Abstract

We examined the effect of different soil sample sizes obtained from an agricultural field, under a single cropping system uniform in soil properties and aboveground crop responses, on bacterial and fungal community structure and microbial diversity indices. DNA extracted from soil sample sizes of 0.25, 1, 5, and 10 g using MoBIO kits and from 10 and 100 g sizes using a bead-beating method (SARDI) were used as templates for high-throughput sequencing of 16S and 28S rRNA gene amplicons for bacteria and fungi, respectively, on the Illumina MiSeq and Roche 454 platforms. Sample size significantly affected overall bacterial and fungal community structure, replicate dispersion and the number of operational taxonomic units (OTUs) retrieved. Richness, evenness and diversity were also significantly affected. The largest diversity estimates were always associated with the 10 g MoBIO extractions with a corresponding reduction in replicate dispersion. For the fungal data, smaller MoBIO extractions identified more unclassified Eukaryota incertae sedis and unclassified glomeromycota while the SARDI method retrieved more abundant OTUs containing unclassified Pleosporales and the fungal genera Alternaria and Cercophora. Overall, these findings indicate that a 10 g soil DNA extraction is most suitable for both soil bacterial and fungal communities for retrieving optimal diversity while still capturing rarer taxa in concert with decreasing replicate variation.

Highlights

  • The complex structural and spatial physico-chemical heterogeneity of soils likely influences microbial community structure, over varying spatial scales

  • Raw 28S rRNA gene sequences were processed for minimum length (400 bp), quality (Q > 20), primer match and barcode sorting using the RDP pyrosequencing pipeline

  • The remaining 266,600 sequences were aligned clustered at 5% nucleotide dissimilarity and representative sequences generated for each operational taxonomic units (OTUs) using RDP tools hosted on the Michigan State University High Performance Computing Center servers2

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Summary

Introduction

The complex structural and spatial physico-chemical heterogeneity of soils likely influences microbial community structure, over varying spatial scales. Spatial heterogeneity due to carbon and nutrient availability and redox potential gradients promote diversity by providing specific niches and creating ecological opportunities (Rainey and Travisano, 1998; Gupta and Germida, 2015). Given this complexity, soil microbial biology was often treated as a “black box” (Tiedje et al, 1999) but, with the advent. Given the spatial heterogeneity of soil, sample size should be large enough to encompass all the significant microhabitats of the ecological unit under study so that larger drivers of biological structure can be discerned

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