Rapid Sampling of Escherichia coli After Changing Oxygen Conditions Reveals Transcriptional Dynamics

Abstract

Escherichia coli is able to shift between anaerobic and aerobic metabolism by adapting its gene expression, e.g., of metabolic genes, to the new environment. The dynamics of gene expression that result from environmental shifts are limited, amongst others, by the time needed for regulation and transcription elongation. In this study, we examined gene expression dynamics after an anaerobic-to-aerobic shift on a short time scale (0.5, 1, 2, 5, and 10 min) by RNA sequencing with emphasis on delay times and transcriptional elongation rates (TER). Transient expression patterns and timing of differential expression, characterized by delay and elongation, were identified as key features of the dataset. Gene ontology enrichment analysis revealed early upregulation of respiratory and iron-related gene sets. We inferred specific TERs of 89 operons with a mean TER of 42.0 nt/s and mean delay time of 22.4 s. TERs correlate with sequence features, such as codon bias, whereas delay times correlate with the involvement of regulators. The presented data illustrate that at very short times after a shift in oxygenation, extensional changes of the transcriptome, such as temporary responses, can be observed. Besides regulation, TERs contribute to the dynamics of gene expression.

Keywords: Escherichia coli; RNA sequencing; oxygen; transcriptional elongation rates; transition.

Figure 1

Venn diagrams of differentially expressed (DE) genes. Number of genes with increasing (a) and decreasing (b) expression compared to anaerobic control at the specified time points (total number of DE genes at the specified time points are provided in brackets). The numbers in overlapping regions represent DE genes at the corresponding time points. Areas are not drawn to scale. Genes are considered DE compared to anaerobic steady state, if |fold change (FC)| > 2 and false discovery rate (FDR) corrected p value < 0.05.

Figure 2

Loadings of principal component 1. Most positively loaded genes are given in the top row (a–c), negatively loaded genes in the bottom row (d–f). RPKM: reads per kilobase per million reads.

Figure 3

Loadings of principal component 2. Most positively loaded genes are given in the top row (a–c), negatively loaded genes in the bottom row (d–f).

Figure 4

Selection of regulon and gene ontology (GO) enrichments of upregulated (a) and downregulated (b) genes compared to anaerobic state. Full list is available from Figure S5. p values with Bonferroni correction of the enrichments are represented.

Figure 5

Calculation and overview of transcriptional elongation rates (TERs). (a) The calculation method is illustrated with the example of the cydAB-operon. Depicted is the expression of the 0th (1–300 nt), 4th (1201–1500 nt), and 8th (2401–2700 nt) bin of the operon (in RPKM ± standard deviation) together with the ordinary differential equation fit of the data. (b) The time points of the kinks are plotted over the positions of the respective bins. The inverse slope of a linear regression of these data gives the TER of the operon, the intersection with the y-axis (position 0 of the operon) gives the delay of transcription initiation. (c) Histogram of the resultant TERs compared to those obtained by Chen et al. [13]. (d) Histogram of the obtained transcription delay times. (e) Comparison of the TERs of individual operons obtained by oxygen and rifampicin methods; log₂ ratios are indicated together with upregulation (red) or downregulation (orange) of the oxygen treatment group. Detailed data are available in Table S4.