Impacts of Sampling Design on Estimates of Microbial Community Diversity and Composition in Agricultural Soils

Castle, Sarah C.; Samac, Deborah A.; Sadowsky, Michael J.; Rosen, Carl J.; Gutknecht, Jessica; Kinkel, Linda L.

doi:10.1007/s00248-019-01318-6

Cited by 17 publications

(15 citation statements)

References 43 publications

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“…We demonstrate that different OTU generation methods applied to the same long amplicon eDNA dataset affect the documented composition of soil microeukaryotic communities. Similarly, earlier studies have reported that large scale ecological patterns are recovered irrespective of the OTU or ASV generation method or clustering threshold (for short read data) (Glassman & Martiny, 2018), sequencing technology (Furneaux et al, 2021) or sampling effort (Castle et al, 2019). We conclude that large scale ecological patterns are robustly recovered irrespective of the OTU or ASV generation method applied.…”

Section: Discussionsupporting

confidence: 84%

Soil eukaryote community shift but not composition is consistently recovered by different OTU inference methods applied to long read metabarcoding data

Sahraei

Furneaux

Kluting

et al. 2021

Preprint

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Long amplicon metabarcoding has opened the door for phylogenetic analysis of the largely unknown communites of microeukaryotes in soil. Here, we amplified and sequenced the ITS and LSU regions of the rDNA operon (around 1500 bp) from grassland soils using PacBio SMRT sequencing and evaluated the performance of three different methods for generation of operational taxonomic units (OTUs). The field site at Kungsängen Nature Reserve has drawn frequent visitors since Linnaeus’s time, and its species rich vegetation includes the largest population of Fritillaria meleagris in Sweden. To test the effect of different OTU generation methods, we sampled soils across an abrupt moisture transition that divides the meadow community into a Carex acuta dominated plant community with low species richness in the wetter part, which is visually distinct from the mesic-dry part that has a species rich grass-dominated plant community including a high frequency of F. meleagris. We used the moisture and plant community transition as a framework to investigare how detected belowground microeukaryotic community composition was influenced by OTU generation methods. Soil communities in both moisture regimes were dominated by protists, a large fraction of which were taxonomically assigned to Ciliophora (Alveolata) while 30-40% of all reads were assigned to kingdom Fungi. Ecological patterns were consistently recovered irrespective of OTU generation method used. However, different methods strongly affect richness estimates and the taxonomic and phylogenetic resolution of the characterized community with implications for how well members of the microeukaryotic communities can be recognized in the data.

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Section: Discussionsupporting

confidence: 84%

Soil eukaryote community shift but not composition is consistently recovered by different OTU inference methods applied to long read metabarcoding data

Sahraei

Furneaux

Kluting

et al. 2021

Preprint

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“…Changes in the magnitude and direction of plant–microbe interactions, but not the variance suggests that the presence or absence of microbial taxa takes precedence in determining microbial impacts, with microbial abundances playing a secondary role. Pooled samples likely included a broader diversity of plant‐interacting microbes (Castle et al ), increasing the likelihood of encountering a strongly interacting microbe. However, this does not mean that the quantitative abundance of all microbes, such as VA mycorrhizae, is not important.…”

Section: Discussionmentioning

confidence: 99%

Inoculum handling alters the strength and direction of plant–microbe interactions

Peacher

Meiners

2020

Ecology

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The pooling of soil samples in plant–microbe interaction studies is commonly employed, but the impact of sample handling has rarely been explored experimentally. Concerns have been raised that sample pooling may reduce biological variation leading to inflated type I errors or may alter the magnitude of microbial effects observed, invalidating the results achieved. To assess the impact of inocula pooling on plant–microbe interactions, we examined the reciprocal influence of unpooled and pooled soil microbial inocula on growth of Solidago altissima and Schizachyrium scoparium, with and without inoculum sterilization. Soil pooling had no effect on the variance among replicates in either plant species. However, pooling dramatically altered the magnitude and direction of microbial impacts on plant performance. Pooling of Solidago altissima soil increased the antagonistic effects on growth of both target species. In contrast, pooling of Schizachyrium scoparium soil shifted impacts on Solidago altissima from effectively neutral to slightly positive. Pooling in this system altered both the strength and direction of plant–microbe interactions relative to unpooled soils. Therefore soil mixing should be avoided when the research goal is to determine naturally occurring interaction strengths, even within a single habitat.

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“…However, methodological artifacts may also account for some observations of weak spatial differences ( 28 ). Microbial biogeographic patterns are known to be sensitive to various factors, including spatial scale ( 42 , 43 ), sampling effort ( 28 , 44 – 46 ), and taxonomic resolution ( 15 , 28 , 44 , 47 – 49 ). Communities are inherently prone to being undersampled, whether through insufficient sampling effort, low sequencing depth, or rarefying data ( 50 , 51 ).…”

Section: Introductionmentioning

confidence: 99%

Soil Bacterial Communities Exhibit Strong Biogeographic Patterns at Fine Taxonomic Resolution

et al. 2020

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Bacteria have been inferred to exhibit relatively weak biogeographic patterns. To what extent such findings reflect true biological phenomena or methodological artifacts remains unclear. Here, we addressed this question by analyzing the turnover of soil bacterial communities from three data sets. We applied three methodological innovations: (i) design of a hierarchical sampling scheme to disentangle environmental from spatial factors driving turnover; (ii) resolution of 16S rRNA gene amplicon sequence variants to enable higher-resolution community profiling; and (iii) application of the new metric zeta diversity to analyze multisite turnover and drivers. At fine taxonomic resolution, rapid compositional turnover was observed across multiple spatial scales. Turnover was overwhelmingly driven by deterministic processes and influenced by the rare biosphere. The communities also exhibited strong distance decay patterns and taxon-area relationships, with z values within the interquartile range reported for macroorganisms. These biogeographical patterns were weakened upon applying two standard approaches to process community sequencing data: clustering sequences at 97% identity threshold and/or filtering the rare biosphere (sequences lower than 0.05% relative abundance). Comparable findings were made across local, regional, and global data sets and when using shotgun metagenomic markers. Altogether, these findings suggest that bacteria exhibit strong biogeographic patterns, but these signals can be obscured by methodological limitations. We advocate various innovations, including using zeta diversity, to advance the study of microbial biogeography. IMPORTANCE It is commonly thought that bacterial distributions show lower spatial variation than for multicellular organisms. In this article, we present evidence that these inferences are artifacts caused by methodological limitations. Through leveraging innovations in sampling design, sequence processing, and diversity analysis, we provide multifaceted evidence that bacterial communities in fact exhibit strong distribution patterns. This is driven by selection due to factors such as local soil characteristics. Altogether, these findings suggest that the processes underpinning diversity patterns are more unified across all domains of life than previously thought, which has broad implications for the understanding and management of soil biodiversity.

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Impacts of Sampling Design on Estimates of Microbial Community Diversity and Composition in Agricultural Soils

Cited by 17 publications

References 43 publications

Soil eukaryote community shift but not composition is consistently recovered by different OTU inference methods applied to long read metabarcoding data

Soil eukaryote community shift but not composition is consistently recovered by different OTU inference methods applied to long read metabarcoding data

Inoculum handling alters the strength and direction of plant–microbe interactions

Soil Bacterial Communities Exhibit Strong Biogeographic Patterns at Fine Taxonomic Resolution

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