Efficient Generation of Multi-gene Knockout Cell Lines and Patient-derived Xenografts Using Multi-colored Lenti-CRISPR-Cas9
Bibliographic record
Abstract
CRISPR-Cas9 based knockout strategies are increasingly used to analyze gene function. However, redundancies and overlapping functions in biological signaling pathways can call for generating multi-gene knockout cells, which remains a relatively laborious process. Here we detail the application of multi-color LentiCRISPR vectors to simultaneously generate single and multiple knockouts in human cells. We provide a complete protocol, including guide RNA design, LentiCRISPR cloning, viral production and transduction, as well as strategies for sorting and screening knockout cells. The validity of the process is demonstrated by the simultaneous deletion of up to four programmed cell death mediators in leukemic cell lines and patient-derived acute lymphoblastic leukemia xenografts, in which single cell cloning is not feasible. This protocol enables any lab with access to basic cellular biology equipment, a biosafety level 2 facility and fluorescence-activated cell sorting capabilities to generate single and multi-gene knockout cell lines or primary cells efficiently within one month.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".