Source 1primary paper2025MED
Toolkit/AdaptUC
AdaptUC
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
Here, we introduce AdaptUC, a computational framework that demonstrates how the fraction of biomass precursors synthesized from unadapted carbon sources governs both the evolutionary driving force and the minimal substrate requirement.
Usefulness & Problems
No literature-backed usefulness or problem-fit explainer has been materialized for this record yet.
Published Workflows
Objective: Design starting strains for adaptive laboratory evolution on unadapted carbon sources by predicting gene knockout combinations that tune biomass precursor dependency and strengthen evolutionary driving force while reducing experimental screening.
Why it works: The abstract states that precursor dependency fraction governs evolutionary driving force and minimal substrate requirement, and that selective pathway blocking can make precursor pools depend on the unadapted substrate. This is presented as the basis for prioritizing starting strains with stronger evolutionary drives.
rendering specific biomass precursor pools dependent on the unadapted carbon source by selectively blocking metabolic pathwayscomputational frameworkgene knockout predictiongenome-scale metabolic modelingadaptive laboratory evolution
Stages
- 1.Genome-scale model-guided candidate navigation and knockout prediction(in_silico_filter)
This stage exists to use genome-scale metabolic models to navigate vast candidate pools and identify knockout combinations before experimental screening.
Selection: Predicted gene knockout strategies that render specific precursor pools dependent on the unadapted substrate and prioritize stronger evolutionary drives.
- 2.Case-study validation against experimental records and literature(confirmatory_validation)
This stage exists to confirm that predicted knockout combinations can fine-tune precursor dependency and accelerate adaptation in reported case studies.
Selection: Agreement of AdaptUC case-study predictions with experimental records and literature in Escherichia coli and Corynebacterium glutamicum.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Mechanisms
evolutionary selection pressure modulationmetabolic pathway blocking by gene knockoutsubstrate-dependent biomass precursor synthesisTarget processes
recombinationselectionValidation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
Case studies in Escherichia coli and Corynebacterium glutamicum validated against experimental records and literature support that AdaptUC can identify knockout combinations that fine-tune precursor dependency and accelerate adaptation.
Case studies in Escherichia coli and Corynebacterium glutamicum, validated against experimental records and literature, confirm AdaptUC's ability to identify knockout combinations that fine-tune precursor dependency and accelerate adaptation.
By leveraging genome-scale metabolic models, AdaptUC navigates vast candidate pools without combinatorial explosion, reducing experimental screening and prioritizing strains with stronger evolutionary drives.
By leveraging genome-scale metabolic models, AdaptUC navigates vast candidate pools without combinatorial explosion, reducing experimental screening and prioritizing strains with stronger evolutionary drives.
AdaptUC predicts gene knockout strategies that construct starting strains for adaptive laboratory evolution by blocking metabolic pathways so that specific precursor pools depend on the unadapted substrate.
AdaptUC predicts gene knockout strategies for constructing the starting strain for adaptive laboratory evolution by selectively blocking metabolic pathways, thereby rendering specific precursor pools dependent on the unadapted substrate.
Smaller dependency fractions correspond to higher evolutionary driving forces for evolution of the starting strain.
We show that smaller dependency fractions correspond to higher driving forces for evolution of the starting strain.
AdaptUC is a computational framework for analyzing how the fraction of biomass precursors synthesized from unadapted carbon sources affects evolutionary driving force and minimal substrate requirement.
Here, we introduce AdaptUC, a computational framework that demonstrates how the fraction of biomass precursors synthesized from unadapted carbon sources governs both the evolutionary driving force and the minimal substrate requirement.
Approval Evidence
1 source5 linked approval claimsfirst-pass slug adaptuc
Here, we introduce AdaptUC, a computational framework that demonstrates how the fraction of biomass precursors synthesized from unadapted carbon sources governs both the evolutionary driving force and the minimal substrate requirement.
Source:
case study validationsupports
Case studies in Escherichia coli and Corynebacterium glutamicum validated against experimental records and literature support that AdaptUC can identify knockout combinations that fine-tune precursor dependency and accelerate adaptation.
Case studies in Escherichia coli and Corynebacterium glutamicum, validated against experimental records and literature, confirm AdaptUC's ability to identify knockout combinations that fine-tune precursor dependency and accelerate adaptation.
Source:
computational scalingsupports
By leveraging genome-scale metabolic models, AdaptUC navigates vast candidate pools without combinatorial explosion, reducing experimental screening and prioritizing strains with stronger evolutionary drives.
By leveraging genome-scale metabolic models, AdaptUC navigates vast candidate pools without combinatorial explosion, reducing experimental screening and prioritizing strains with stronger evolutionary drives.
Source:
design capabilitysupports
AdaptUC predicts gene knockout strategies that construct starting strains for adaptive laboratory evolution by blocking metabolic pathways so that specific precursor pools depend on the unadapted substrate.
AdaptUC predicts gene knockout strategies for constructing the starting strain for adaptive laboratory evolution by selectively blocking metabolic pathways, thereby rendering specific precursor pools dependent on the unadapted substrate.
Source:
mechanistic relationshipsupports
Smaller dependency fractions correspond to higher evolutionary driving forces for evolution of the starting strain.
We show that smaller dependency fractions correspond to higher driving forces for evolution of the starting strain.
Source:
tool introductionsupports
AdaptUC is a computational framework for analyzing how the fraction of biomass precursors synthesized from unadapted carbon sources affects evolutionary driving force and minimal substrate requirement.
Here, we introduce AdaptUC, a computational framework that demonstrates how the fraction of biomass precursors synthesized from unadapted carbon sources governs both the evolutionary driving force and the minimal substrate requirement.
Source:
Comparisons
No literature-backed comparison notes have been materialized for this record yet.
Ranked Citations
- 1.