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

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.

Automated summary

Soil-borne microbes play a crucial role in terrestrial ecosystems by cycling organic matter, transporting nutrients between trophic levels, and impacting plant growth. The advancement of high-throughput sequencing platforms has allowed for in-depth study of complex microbiota in soils and plants, with DNA metabarcoding emerging as a powerful and cost-effective method for characterizing microbiota in environmental samples. However, the processing steps involved in DNA metabarcoding may introduce biases that compromise the reliability of the results, making it important to consider crucial steps to ensure an accurate and standardized characterization of microbiota in environmental studies.