five

Fishing Active Soil Protists

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/sra/ERP182506
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Understanding the diversity and ecological roles of soil protists is hindered by methodological limitations in both molecular detection and the isolation of actively growing taxa from complex soil matrices. Here, two complementary methodological advances designed are presented to overcome these constraints: (1) a new pair of primers optimized for near full-length amplification of the eukaryotic rRNA operon in soil protists, and (2) a 200 µm mesh bag microcosm approach for selectively capturing active protist communities in situ. The primer pair was developed through extensive in silico evaluation of previously published 18S and 28S primer sets against the PR2 and EUKARYOME databases, followed by optimization to maximize protist coverage, particularly for underrepresented Amoebozoa, while minimizing amplification of animal, fungal and plant sequences. Empirical validation using a five-strain Amoebozoa MOCK community confirmed high amplification efficiency and sequencing accuracy (> 99% similarity to references) on the PacBio Revio platform. To process long-read data, a custom workflow was integrated in an already developed amplicon pipeline (https://github.com/lentendu/DeltaMP), combining quality correction, primer detection, and multi-step denoising and clustering to generate high-confidence operational taxonomic units. Application of this workflow to temperate forest soil samples demonstrated that while bulk soils are dominated by parasitic protists (mainly Apicomplexa), the 200 µm mesh bags promoted colonization by metabolically active predatory protists such as Cercozoa and Ciliophora. Together, these methods enable simultaneous recovery of near-complete rRNA operons and ecological partitioning of active versus dormant protist assemblages, offering a robust framework for future studies of soil microbial food webs and nutrient cycling.
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2026-01-05
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