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

Abstract

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.

Equivolumetric protocol generates library sizes proportional to total microbial load in next-generation sequencing

“…One way to recover absolute bacterial abundance is to associate relative information from high-throughput technology with absolute information from other methods. This has been previously done using qPCR or flow cytometry data as absolute abundance methodologies, and NGS as provider of bacterial proportions 7,9,27 . Here, however, total microbial load gains importance as a measure of total contamination for surveillance of indoor environments, as opposed to merely a means to project proportions onto absolute terms.…”

“…The application of next-generation sequencing (NGS) methodologies allows large-scale identification of microorganisms, revealing the colonization and dispersion patterns throughout studied sites such as hospitals, indoor or outdoor natural environments [1][2][3][4][5][6] . Despite various detailed microbiome characterization studies, most efforts address solely relative bacterial abundances, i.e., do not account for major variations of total microbial load [7][8][9] .…”

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

“…A promising solution to these problems is the incorporation of an internal standard (ISD) 67 into the DNA sequencing process (Chen et al 2016;Hossain et al 2020;Jiang et al 2011; 68 Smets et al 2016;Tourlousse et al 2017;Zemb et al 2020). Colloquially, this process is re-69 ferred to as adding a "spike-in" of known quantity to samples.…”

“…We suggest that understanding the effect of PCR inhibitors on taxa of particular biological 374 interest (e.g., important pathogens) and within oft-studied substances (e.g., blood, urine, 375 tissues of model organisms) is a pressing need. Because of the looming issue of PCR in-376 hibitors, we suggest that nucleic acid extraction protocols be preferred that consistently 377 remove problematic compounds at the outset-a stated benefit of many commercially avail- Zemb et al 2020). This allows an ISD to capture variation in extraction perfor-401 mance (as mentioned above; Fig.…”

“…Tkacz et al (2018) added ISDs to soil samples both 402 before and after DNA-extraction and report superior performance when ISDs were added 403 before extraction. We note that measuring variation in extraction yield is best achieved via 404 a cellular ISD that mimics traits of focal taxa (see above), however adding a DNA ISD to 405 samples pre-extraction is also be beneficial (Zemb et al 2020). The benefit of the latter during nucleic acid extraction, then an ISD could be added after extraction but prior to nor-413 malizing DNA concentrations for PCR ( Fig.…”