ArticleApplied and environmental microbiology2015
Use of adaptive laboratory evolution to discover key mutations enabling rapid growth of Escherichia coli K-12 MG1655 on glucose minimal medium.
Article in Applied and environmental microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 146 papers.
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
146 citing papers in PubMed, 271 citations in OpenAlex.
- Article
- Selection favors cost-ordered adaptive mutational paths in a stress-magnitude-dependent manner.EMBO reports · 2026Article
- Metabolite correlation networks reveal complex phenotypes of adaptation-driving mutations.Nature communications · 2026Article
- Article
- Adaptive Laboratory Evolution inMicroorganisms · 2026Review
- Cell geometry and membrane protein crowding constrain Escherichia coli growth rate, overflow metabolism, respiration, and maintenance energy.FEBS letters · 2026Article
- Simultaneous optimization of lignocellulosic sugar catabolism via systematic laboratory evolution under complex selection pressure.Nature communications · 2026Article
- Transcriptome Profiling ofAntibiotics (Basel, Switzerland) · 2026Article
- Gene loss and compensatory evolution as a source of metabolic preadaptations.Molecular biology and evolution · 2026Article
- Aerobicity stimulon iniScience · 2026Article
- Inferring bacterial cell size dynamics across media conditions.Scientific reports · 2026Article
- Advances in adaptive laboratory evolution applications forSynthetic and systems biotechnology · 2025Review
- Phage Resistance ModulatesAntibiotics (Basel, Switzerland) · 2025Article
- Naphthoquinone preferentially pairs with non-proton-pumping NADH dehydrogenase for respiratory electron transport.PLoS genetics · 2025Article
- Cell Geometry and Membrane Protein Crowding Constrain Growth Rate, Overflow Metabolism, Respiration, and Maintenance Energy.bioRxiv : the preprint server for biology · 2025Article
- Engineering controllable alteration of malonyl-CoA levels to enhance polyketide production.Nature chemical biology · 2025Article
- Multiple factors based adaptive laboratory evolution strategy enhances DHA production in Aurantiochytrium sp. PKU#Mn16 by rewiring key metabolic pathways.Microbial cell factories · 2025Article
- System-level characterization of engineered and evolved formatotrophicSynthetic and systems biotechnology · 2025Article
- Industrial Microbial Technologies for Feed Protein Production from Non-Protein Nitrogen.Microorganisms · 2025Review
- Transcriptome analysis and reverse engineering verification of SNZ3Biotechnology for biofuels and bioproducts · 2025Article
86 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
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adaptive laboratory evolution (ALE) has emerged as an effective tool for scientific discovery and addressing biotechnological needs. Much of ALE's utility is derived from reproducibly obtained fitness increases. Identifying causal genetic changes and their combinatorial effects is challenging and time-consuming. Understanding how these genetic changes enable increased fitness can be difficult. A series of approaches that address these challenges was developed and demonstrated using Escherichia coli K-12 MG1655 on glucose minimal media at 37°C. By keeping E. coli in constant substrate excess and exponential growth, fitness increases up to 1.6-fold were obtained compared to the wild type. These increases are comparable to previously reported maximum growth rates in similar conditions but were obtained over a shorter time frame. Across the eight replicate ALE experiments performed, causal mutations were identified using three approaches: identifying mutations in the same gene/region across replicate experiments, sequencing strains before and after computationally determined fitness jumps, and allelic replacement coupled with targeted ALE of reconstructed strains. Three genetic regions were most often mutated: the global transcription gene rpoB, an 82-bp deletion between the metabolic pyrE gene and rph, and an IS element between the DNA structural gene hns and tdk. Model-derived classification of gene expression revealed a number of processes important for increased growth that were missed using a gene classification system alone. The methods described here represent a powerful combination of technologies to increase the speed and efficiency of ALE studies. The identified mutations can be examined as genetic parts for increasing growth rate in a desired strain and for understanding rapid growth phenotypes.
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.