DNA Metabarcoding for the Characterization of Terrestrial Microbiota—Pitfalls and Solutions

Abstract

Soil-borne microbes are major ecological players in terrestrial environments since they cycle organic matter, channel nutrients across trophic levels and influence plant growth and health. Therefore, the identification, taxonomic characterization and determination of the ecological role of members of soil microbial communities have become major topics of interest. The development and continuous improvement of high-throughput sequencing platforms have further stimulated the study of complex microbiota in soils and plants. The most frequently used approach to study microbiota composition, diversity and dynamics is polymerase chain reaction (PCR), amplifying specific taxonomically informative gene markers with the subsequent sequencing of the amplicons. This methodological approach is called DNA metabarcoding. Over the last decade, DNA metabarcoding has rapidly emerged as a powerful and cost-effective method for the description of microbiota in environmental samples. However, this approach involves several processing steps, each of which might introduce significant biases that can considerably compromise the reliability of the metabarcoding output. The aim of this review is to provide state-of-the-art background knowledge needed to make appropriate decisions at each step of a DNA metabarcoding workflow, highlighting crucial steps that, if considered, ensures an accurate and standardized characterization of microbiota in environmental studies.

Multiple species‐specific molecular markers using nanofluidic array as a tool to detect prey DNA from carnivore scats

“…When investigating generalist species or predators with unknown diets, universal primers followed by DNA sequencing have been frequently used in both vertebrates (De Barba et al., 2014 ; Jarman et al., 2013 ; Shutt et al., 2020 ; Šturm et al., 2021 ) and invertebrates (Pons, 2006 ; Symondson, 2002 ). Metabarcoding with next‐generation sequencing allows for high‐throughput identification of several species by simultaneously sequencing DNA from multiple species in environmental samples (eDNA; Francioli et al., 2021 ; Taberlet et al., 2012 ). In prey detection with generic primers, the amplifiable host DNA can however largely outnumber the presence of prey DNA (Krehenwinkel et al., 2017 ), and strategies to prevent host DNA amplification may be necessary, for example, by using predator‐specific blocking primers (Krehenwinkel et al., 2019 ; Shi et al., 2021 ; Vestheim & Jarman, 2008 ).…”

Mycobiome and Cancer: What Is the Evidence?

“…The use of ITS2 subregion may offer a more ubiquitous primer location and reduced length variability, resulting in fewer taxonomic errors in comparison to ITS1 [79]. Nevertheless, conflicting results have been emerged in the comparisons between the sub-regions ITS1 or ITS2 for the analyses of fungal profiles [83]. The advantages of using the full ITS region instead of ITS1 or ITS2 with third-generation HTS platforms such as Oxford Nanopore or Pacific Biosciences include the higher taxonomic discrimination and the decreased amplification of non-living microorganisms; however, a shortcoming is the low performance with poor-quality samples due to the DNA deterioration, where full ITS sequencing may be impossible [1].…”

“…HTS significant biases may happen from additive systematic and random errors, which include, among others, biases in genetic material extraction, markers, primers, PCR, library preparation, sequencing, bioinformatics analysis, index-switching, low clustering, unequal sequencing depth, etc. [1,83]. Moreover, DNA metabarcoding for microbiota analyses presents significant shortcomings, including the variability of copy numbers of the targeted barcodes in microorganism genomes, the poor taxonomic discrimination at the species level for some microbiota, and errors in the taxonomic assignment of sequences based on the selected variable region [83].…”

“…[1,83]. Moreover, DNA metabarcoding for microbiota analyses presents significant shortcomings, including the variability of copy numbers of the targeted barcodes in microorganism genomes, the poor taxonomic discrimination at the species level for some microbiota, and errors in the taxonomic assignment of sequences based on the selected variable region [83].…”

Molecular Screening of Microorganisms Associated with Discolored Wood in Dead European Beech Trees Suffered from Extreme Drought Event Using Next Generation Sequencing

“…Thus, NGS would be a prime technology to identify the status quo of an infection. Nevertheless, biases introduced by primer selection and PCR can be considered as important shortcomings of NGS [16]. For examples, universal ITS primer sets for fungi may have limited ability to identify plant pathogens of different taxa, especially oomycetes [17].…”