Quantifying Soil Microbiome Abundance by Metatranscriptomics and Complementary Molecular Techniques—Cross-Validation and Perspectives

Abstract

Linking meta-omics and biogeochemistry approaches in soils has remained challenging. This study evaluates the use of an internal RNA extraction standard and its potential for making quantitative estimates of a given microbial community size (biomass) in soil metatranscriptomics. We evaluate commonly used laboratory protocols for RNA processing, metatranscriptomic sequencing and quantitative reverse transcription polymerase chain reaction (qRT-PCR). Metatranscriptomic profiles from soil samples were generated using two library preparation protocols and prepared in triplicates. RNA extracted from pure cultures of Saccharolobus solfataricus was added to the samples as an internal nucleic acid extraction standard (NAE_std). RNA reads originating from NAE_std were identified with a 99.9% accuracy. A remarkable replication consistency between triplicates was seen (average Bray–Curtis dissimilarity 0.03 ± 0.02), in addition to a clear library preparation bias. Nevertheless, the between-sample pattern was not affected by library type. Estimates of 16S rRNA transcript abundance derived from qRT-PCR experiments, NAE_std and a previously published quantification method of metatranscriptomics (hereafter qMeTra) were compared with microbial biomass carbon (MBC) and nitrogen (MBN) extracts. The derived biomass estimates differed by orders of magnitude. While most estimates were significantly correlated with each other, no correlation was observed between NAE_std and MBC extracts. We discuss how simultaneous changes in community size and the soils nucleic acid retention strength might hamper accurate biomass estimation. Adding NAE_std has the potential to shed important light on nucleic acid retention in the substance matrix (e.g., soil) during extraction.