rRNA/rDNA and looking for active taxa in microbial communities

During my scientific research, many of experiments did not work, some of my hypotheses were wrong, and sometimes I got negative results.

One of these studies where I had high expectations, but I did not get interesting results was years ago during my PhD. There I attempted to identify the metabolically active taxa in a biofilm community, by sequencing ribosomes, i.e. ribosomal rRNA (rRNA). This is because cells need ribosomes to make proteins, and for some Proteobacteria it has been observed that their ribosomal content increases when they are growing. A theoretical advantage of this approach is that is has the potential to distinguish metabolically active, dormant and dead populations, something that ribosomal rRNA gene (rDNA) cannot achieve.

Active 😀yesyes
Dormant 😴yeslow
Dead 💀yesno

If 5% of your community in your rRNA dataset species belongs to species X, then we could think that species X is metabolically active. We are detecting their ribosomes. However, the rRNA values you get will depend in (1) the average number of ribosomes your population have, and (2) the abundance of your population. So maybe species X could be very abundant, but it could have a low ribosomal content.

A workaround around this problem is to normalize your rRNA values by the relative abundance of a taxa in your community. These are the so-called rRNA:rDNA ratios. This method was widely used during the 2010s to identify active taxa in all kinds of microbial communities like soil, water, atmosphere, and wastewater bioreactors. However, that approach is far from being perfect. (For a discussion on the topic the read the paper by the Steven Blazewicz et al: https://www.nature.com/articles/ismej2013102)

Sequencing rDNA and rRNA

In my PhD, we used rRNA sequencing to identify active taxa in biofilms from a wastewater bioreactor. In the plot below rDNA and rRNA are compared, with the diagonal line showing an rDNA:rRNA of one. We observed that some taxa like Firmicutes (the pink dots) had high rDNA:rRNA, while others like Acidobacteria (the light blue dots) had low rDNA:rRNA ratios.

So, what do rDNA:rRNA ratios mean? Traditionally it has been assumed that rRNA:rDNA values higher than one are an indication of activity. In other words, taxa overrepresented in the rRNA library are metabolically active. Values lower than one would indicate dormant taxa. But the rDNA:rRNA ratio of one is an arbitrary threshold and it might lead to underestimation of active taxa, as reported by Blaire Steven et al (https://doi.org/10.1128/AEM.00696-17)

Maybe sequencing rRNA is not the best approach

Katerina Papp et al (https://doi.org/10.1128/AEM.02441-17) showed that rRNA:rDNA ratios are a poor proxy to ribosomal production. By using stable isotope probing they quantified ribosomal production and found that sequencing and rRNA:rDNA ratios did not correlate with ribosomal production. Most taxa were producing ribosomes, and thus this supports that rRNA:rDNA ratios underestimate active taxa.

Sequencing of rRNA might not be a valid approach to estimate the activity of a population. Still, it can be useful to sequence ribosomes. For example, Søren M Karst et al (https://doi.org/10.1038/nbt.4045) used a primer-free approach to sequence rRNA, which allow them to identify novel taxa.

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