Determining lineage-specific bacterial growth curves with a novel approach based on amplicon reads normalization using internal standard (ARNIS)

Piwosz, Kasia; Shabarova, Tanja; Tomasch, Jürgen; Šimek, Karel; Kopejtka, Karel; Kahl, Silke; Pieper, Dietmar H.; Koblížek, Michal

doi:10.1038/s41396-018-0213-y

Cited by 22 publications

(27 citation statements)

References 81 publications

(102 reference statements)

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“…For example, Stämmler et al spiked mice fecal samples with a mixture of bacteria that do not exist in the gut microbiome under physiological conditions in order to quantify the OTU (Stämmler et al, 2016). More recently, Piwosz and colleagues added 7.5 × 10 7 Escherichia coli cells per sample in order to reconstruct the absolute abundance of the other OTUs present in the sample (Piwosz et al, 2018). Some authors use DNA spike-in rather than whole cells because DNA quantitation is easier, more accurate and reproducible.…”

Section: Introductionmentioning

confidence: 99%

Absolute quantitation of microbes using 16S rRNA gene metabarcoding: A rapid normalization of relative abundances by quantitative PCR targeting a 16S rRNA gene spike‐in standard

et al. 2020

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Metabarcoding of the 16S rRNA gene is commonly used to characterize microbial communities, by estimating the relative abundance of microbes. Here, we present a method to retrieve the concentrations of the 16S rRNA gene per gram of any environmental sample using a synthetic standard in minuscule amounts (100 ppm to 1% of the 16S rRNA sequences) that is added to the sample before DNA extraction and quantified by two quantitative polymerase chain reaction (qPCR) reactions. This allows normalizing by the initial microbial density, taking into account the DNA recovery yield. We quantified the internal standard and the total load of 16S rRNA genes by qPCR. The qPCR for the latter uses the exact same primers as those used for Illumina sequencing of the V3‐V4 hypervariable regions of the 16S rRNA gene to increase accuracy. We are able to calculate the absolute concentration of the species per gram of sample, taking into account the DNA recovery yield. This is crucial for an accurate estimate as the yield varied between 40% and 84%. This method avoids sacrificing a high proportion of the sequencing effort to quantify the internal standard. If sacrificing a part of the sequencing effort to the internal standard is acceptable, we however recommend that the internal standard accounts for 30% of the environmental 16S rRNA genes to avoid the PCR bias associated with rare phylotypes. The method proposed here was tested on a feces sample but can be applied more broadly on any environmental sample. This method offers a real improvement of metabarcoding of microbial communities since it makes the method quantitative with limited efforts.

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Section: Introductionmentioning

confidence: 99%

Absolute quantitation of microbes using 16S rRNA gene metabarcoding: A rapid normalization of relative abundances by quantitative PCR targeting a 16S rRNA gene spike‐in standard

et al. 2020

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“…The accuracy of CARD-FISH may be compromised by imperfect probe coverage and specificity, uneven permeabilization across phylogenetic groups, differences in the presence of endogenous peroxidases between phylogenetic groups and environmental samples, poor detection of low abundance or inactive community members, and difficulties in counting aggregated cells (23,24). Despite these limitations, relative abundances obtained with CARD-FISH corresponded well to the actual proportions of phylotypes in mock communities (31). The main advantage of CARD-FISH over the HTS methods is that the relative abundance of a particular lineage can be evaluated independent of the other taxa in the samples.…”

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confidence: 99%

“…Limitations connected with PCR biases and imperfect probe and primer coverage and specificity may be potentially overcome by the use of taxonomically profiled metagenomic data to estimate relative abundances of specific groups, but so far tests with mock communities have suggested otherwise (45). Recently, an addition of known amounts of Escherichia coli cells has been proposed as an internal standard for amplicon read normalization in freshwater bacterial communities (31). This approach provided substantially improved estimates for relative changes of phylotype contributions between samples compared to those of nonnormalized reads.…”

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confidence: 99%

Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations

Piwosz

Shabarova

Pernthaler

et al. 2020

mSphere

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High-throughput sequencing (HTS) of gene amplicons is a preferred method of assessing microbial community composition, because it rapidly provides information from a large number of samples at high taxonomic resolution and low costs. However, mock community studies show that HTS data poorly reflect the actual relative abundances of individual phylotypes, casting doubt on the reliability of subsequent statistical analysis and data interpretation. We investigated how accurately HTS data reflect the variability of bacterial and eukaryotic community composition and their relationship with environmental factors in natural samples. For this, we compared results of HTS from three independent aquatic time series (n ϭ 883) with those from an established, quantitative microscopic method (catalyzed reporter deposition-fluorescence in situ hybridization [CARD-FISH]). Relative abundances obtained by CARD-FISH and HTS disagreed for most bacterial and eukaryotic phylotypes. Nevertheless, the two methods identified the same environmental drivers to shape bacterial and eukaryotic communities. Our results show that amplicon data do provide reliable information for their ecological interpretations. Yet, when studying specific phylogenetic groups, it is advisable to combine HTS with quantification using microscopy and/or the addition of internal standards. IMPORTANCE High-throughput sequencing (HTS) of amplified fragments of rRNA genes provides unprecedented insight into the diversity of prokaryotic and eukaryotic microorganisms. Unfortunately, HTS data are prone to quantitative biases, which may lead to an erroneous picture of microbial community composition and thwart efforts to advance its understanding. These concerns motivated us to investigate how accurately HTS data characterize the variability of microbial communities, the relative abundances of specific phylotypes, and their relationships with environmental factors in comparison to an established microscopy-based method. We compared results obtained by HTS and catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) from three independent aquatic time series for both prokaryotic and eukaryotic microorganisms (almost 900 data points, the largest obtained with both methods so far). HTS and CARD-FISH data disagree with regard to relative abundances of bacterial and eukaryotic phylotypes but identify similar environmental drivers shaping bacterial and eukaryotic communities.

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“…Usage Cellular ISDs K. Piwosz et al (2018). "Determining lineage-specific bacterial growth curves with a novel approach based on amplicon reads normalization using internal standard (ARNIS)".…”

Section: Design (Taxon or Sequence)mentioning

confidence: 99%

The quest for absolute abundance: the use of internal standards for DNA-based microbial and community ecology

Harrison¹,

Calder²,

Shuman³

et al. 2020

Preprint

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To characterize microbiomes, microbial ecologists routinely sequence and compare short loci that differ among focal taxa. Counts of these sequences convey information regarding the occurrence and relative abundances of taxa in an assemblage, but provide no direct measure of their absolute abundances, due to the limitations of the sequencing process. The relative abundances in compositional data are inherently constrained and difficult to interpret. The incorporation of internal standards (ISDs; colloquially referred to as ``spike-ins'') into DNA pools for sequencing can ameliorate the problems posed by relative abundance data and allow absolute abundances to be approximated. Unfortunately, many laboratory and sampling biases cause ISDs to underperform or fail. Here, we discuss how careful deployment of ISDs can avoid these complications and be an integral component of well-designed, amplicon-based studies of microbial ecology.

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Determining lineage-specific bacterial growth curves with a novel approach based on amplicon reads normalization using internal standard (ARNIS)

Cited by 22 publications

References 81 publications

Absolute quantitation of microbes using 16S rRNA gene metabarcoding: A rapid normalization of relative abundances by quantitative PCR targeting a 16S rRNA gene spike‐in standard

Absolute quantitation of microbes using 16S rRNA gene metabarcoding: A rapid normalization of relative abundances by quantitative PCR targeting a 16S rRNA gene spike‐in standard

Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations

The quest for absolute abundance: the use of internal standards for DNA-based microbial and community ecology

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