Evaluation of 16S rRNA Gene Primer Pairs for Monitoring Microbial Community Structures Showed High Reproducibility within and Low Comparability between Datasets Generated with Multiple Archaeal and Bacterial Primer Pairs

Abstract

The application of next-generation sequencing technology in microbial community analysis increased our knowledge and understanding of the complexity and diversity of a variety of ecosystems. In contrast to Bacteria, the archaeal domain was often not particularly addressed in the analysis of microbial communities. Consequently, established primers specifically amplifying the archaeal 16S ribosomal gene region are scarce compared to the variety of primers targeting bacterial sequences. In this study, we aimed to validate archaeal primers suitable for high throughput next generation sequencing. Three archaeal 16S primer pairs as well as two bacterial and one general microbial 16S primer pairs were comprehensively tested by in-silico evaluation and performing an experimental analysis of a complex microbial community of a biogas reactor. The results obtained clearly demonstrate that comparability of community profiles established using different primer pairs is difficult. 16S rRNA gene data derived from a shotgun metagenome of the same reactor sample added an additional perspective on the community structure. Furthermore, in-silico evaluation of primers, especially those for amplification of archaeal 16S rRNA gene regions, does not necessarily reflect the results obtained in experimental approaches. In the latter, archaeal primer pair ArchV34 showed the highest similarity to the archaeal community structure compared to observed by the metagenomic approach and thus appears to be the appropriate for analyzing archaeal communities in biogas reactors. However, a disadvantage of this primer pair was its low specificity for the archaeal domain in the experimental application leading to high amounts of bacterial sequences within the dataset. Overall our results indicate a rather limited comparability between community structures investigated and determined using different primer pairs as well as between metagenome and 16S rRNA gene amplicon based community structure analysis. This finding, previously shown for Bacteria, was as well observed for the archaeal domain.

Asgard archaea are diverse, ubiquitous, and transcriptionally active microbes

“…As the minimum intragroup similarity (71%, Supplementary Table 1) of sequences within Heimdallarchaeota was below the suggested phylum-level threshold of 75% 17 , the lineage was divided into two subgroups [Heimdall (AAG) and Heimdall (MHVG)], as previously recommended 7,19 . Three of the 13 subgroups (Asgard 2-4) comprised sequences from the reference study 15 ( Supplementary 6 Table 1), while only two lineages [Heimdall (AAG) and Loki-3] contained >70% sequences from public databases, indicating that the previously used universal archaeal primers or Asgard-specific primers [20][21][22] retrieved sequences only from certain Asgard subgroups. We suggest that alternative approaches, e.g., RNA-extraction-based method 15 or deep-sequencing technology 7 , will provide additional sequences for primer-set design, thus informing comprehensive and precise phylogenetic reconstruction of the Asgard superphylum in the future.…”

Long‐term investigation of microbial community composition and transcription patterns in a biogas plant undergoing ammonia crisis

“…Primers applied for the amplification of the amplification of the bacterial and archaeal 16S rRNA gene fragments are listed in Table and were previously tested for applicability to monitor the microbial community in biogas environments (Fischer et al ., ). Extracted DNA was adjusted to a concentration of 20 ng μl −1 and applied in the amplification reaction.…”

Exploring the archaeome: detection of archaeal signatures in the human body

“…A few of the underlying reasons for the under-representation of archaea in microbiome studies are (i) primer mismatches of the "universal primers" (Raymann et al, 2017), (ii) the sometimes too low abundance of the archaeal DNA in the studied samples, (iii) improper DNA extraction methods, and (iv) the incompleteness of the 16S rRNA gene reference databases. This is not only leading to an insufficient taxonomy assignment (unclassification) of archaea, but also, in the worst case, to the removal of archaeal signatures from the retrieved datasets (Ding and Schloss, 2014;Fischer et al, 2016). Moreover, the clinical interest on archaea is minor, due to the fact that there are no known or proved archaeal pathogens yet (Gill et al, 2006).…”