Presentation is loading. Please wait.

Presentation is loading. Please wait.

An RpaA-Dependent Sigma Factor Cascade Sets the Timing of Circadian Transcriptional Rhythms in Synechococcus elongatus  Kathleen E. Fleming, Erin K. O’Shea 

Similar presentations


Presentation on theme: "An RpaA-Dependent Sigma Factor Cascade Sets the Timing of Circadian Transcriptional Rhythms in Synechococcus elongatus  Kathleen E. Fleming, Erin K. O’Shea "— Presentation transcript:

1 An RpaA-Dependent Sigma Factor Cascade Sets the Timing of Circadian Transcriptional Rhythms in Synechococcus elongatus  Kathleen E. Fleming, Erin K. O’Shea  Cell Reports  Volume 25, Issue 11, Pages e3 (December 2018) DOI: /j.celrep Copyright © 2018 The Authors Terms and Conditions

2 Cell Reports 2018 25, 2937-2945.e3DOI: (10.1016/j.celrep.2018.11.049)
Copyright © 2018 The Authors Terms and Conditions

3 Figure 1 RpaA-Dependent Timing of rpoD2, rpoD6, rpoD5, and sigF2 Transcripts and Their Encoded Protein Products (A) Profile of phosphorylated RpaA (RpaA∼P) measured by immunoblotting of protein extracts from wild-type cells grown under constant light. Shown are profiles of rpoD2, rpoD6, rpoD5, and sigF2 mRNA measured by qRT-PCR from wild-type cells grown under constant light. The levels were normalized to the interval [0 1] for each mRNA; points in the plot represent the mean of three biological replicates, and error bars displaySEM. The levels of 1.0 and 0.0 on the y axis correspond to the maximum and minimum levels of the mRNA measured over the time series, respectively, as done by Markson et al. (2013). Subjective day is shaded light yellow. Subjective night is shaded light gray. (B) RpoD6, RpoD5, and SigF2 profiles measured by immunoblotting of extracts from epitope-tagged sigma factor strains grown under constant light. Points represent the mean of three biological replicates, and error bars display the SEM (see also Figure S2). Subjective day is shaded light yellow. Subjective night is shaded light gray. (C) Active RpaA (RpaA-D53E) profile measured by immunoblotting of extracts from the OX-D53E strain (kaiBCΔ, rpaAΔ, Ptrc::rpaA(D53E)) and OX-D53E sigma factor knockout strains before (T = 0 hr, corresponding to subjective dawn) and after induction by addition of IPTG; points represent the mean of two biological replicates, and error bars display range. Shown are profiles of rpoD2, rpoD6, rpoD5, and sigF2 mRNA measured by RNA-seq before (at T = 0 hr) and after induction of active RpaA by addition of IPTG; levels were normalized to the interval [0 1] for each mRNA. Points in the plot represent the mean of two biological replicates, and error bars display the range. Subjective day is shaded light yellow. (D) RpoD6, RpoD5, and SigF2 profiles measured by immunoblotting of extracts from OX-D53E epitope-tagged sigma factor strains before (T = 0 hr) and after induction of active RpaA by addition of IPTG. Points in plots represent the mean of two biological replicates, and error bars display the range (see also Figure S3). Subjective day is shaded light yellow. Cell Reports  , e3DOI: ( /j.celrep ) Copyright © 2018 The Authors Terms and Conditions

4 Figure 2 The RpaA-Dependent Sigma Factor Genes rpoD2, rpoD6, rpoD5, and sigF2 Are Required for Proper Expression of Circadian mRNAs (A) Temporal dynamics of circadian mRNA abundances (displayed in grayscale heatmap format) in wild-type and OX-D53E parental strains lacking sigma factors. Time series mRNA levels from one biological replicate measured by RNA-seq for each strain were normalized to the interval [0 1]; analysis of the second biological replicate shows similar results. Colored heatmaps display the ratio of maximum mRNA abundance in the sigma factor knockout strain relative to that in the parental strain for each circadian mRNA normalized to interval [ ], reflecting a 3-fold or more reduction and a 3-fold or more increase, respectively. The rows in all heatmaps are sorted based on phasing of circadian mRNA abundances in the wild-type strain; the clustergram function was utilized in MATLAB. Data for high-confidence circadian mRNAs (n = 336) are displayed (STAR Methods). The data displayed for mRNA abundances in wild-type cells are from Markson et al. (2013) (GEO: GS350922). (B) Scatterplots displaying alterations to phasing and peak expression for each circadian mRNA in each sigma factor knockout strain relative to the parental strain for the data shown in (A). Displayed on y axis is the ratio of maximum expression in the sigma factor knockout strain compared with maximum expression in the reference strain; a ratio of 1 reflects no peak amplitude differences for a given transcript in the sigma factor knockout strain compared with the parental strain. Displayed on the x axis is the cross-correlation value of the time series mRNA levels, normalized to the interval [0 1], in the sigma factor knockout strain compared with the parental strain. This value ranges from 0, reflecting a strong negative correlation, to 1, reflecting a strong positive correlation; the crosscorr function was utilized in MATLAB. Points in plots are colored pink when x value < 0.5 or when 0.5 ≥ y value or when y value ≥ 2.0. Dashed blue lines box the area containing points colored in black representing mRNAs with unchanged dynamics (cross-correlation less than 0.5) and/or unchanged peak amplitude (less than a 2-fold increase or decrease in the ratio of maximum expression). Cell Reports  , e3DOI: ( /j.celrep ) Copyright © 2018 The Authors Terms and Conditions

5 Figure 3 Perturbations of RpaA-Dependent Sigma Factor mRNA Levels Reveal Sigma Factor Interdependencies (A) Profiles of rpoD2, rpoD6, rpoD5, and sigF2 mRNA measured by RNA-seq in wild-type and sigF2Δ strains grown under constant light conditions; levels were normalized per mRNA to the interval [0 1], representing the expression range measured in the wild-type parental strain. Points in sigF2Δ curves represent the mean of two biological replicates, and error bars display the range. Subjective day is shaded light yellow. Subjective night is shaded light gray. (B) Profiles of rpoD2, rpoD6, rpoD5, and sigF2 mRNA measured by RNA-seq before (T = 0 hr) and after induction of active RpaA by addition of IPTG in the OX-D53E strains lacking rpoD2, rpoD6, or rpoD5; levels were normalized per mRNA to interval [0 1], representing the expression range measured for that mRNA in the OX-D53E parental strain. Shown are profiles of rpoD2, rpoD6, rpoD5, and sigF2 mRNA measured by qRT-PCR before (T = 0 hr) and after induction of active RpaA by addition of IPTG in the OX-D53E strain, with rpoD2 driven by the Synpcc7942_0456 promoter; levels were normalized per mRNA to interval [0 1], representing the expression range measured for that mRNA in the OX-D53E parental strain. Points in plots represent the mean of two biological replicates, and error bars display range. Subjective day is shaded light yellow. (C) A wiring diagram obtained by manual curation, taking into account the dependencies among the sigma factor genes rpoD2, rpoD6, rpoD5, and sigF2 observed in (A) and (B). Arrow-headed lines and bar-headed lines indicate activation and inhibition, respectively. Cell Reports  , e3DOI: ( /j.celrep ) Copyright © 2018 The Authors Terms and Conditions

6 Figure 4 Changes to High-Confidence Circadian mRNAs in Different Sigma Factor Knockout Strains Are Consistent with Predictions Based on the RpaA-Dependent Sigma Factor Cascade (A) Combination heatmap displaying, for each sigma factor knockout strain, the correlation of temporal mRNA abundance in a sigma factor knockout strain relative to that in the parental strain and the ratio of maximum mRNA abundance in the sigma factor knockout strain relative to that in the parental stain for circadian mRNAs (n = 336). The former metric is the cross-correlation value with lag = 0 of the time series mRNA levels normalized to interval [0 1] in the sigma factor knockout strain compared with the reference strain; this cross-correlation value ranges from −1 to 1, reflecting a negative or positive correlation, respectively. The crosscorr function was utilized in MATLAB. The latter metric is displayed normalized to interval [ ], reflecting a 3-fold or more reduction and a 3-fold or more increase in the sigma factor knockout strain relative with the parental strain. The heatmap rows were ordered based on hierarchical clustering that minimizes Euclidean distance. The clustergram function was utilized in MATLAB. The light and dark blue brackets indicate prominent clusters I and II, respectively. (B) Bar graphs displaying the averages of the metrics in (A) across all circadian mRNAs in the bracketed clusters I and II in (A). Error bars display the SEM. Statistical significance was determined by ordinary one-way ANOVA multiple comparison test conducted in Prism7 software. Cell Reports  , e3DOI: ( /j.celrep ) Copyright © 2018 The Authors Terms and Conditions


Download ppt "An RpaA-Dependent Sigma Factor Cascade Sets the Timing of Circadian Transcriptional Rhythms in Synechococcus elongatus  Kathleen E. Fleming, Erin K. O’Shea "

Similar presentations


Ads by Google