Large Insert Environmental Genomic Library Production
Bibliographic record
Abstract
The vast majority of microbes in nature currently remain inaccessible to traditional cultivation methods. Over the past decade, culture-independent environmental genomic (i.e. metagenomic) approaches have emerged, enabling researchers to bridge this cultivation gap by capturing the genetic content of indigenous microbial communities directly from the environment. To this end, genomic DNA libraries are constructed using standard albeit artful laboratory cloning techniques. Here we describe the construction of a large insert environmental genomic fosmid library with DNA derived from the vertical depth continuum of a seasonally hypoxic fjord. This protocol is directly linked to a series of connected protocols including coastal marine water sampling [1], large volume filtration of microbial biomass [2] and a DNA extraction and purification protocol [3]. At the outset, high quality genomic DNA is end-repaired with the creation of 5 -phosphorylated blunt ends. End-repaired DNA is subjected to pulsed-field gel electrophoresis (PFGE) for size selection and gel extraction is performed to recover DNA fragments between 30 and 60 thousand base pairs (Kb) in length. Size selected DNA is purified away from the PFGE gel matrix and ligated to the phosphatase-treated blunt-end fosmid CopyControl vector pCC1 (EPICENTRE http://www.epibio.com/item.asp?ID=385). Linear concatemers of pCC1 and insert DNA are subsequently headfull packaged into phage particles by lambda terminase, with subsequent infection of phage-resistant E. coli cells. Successfully transduced clones are recovered on LB agar plates under antibiotic selection and archived in 384-well plate format using an automated colony picking robot (Qpix2, GENETIX). The current protocol draws from various sources including the CopyControl Fosmid Library Production Kit from EPICENTRE and the published works of multiple research groups [4-7]. Each step is presented with best practice in mind. Whenever possible we highlight subtleties in execution to improve overall quality and efficiency of library production. The whole process of fosmid library production and automated colony picking takes at least 7-10 days as there are many incubation steps included. However, there are several stopping points possible which are mentioned within the protocol.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.016 |
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".