Simulated rRNA/DNA Ratios Show Potential To Misclassify Active Populations as Dormant

Abstract

The use of rRNA/DNA ratios derived from surveys of rRNA sequences in RNA and DNA extracts is an appealing but poorly validated approach to infer the activity status of environmental microbes. To improve the interpretation of rRNA/DNA ratios, we performed simulations to investigate the effects of community structure, rRNA amplification, and sampling depth on the accuracy of rRNA/DNA ratios in classifying bacterial populations as “active” or “dormant.” Community structure was an insignificant factor. In contrast, the extent of rRNA amplification that occurs as cells transition from dormant to growing had a significant effect (P < 0.0001) on classification accuracy, with misclassification errors ranging from 16 to 28%, depending on the rRNA amplification model. The error rate increased to 47% when communities included a mixture of rRNA amplification models, but most of the inflated error was false negatives (i.e., active populations misclassified as dormant). Sampling depth also affected error rates (P < 0.001). Inadequate sampling depth produced various artifacts that are characteristic of rRNA/DNA ratios generated from real communities. These data show important constraints on the use of rRNA/DNA ratios to infer activity status. Whereas classification of populations as active based on rRNA/DNA ratios appears generally valid, classification of populations as dormant is potentially far less accurate.IMPORTANCE The rRNA/DNA ratio approach is appealing because it extracts an extra layer of information from high-throughput DNA sequencing data, offering a means to determine not only the seedbank of taxa present in communities but also the subset of taxa that are metabolically active. This study provides crucial insights into the use of rRNA/DNA ratios to infer the activity status of microbial taxa in complex communities. Our study shows that the approach may not be as robust as previously supposed, particularly in complex communities composed of populations employing different growth strategies, and identifies factors that inflate the erroneous classification of active populations as dormant.

Dormancy dampens the microbial distance-decay relationship

“…For example, studies that characterize microbial communities using high-throughput DNA sequencing implicitly assume that primer coverage, extraction efficiency, and amplification bias do not prevent molecular surveys from reflecting actual community structure[49]. There are also assumptions regarding the relationship between growth rate and rRNA content, when making inferences about the metabolic activity of microbial taxa using 16S ribosomal DNA and RNA sequencing [50, 51]. However, these caveats and limitations can, in part, be addressed by coupling empirical efforts with models that explicitly encode hypothesized mechanisms and that are independent of methodological assumptions.…”

Diversity and gene expression patterns of functional groups in sidestream and mainstream wastewater partial-nitritation anammox biofilms

“…On the other hand, although rRNA:rDNA values larger 233 than one are frequently used as criteria for activity (Blazewicz, et al 2013), different taxa might differ 234 in their rRNA content during growth or dormancy to the extent that rRNA content and growth rate are 235 not linked (Blazewicz, et al 2013). Thus, potentially active taxa might be misclassified as dormant 236 just because their rRNA:rDNA ratio is below one (Steven, et al 2017). 237…”

“…The disproportionally high read abundances of rRNA at low rDNA abundances for most phyla 239 ( Figure S4) confirm previous similar observations, suggesting higher activity among rare taxa 240 (Campbell, et al 2011, Jia, et al 2019, Jones and Lennon 2010, Klein, et al 2016, Wilhelm, et al 241 2014. This phenomenon could perhaps be due to under-sampling (Steven, et al 2017), but higher 242 growth rate among rare taxa could arise due to intraspecific competition or predation of abundant taxa 243 (Jousset, et al 2017). In fact, by using metagenomic data, Jia, et al (2019) observed higher 244 replication rates for taxa at low relative abundances supporting that this is a real phenomenon.…”

16S rRNA:rDNA ratios and cell activity staining reveal consistent patterns of soil microbial activity

“…Taxa with 16S ratios greater than a specified threshold are considered ‘active’, and most studies report using a threshold of 1.0, which indicates more rRNA reads than rDNA reads for those taxa (6, 8, 16). One limitation to this approach is that using an arbitrary threshold to distinguish active from dormant taxa may be problematic in diverse communities (13, 17), given that rRNA production and growth rate are not necessarily always correlated (24–29). Another challenge in assessing 16S ratios is the occurrence of ‘phantom taxa’: taxa that are detected in rRNA but not rDNA sequences (18) which leads to a zero-denominator (and thus undefined) 16S ratio.…”