ArticlePLoS computational biology2014
Linear superposition and prediction of bacterial promoter activity dynamics in complex conditions.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- An Experimentally Verified Mechanistic Model for Predicting Quorum Sensing-Based Switches.Microbial biotechnology · 2026Article
- Article
- Combinatorial processing of bacterial and host-derived innate immune stimuli at the single-cell level.Molecular biology of the cell · 2019Article
- Pairwise interactions and the battle against combinatorics in multidrug therapies.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Combination Effects of Antimicrobial Peptides.Antimicrobial agents and chemotherapy · 2016Article
- Computing the functional proteome: recent progress and future prospects for genome-scale models.Current opinion in biotechnology · 2015Review
- Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.PLoS computational biology · 2015Article
- Hierarchy of non-glucose sugars in Escherichia coli.BMC systems biology · 2014Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
Bacteria often face complex environments. We asked how gene expression in complex conditions relates to expression in simpler conditions. To address this, we obtained accurate promoter activity dynamical measurements on 94 genes in E. coli in environments made up of all possible combinations of four nutrients and stresses. We find that the dynamics across conditions is well described by two principal component curves specific to each promoter. As a result, the promoter activity dynamics in a combination of conditions is a weighted average of the dynamics in each condition alone. The weights tend to sum up to approximately one. This weighted-average property, called linear superposition, allows predicting the promoter activity dynamics in a combination of conditions based on measurements of pairs of conditions. If these findings apply more generally, they can vastly reduce the number of experiments needed to understand how E. coli responds to the combinatorially huge space of possible environments.
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Registered trials
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