Targeting novel soil glycosyl hydrolases by combining stable isotope probing and metagenomics
Bibliographic record
Abstract
Soil represents the largest global reservoir of microbial diversity for the discovery of novel genes and enzymes. Both stable-isotope probing (SIP) and metagenomics have been used to access uncultured microbial diversity, but few studies have combined these two methods for accessing the biotechnological potential of soil genetic diversity and fewer yet have employed functional metagenomics for recovering novel genes and enzymes for bioenergy or bioproduct applications. In this research, I demonstrate the power of combining functional metagenomics and SIP using multiple plant-derived carbon substrates and diverse soils for characterizing active soil bacterial communities and recovering glycosyl hydrolases based on gene expression. Three disparate Canadian soils (tundra, temperate rainforest and agricultural) were incubated with five native carbon (12C) or stable-isotope labelled (13C) carbohydrates (glucose, cellobiose, xylose, arabinose and cellulose). Sampling at defined time intervals (one, three and six weeks) was followed by DNA extraction and cesium chloride density gradient ultracentrifugation. Denaturing gradient gel electrophoresis (DGGE) of all gradient fractions confirmed the recovery of labeled nucleic acids. Sequencing of original soil samples and labeled DNA fractions demonstrated unique heavy DNA patterns associated with all soils and substrates. Indicator species analysis revealed many uncultured and unclassified bacterial taxa in the heavy DNA for all soils and substrates. Among characterized taxa, Salinibacterium (Actinobacteria), Devosia (Alphaproteobacteria), Telmatospirillum (Alphaproteobacteria), Phenylobacterium (Alphaproteobacteria) and Asticcacaulis (Alphaproteobacteria) were the bacterial “indicator species” for the heavy substrates and soils tested. Both Actinomycetales and Caulobacterales (genus Phenylobacterium) were associated with metabolism of cellulose. Members of the Alphaproteobacteria were associated with the metabolism of arabinose and members of the order Rhizobiales were strongly associated with the metabolism of xylose. \nAnnotated metagenomic data suggested diverse glycosyl hydrolase gene representation within the pooled heavy DNA. By screening only 2876 inserts derived from the 13C-cellulose heavy DNA, stable-isotope probing and functional screens enabled the recovery of six clones with activity against carboxymethylcellulose and methylumbelliferone-based substrates.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".