Open resource metagenomics: a model for sharing metagenomic libraries
Bibliographic record
Abstract
Both sequence-based and activity-based exploitation of environmental DNA have provided unprecedented access to the genomic content of cultivated and uncultivated microorganisms. Although researchers deposit microbial strains in culture collections and DNA sequences in databases, activity-based metagenomic studies typically only publish sequences from the hits retrieved from specific screens. Physical metagenomic libraries, conceptually similar to entire sequence datasets, are usually not straightforward to obtain by interested parties subsequent to publication. In order to facilitate unrestricted distribution of metagenomic libraries, we propose the adoption of open resource metagenomics, in line with the trend towards open access publishing, and similar to culture- and mutant-strain collections that have been the backbone of traditional microbiology and microbial genetics. The concept of open resource metagenomics includes preparation of physical DNA libraries, preferably in versatile vectors that facilitate screening in a diversity of host organisms, and pooling of clones so that single aliquots containing complete libraries can be easily distributed upon request. Database deposition of associated metadata and sequence data for each library provides researchers with information to select the most appropriate libraries for further research projects. As a starting point, we have established the Canadian MetaMicroBiome Library (CM(2)BL [1]). The CM(2)BL is a publicly accessible collection of cosmid libraries containing environmental DNA from soils collected from across Canada, spanning multiple biomes. The libraries were constructed such that the cloned DNA can be easily transferred to Gateway® compliant vectors, facilitating functional screening in virtually any surrogate microbial host for which there are available plasmid vectors. The libraries, which we are placing in the public domain, will be distributed upon request without restriction to members of both the academic research community and industry. This article invites the scientific community to adopt this philosophy of open resource metagenomics to extend the utility of functional metagenomics beyond initial publication, circumventing the need to start from scratch with each new research project.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".