ReviewMetabolic engineering2019
The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology.
Review in Metabolic engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 215 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
215 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Meta-analysis Driven Strain Design for Mitigating Oxidative Stresses Important in Biomanufacturing.ACS synthetic biology · 2024Pooled it
- Pooled it
- Strategies and applications for alleviating carbon catabolite repression.Synthetic and systems biotechnology · 2027Review
- Application and progress of synthetic biology technology in amino acid production.Bioprocess and biosystems engineering · 2026Review
- Proteome-informed interrogation of a methanogenic archaeon links stress response mechanisms with microbial performance and robustness during biomethanation.Engineering microbiology · 2026Article
- Growth-coupled microbial biosynthesis of the animal pigment xanthommatin.Nature biotechnology · 2026Article
- Adaptive Laboratory Evolution inMicroorganisms · 2026Review
- Closing the Loop with Gates: A Scale-up-Gated Design-Build-Test-Learn Framework for Industrial Fermentation.Microorganisms · 2026Review
- Genome shuffling enables quantitative trait locus mapping in Bacillus subtilis.Nature communications · 2026Article
- Engineering growth independent production: programmable control loops for high-titer rhamnolipids for improved green surfactant sustainability.Bioprocess and biosystems engineering · 2026Review
- Simultaneous optimization of lignocellulosic sugar catabolism via systematic laboratory evolution under complex selection pressure.Nature communications · 2026Article
- Enhanced arabinose utilization by adaptively evolvedSustainable energy & fuels · 2026Article
- Acetate as alternative carbon source for production of mono- and di-rhamnolipids in Pseudomonas putida KT2440.Microbial cell factories · 2026Article
- Novel utilization of the seaweed-based deoxy sugars rhamnose and fucose by engineered Corynebacterium glutamicum.Microbial cell factories · 2026Article
- Article
- Article
- Adaptive Laboratory Evolution Unlocks Membrane Permeability as a Key Limitation in Long-Chain Alcohol Metabolism by Pseudomonas putida KT2440.Microbial biotechnology · 2026Article
- Base Editors for Engineering Industrial Microorganisms: Types, Applications, and Future Perspectives.Biotechnology journal · 2026Review
- Genome-Scale Engineering Importing Property of Escherichia coli for Improving Production of 3-Hydroxypropionic Acid.Microbial biotechnology · 2026Article
- Characterization of acetovanillone degradation in wild-type and engineeredApplied and environmental microbiology · 2026Article
155 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Harnessing the process of natural selection to obtain and understand new microbial phenotypes has become increasingly possible due to advances in culturing techniques, DNA sequencing, bioinformatics, and genetic engineering. Accordingly, Adaptive Laboratory Evolution (ALE) experiments represent a powerful approach both to investigate the evolutionary forces influencing strain phenotypes, performance, and stability, and to acquire production strains that contain beneficial mutations. In this review, we summarize and categorize the applications of ALE to various aspects of microbial physiology pertinent to industrial bioproduction by collecting case studies that highlight the multitude of ways in which evolution can facilitate the strain construction process. Further, we discuss principles that inform experimental design, complementary approaches such as computational modeling that help maximize utility, and the future of ALE as an efficient strain design and build tool driven by growing adoption and improvements in automation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.