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Scalable isolation of soil genomic DNA from microbes to multicellular micro- and mesofauna

Velmala, S.; Tuomivirta, T.; Latvala, S.; Pitkanen, J.-M.; Pennanen, T.

2026-01-17 microbiology
10.64898/2026.01.16.699919 bioRxiv
Show abstract

Global initiatives emphasize the need for harmonized soil biodiversity assessments. Efficient DNA extraction methods that accommodate larger soil volumes are essential for capturing higher trophic levels than bacteria and fungi and supporting extensive sampling campaigns. We developed and evaluated a scalable, cost-efficient, and automation-ready soil DNA isolation technique alongside commercial protocols. Three starting soil amounts (0.25 g, 2.5 g, and 5 g) were tested using widely used Qiagen kits, the developed isolation method, or combinations thereof. Lysis volumes ranged from 800 {micro}l to 15 ml, and purification employed either silica membrane or carboxyl-coated magnetic beads. Four different types of soil, both agricultural and forest soil, samples were sequenced on an Illumina MiSeq platform using universal eukaryotic primers targeting the 18S rRNA SSU region, enabling detection of non-fungal eukaryotes such as soil mesofauna and protozoa. The developed protocol, which combined a tenfold increase in sample volume with hybrid purification steps, yielded the highest DNA recovery and consistently improved detected richness in several soil types. Species richness patterns varied by soil type and organism group: for eukaryotes and protozoa, commercial maxiprep methods along with the combination methods outperformed the miniprep approach in agricultural soils, while the developed technique excelled in coarse xeric forest soils. For metazoans, larger extraction volumes were associated with higher richness in forest soils. Our findings indicate that at least a tenfold increase in soil input compared to conventional 0.2-0.3 g is required to reliably capture mesofaunal diversity, with preliminary evidence suggesting further benefits at 20-fold volumes. We confirm that extraction volume is a key factor shaping detection of both soil metazoan and protozoan community compositions, with effects varying by soil type and organism group. The developed scalable approach offers a practical solution for large-scale soil biodiversity assessments, aligning with global monitoring goals and enabling integration of higher trophic levels into eDNA-based frameworks.

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