A ‘universal’ type II chaperonin PCR detection system for the investigation of Archaea in complex microbial communities
Bibliographic record
Abstract
Bacteria and Archaea are evolutionarily and biochemically distinct domains found together in many environments. Robust 'universal' PCR primer sets targeting both the bacterial 16S rRNA gene and the type I chaperonin gene have been established. However, 'universal' PCR primers for Archaea are currently limited to the 16S rRNA gene. We investigated the type II chaperonin (known as the thermosome, TF55, CCT or TCP-1) as a potential universal target (UT) for Archaea. Reproducible amplification of thermosome gene sequences from all major phyla tested was achieved through the application of a mixture or 'cocktail' of two forward and two reverse primers. Phylogenies based on the ∼750-bp thermosome UT were congruent with 16S rRNA gene phylogenies while exhibiting longer branch lengths, improving resolution of closely related taxa. 'Universal' thermosome primers were applied to profiling the archaeal community of dairy cow rumen and results compared with profiles based on the 16S rRNA gene and methyl co-enzyme M reductase (methanogen-specific) gene. Clone libraries generated from each target gene, as well as a pyrosequencing profile of one thermosome rumen library, revealed that all three targets consistently detected Methanobrevibacter smithii, Methanobrevibacter ruminantium and Methanosphaera stadtmanae as the dominant constituents; however, thermosome gene sequences were more diverse than either of the other targets providing a higher resolution description of the archaeal community. These findings demonstrate that a 'universal' thermosome PCR protocol is a powerful metagenomic tool for detecting and characterizing Archaea and archaeal communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".