The choice of the DNA extraction method may influence the outcome of the soil microbial community structure analysis

Zielińska, Sylwia; Radkowski, Piotr; Blendowska, Aleksandra; Ludwig-Gałęzowska, Agnieszka H.; Łoś, Jerzy; Łoś, Marcin

doi:10.1002/mbo3.453

Cited by 61 publications

(61 citation statements)

References 29 publications

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“…Sieving of soil can bring about change in microbial activity and community composition [94][95][96]. Bias associated with DNA extraction and PCR and sequencing techniques are also known [97][98][99][100]. Moreover, the choice of bioinformatics pipeline influences the analyses [101,102].…”

Section: Discussionmentioning

confidence: 99%

Effects of Nanoparticles on Plant Growth-Promoting Bacteria in Indian Agricultural Soil

Chavan

Vigneshwaran

2019

Agronomy

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Soil bacteria are some of the key players affecting plant productivity. Soil today is exposed to emerging contaminants like metal engineered nanoparticles. The objective of this study was to evaluate the toxicological effects of silver and zinc oxide nanoparticles on bacteria classified as plant growth-promoting bacteria. Three types of bacteria-nitrogen fixers, phosphate solubilizers, and biofilm formers-were exposed to engineered nanoparticles. Initially, the effect of silver and zinc oxide nanoparticles was determined on pure cultures of the bacteria. These nanoparticles were then applied to soil to assess changes in composition of bacterial communities. Impacts of the nanoparticles were analyzed using Illumina MiSeq sequencing of 16S rRNA genes. In the soil used, relative abundances of the dominant and agriculturally significant phyla, namely, Proteobacteria, Actinobacteria, and Firmicutes, were altered in the presence of silver nanoparticles. Silver nanoparticles changed the abundance of the three phyla by 25 to 45%. Zinc oxide nanoparticles showed negligible effects at the phylum level. Thus, silver nanoparticles may impact bacterial communities in soil, and this in turn may influence processes carried out by soil bacteria.

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Section: Discussionmentioning

confidence: 99%

Effects of Nanoparticles on Plant Growth-Promoting Bacteria in Indian Agricultural Soil

Chavan

Vigneshwaran

2019

Agronomy

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“…Technical biases can be introduced during DNA extraction and PCR amplification. DNA extraction protocols can be more or less optimized for soil chemistry, which can influence the extent to which DNA is recovered (Zielińska et al., ). Soils rich in clays or humic acids may bind DNA, for example, reducing DNA recovery (Direito, Marees, & Röling, ).…”

Section: Introductionmentioning

confidence: 99%

Minimizing polymerase biases in metabarcoding

Nichols

Vollmers

Newsom

et al. 2018

Molecular Ecology Resources

195

175

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DNA metabarcoding is an increasingly popular method to characterize and quantify biodiversity in environmental samples. Metabarcoding approaches simultaneously amplify a short, variable genomic region, or "barcode," from a broad taxonomic group via the polymerase chain reaction (PCR), using universal primers that anneal to flanking conserved regions. Results of these experiments are reported as occurrence data, which provide a list of taxa amplified from the sample, or relative abundance data, which measure the relative contribution of each taxon to the overall composition of amplified product. The accuracy of both occurrence and relative abundance estimates can be affected by a variety of biological and technical biases. For example, taxa with larger biomass may be better represented in environmental samples than those with smaller biomass. Here, we explore how polymerase choice, a potential source of technical bias, might influence results in metabarcoding experiments. We compared potential biases of six commercially available polymerases using a combination of mixtures of amplifiable synthetic sequences and real sedimentary DNA extracts. We find that polymerase choice can affect both occurrence and relative abundance estimates and that the main source of this bias appears to be polymerase preference for sequences with specific GC contents. We further recommend an experimental approach for metabarcoding based on results of our synthetic experiments.

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“…Marker gene surveys utilizing PCR amplification of a short region of the bacterial 16S rRNA gene from bacterial DNA extracted from environmental samples are becoming increasingly affordable, leading to their ubiquitous implementation in nearly every aspect of biological sciences research [1-8]. However, this method can be heavily affected by technical bias, which is induced at each step in the experimental protocol required to generate marker gene data including; sample handling, bacterial DNA extraction, PCR amplification, sequencing and bioinformatics anlysis [9, 10]. PCR conditions and primer choice can impact biases during the amplification process, which has downstream effects on library preparation and formation of chimeric sequences [11, 12].…”

Section: Introductionmentioning

confidence: 99%

Impact of sequence variant detection and bacterial DNA extraction methods on the measurement of microbial community composition in human stool

Hughes

Alkan

Keim

et al. 2017

Preprint

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BackgroundThe human gut microbiome has been widely studied in the context of human health and metabolism, however the question of how to analyze this community remains contentious. This study compares new and previously well established methods aimed at reducing bias in bioinformatics analysis (QIIME 1 and DADA2) and bacterial DNA extraction of human fecal samples in 16S rRNA marker gene surveys.ResultsAnalysis of a mock DNA community using DADA2 identified more chimeras (QIIME 1: 0.70% of total reads vs DADA2: 1.96%), fewer sequence variants, (QIIME 1: 1297.4 + 98.88 vs. DADA2: 136.27 + 11.35, mean + SD) and correct taxa at a higher resolution of classification (i.e. genus-level) than open reference OTU picking in QIIME 1. Additionally, the extraction of whole cell mock community bacterial DNA using four commercially available kits resulted in varying DNA yield, quality and bacterial community composition. Of the four kits compared, ZymoBIOMICS DNA Miniprep Kit provided the greatest yield, with a slight enrichment of Enterococcus. However, QIAamp Fast DNA Stool Mini Kit resulted in the highest DNA quality. Mo Bio PowerFecal DNA Kit had the most dramatic effect on the mock community composition, resulting in an increased proportion of members of the family Enterobacteriaceae and genus Eshcerichia as well as members of genera Lactobacillus and Pseudomonas. The presence of a sterile fecal matrix had a slight, but inconsistent effect on the yield, quality and taxa identified after extraction with all four DNA extraction kits. Extraction of bacterial DNA from native stool samples revealed a distinct effect of the DNA stabilization reagent DNA/RNA Shield on community composition, causing an increase in the detected abundance of members of orders Bifidobacteriales, Bacteroidales, Turicibacterales, Clostridiales and Enterobacteriales.ConclusionThese results confirm that the DADA2 algorithm is superior to sequence clustering by similarity to determine microbial community structure. Additionally, commercially available kits used for bacterial DNA extraction from fecal samples have some effect on the proportion of high abundance members detected in a microbial community, but it is less significant than the effect of using DNA stabilization reagent, DNA/RNA Shield.

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The choice of the DNA extraction method may influence the outcome of the soil microbial community structure analysis

Cited by 61 publications

References 29 publications

Effects of Nanoparticles on Plant Growth-Promoting Bacteria in Indian Agricultural Soil

Effects of Nanoparticles on Plant Growth-Promoting Bacteria in Indian Agricultural Soil

Minimizing polymerase biases in metabarcoding

Impact of sequence variant detection and bacterial DNA extraction methods on the measurement of microbial community composition in human stool

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