Linear Superposition and Prediction of Bacterial Promoter Activity Dynamics in Complex Conditions

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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. © 2014 Rothschild et al.

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Rothschild, D., Dekel, E., Hausser, J., Bren, A., Aidelberg, G., Szekely, P., & Alon, U. (2014). Linear Superposition and Prediction of Bacterial Promoter Activity Dynamics in Complex Conditions. PLoS Computational Biology, 10(5). https://doi.org/10.1371/journal.pcbi.1003602

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