a broad range of scientists. The main method to characterize soil nematode communities until at least genus level is still based on microscopic observations of nematode morphology. Such an approach is time-consuming, labor-intensive, and requires specialized personnel. The first studies on the potential use of DNA-metabarcoding to characterize nematode communities showed some shortcomings: under- or overestimation of species richness caused by failure to detect a number of nematode species or caused by intraspecific sequence variants increasing the number of OTUs (operational taxonomic units) or ‘molecular’ species, and flaws in quantification. We set up experiments to optimize this metabarcoding approach. Our results provided new insights such as the drastic effect of different DNA-extraction methods on nematode species richness due to variation in lysis efficacy. Our newly designed primer set (18S rRNA gene, V4-V5 region) showed in silico an improved taxonomic coverage compared with a published primer set (18S rRNA gene, V6-V8 region). However, results of DNA-metabarcoding with the new primer set showed less taxonomic coverage, and more non-nematode reads. Thus, the new primer set might be more suitable for whole soil faunal analysis. Species-specific correction factors calculated from a mock community with equal amounts of different nematode species were applied on another mock community with different amounts of the same nematode species and on a biological sample spiked with four selected nematode species. Results showed an improved molecular quantification. In conclusion, DNA-metabarcoding of soil nematode communities is useful for monitoring shifts in nematode composition but the technique still needs further optimization to enhance its precision.

Comparison of morphological, DNA barcoding, and metabarcoding characterizations of freshwater nematode communities

“…However, we found that, especially for the 18S gene region, the performance of dada2 was not satisfactory, as it led to the identification of only six ASVs. A similar result was reported in another nematode study, in which a reduced taxonomic assignment was obtained using the dada2 pipeline (Waeyenberge, Sutter, Viaene, & Haegeman, ). As the dada2 pipeline uses a more stringent filtering process than the standard OTU‐pipeline, it might omit several sequences maintained in the OTU approach, resulting in a much lower number of reads in the final ASV table construction (OTU: 10,150 reads vs. ASV: 1,015 reads).…”

Effects of synthetic fertilizer and farm compost on soil nematode community in long-term crop rotation plots: A morphological and metabarcoding approach

“…Molecular characterisation of the nematode community was carried out following the protocol described in Waeyenberge et al [31]. Briefly, metabarcoding analysis was carried out by extracting DNA using the DNeasy Blood and Tissue Kit (Qiagen).…”

“…Briefly, metabarcoding analysis was carried out by extracting DNA using the DNeasy Blood and Tissue Kit (Qiagen). Amplicon libraries of approximately 490bp were produced with the Illumina Nextera XT Indext Kit v2 using 18S rRNA gene primers (NemFopt and 18Sr2bRopt) and sequenced with Illumina MiSeq v3 (2x300 bp) as described in Waeyenberge et al [31]. The raw reads were uploaded to the Sequence Read Archive (SRA) of NCBI under BioProject PRJNA607002.…”

“…On the other hand, several nematode families appeared to be underrepresented in the metabarcoding data as compared to the morphological data, such as Tylenchidae, Pratylenchidae and Rhabditidae. It is likely that the read counts in the metabarcoding data are skewed by body size, such as is seen with the Mononchidae, Anatonchidae or Aporcelaimidae, or by DNA extraction being more successful from certain nematodes than others [31,57,58].…”

“…Furthermore, and most importantly, metabarcoding is unable to provide absolute quantitative data on the nematode community [60]. The use of a correction factor has been suggested as a method to estimate abundances from metabarcoding data [31], but this still requires further standardization and investigation to determine the classification level at which the correction factor can be applied. Nevertheless, despite the significant methodological differences between morphological and metabarcoding methods actual differences in the interpretation of the results are limited.…”