Fig 1.
Dynamics of physiology and transcriptome remodeling during a nitrogen upshift.
A) 400μM glutamine was added to a culture of yeast cells growing in minimal media containing 800μM proline as a sole nitrogen source. Measurements of culture density across the upshift are plotted. Dotted lines denote linear regression of the natural log of cell density against time before the upshift and after the 2 hour lag. B) Average cell size during the same experiment. Dotted lines denote the mean cell diameter before the upshift and after the 2 hour lag. C) PCA analysis of global mRNA expression in steady-state chemostats and following an upshift [25]. Steady-state nitrogen-limited chemostat cultures maintained at different growth rates (colored circles) primarily vary along principal component 2. Expression following a nitrogen-upshift in either a chemostat (squares) or batch culture (triangles) show similar trajectories and vary along both components. Grey lines depict the major trajectory of variation for steady-state and upshift experiments.
Fig 2.
Global mRNA stability changes following a nitrogen upshift.
A) 4tU-labeled mRNA from each gene was measured over time, before and after the addition (vertical dotted line) of glutamine (nitrogen-upshift) or water (mock). Linear regression models were fit to the data with a rate before the upshift (solid line) and a change in rate after glutamine addition (dashed line). HTA1 is not significantly destabilized, whereas mRNAs encoding NCR-regulated transporters or pyruvate and trehalose metabolism components are significantly destabilized. Plots for all genes are available in the associated Shiny application (Methods). B) Comparison between the pre-upshift mRNA degradation rate (y-axis) and the post-upshift mRNA degradation rate (x-axis). Details of modeling are in S1 Appendix. C) Comparison between changes in mRNA expression following upshift [25] (y-axis) and the post-upshift degradation rate (x-axis). Transcripts that are significantly destabilized are colored red, and shown with red rug-marks in the marginal histograms.
Table 1.
Summary of mRNA stability and changes upon the upshift.
Shown here are the median rates or changes in rates for the specified sets. Destabilized transcripts were identified using the criteria of a significant (FDR < 0.01) change in estimated degradation rates and at least a doubling of the rate of clearance.
Fig 3.
GAP1 mRNA dynamics measured by flow cytometry.
A) GAP1 mRNA following upshift measured using RT-qPCR, relative to an external spike-in mRNA standard. The dashed line is fit to points 2 minutes after the upshift. B) Flow cytometry of wild-type yeast probed for GAP1 mRNA in nitrogen-limited conditions and following an upshift. The vertical grey lines indicate FACS gate boundaries used for cell sorting. C) Representative cells from each bin sorted from the experiment in panel B. D) Quantification of microscopy data. Each black dot represents a single cell. The mean number of foci per cell in each bin from panel B is displayed as a red point.
Fig 4.
BFF estimates of GAP1 mRNA abundance per mutant.
A) Flow cytometry analysis of GAP1 mRNA abundance in the prototrophic deletion collection (n = 3,230 mutants) before and after the upshift. The vertical gray lines denote boundaries of the four FACS gates. Biological replicates are indicated by color. B) Measurements for individual genes before and after the upshift. Pseudo-events per strain per bin are on the y-axis. Black dashed lines indicate maximum-likelihood fits of a log-normal to pseudo-events within each bin for each mutant. For plotting purposes, points are positioned on the x-axis at the average signal for the library in that bin. Colors are as in panel A. C) Distribution of modeled mean GAP1 mRNA levels for each mutant. D) The mean GAP1 mRNA expression levels fit using all replicate data for individual mutants before and after the upshift are shown as points connected by a line, colored according to the type of gene. The background violin plot shows the distribution of all 3,230 mutants. Plots for all mutants are available in the associated Shiny application (Methods).
Fig 5.
Disrupting the Lsm1-7p/Pat1p complex and translational regulation impairs clearance of GAP1 mRNA.
A) In the background is the distribution of fit GAP1 mRNA mean expression levels for all mutants in the pool. Indicated by colored points and lines are the means for individual knockout strains, as labeled. B-E), GAP1 mRNA relative to HTA1 mRNA before and 10 minutes after a glutamine upshift, in biological replicates. Lines are a log-linear regression fit. Points are dodged horizontally for clarity, but timepoints for modeling and for drawn lines are 0 and 10 minutes exactly. Wild-type is FY4, and each estimate of the GAP1/HTA1 ratio is normalized to the average ratio measured of FY4 at t = 0 for that qPCR batch. B) xrn1Δ, ccr4Δ, pop2Δ are all defective in GAP1 mRNA clearance (p-values < 0.004). C) lsm1Δ and lsm6Δ are slowed in GAP1 mRNA clearance (p-values < 0.0132 and 0.0299, respectively). D) edc3Δ is slowed in GAP1 mRNA clearance (p-value < 10−4). scd6Δ and tif4632Δ are slowed in GAP1 mRNA clearance (p-values < 10−5) and have lower levels of expression before the upshift (p-values < 0.003). E) A deletion of 150bp 3’ of GAP1 stop codon has no significant effect, but a deletion of 100bp 5’ of the start codon has a defect in GAP1 mRNA clearance (p-value < 10−4) and lower level of expression before the upshift (p-value < 0.0015).