Stochastic activation of a DNA damage response causes cell-to-cell mutation rate variation

Abstract

Cells rely on the precise action of proteins that detect and repair DNA damage. However, gene expression noise causes fluctuations in protein abundances that may compromise repair. For the Ada protein in Escherichia coli, which induces its own expression upon repairing DNA alkylation damage, we found that undamaged cells on average produce one Ada molecule per generation. Because production is stochastic, many cells have no Ada molecules and cannot induce the damage response until the first expression event occurs, which sometimes delays the response for generations. This creates a subpopulation of cells with increased mutation rates. Nongenetic variation in protein abundances thus leads to genetic heterogeneity in the population. Our results further suggest that cells balance reliable repair against toxic side effects of abundant DNA repair proteins.

Fig. 1. Stochastic gene expression delays Ada response activation in a cell subpopulation

(A) Methylation of Ada N- and C-terminal domains functions as a damage sensor, turning Ada into an auto-regulatory activator of genes involved in DNA alkylation repair. (B) Ada-mYPet fluorescence (yellow) in cells treated with 10 mM MMS for 1 hour. Constitutive mKate2 serves as fluorescent cell marker (gray). Scale bar, 5 µm. (C) Percentage of cells that activated Ada-mYPet expression after 1 hour in MMS. (Inset) Histogram of Ada-mYPet fluorescence per cell with 10 mM MMS. (D and E) Time traces of Ada-mYPet fluorescence in single cells treated with 50 µM and 750 µM MMS (added at time 0). Example cells in yellow; time in units of average generation times (42 min) throughout. (F) (Inset) Transformed cumulative distribution log(1-CDF) of response delay times for the last 30% of cells to activate Ada-mYPet expression upon MMS treatment in the microfluidic chip. Different MMS concentrations in colours as in main plot. Straight lines on log scale reflect exponential distributions as generated by a Poisson process; the slope corresponds to the average delay time constant. Gray area: Poisson process with a rate of 1 ± 0.1 per generation. Main plot: Average delay time constants from the inset data (±SEM). (G) Single-molecule counting of Ada-mYPet without MMS. Example cell shown. Poisson model was generated using measured production rate of 1 molecule per generation. Note that the actual value may be closer to 1.2 because of delayed maturation of mYPet (see supplementary materials).

Fig. 2. Single-molecule trigger of the Ada response

(A) Stochastic expression and random segregation of molecules at cell division creates a subpopulation of cells with zero Ada molecules which therefore fails to autoinduce the adaptive response. (B) Sections of time traces showing distinct steps in Ada-mYPet expression rates during response activation upon 200 µM MMS treatment, deactivation after MMS removal, and stochastic activation and deactivation transitions with 100 µM MMS. Vertical lines indicate cell divisions. Histograms show number of frames spent in the expression rate states. Losses can occur due to rare meAda degradation or by segregation at cell division. At very low numbers, all meAda molecules should sometimes remain in the same cell, maintaining expression rates as observed. (C) Uniform Ada-mYPet induction when cell division was inhibited with cephalexin prior to MMS treatment (orange). (D) Uniform accumulation of endogenous Ada-mYPet with additional MiniF plasmid carrying P_Ada ada (green). Scale bars, 5 µm.

Fig. 3. High precision of the Ada response

(A) Cell fates after treatment with 10 mM MMS for 1 hour: Percentages of cells failing to recover growth during time-lapse microscopy without MMS for 3 hours (±SEM). Cells were distinguished if they had activated (Ada on) or failed the response (Ada off). (B) Percentages of cells spontaneously triggering Ada-mYPet expression without MMS (±SEM). (C) Fano factors (variance/mean) for Ada-mYPet without MMS, using single-molecule counting data (Fig. 1G, ±SEM bootstrapped). Cells grouped by size. Expression bursting would give Fano factors above Poisson limit of 1. (D) Dual reporter assay: Delay times between MMS addition and response activation for endogenous ada-mYPet and ectopic P_Ada cfp are closely correlated. Each dot represents one cell. Inset: Example expression rate time-traces with simultaneous activation of both genes. (E) Example time-traces showing correlated expression rate fluctuations of the dual reporter genes and simultaneous response deactivation after MMS removal. (F) Deterministic response deactivation: Time-traces following MMS removal at time 0 (average: yellow). The dilution model (circles) has an exponential decay constant equal to the average generation time. Inset: Narrow distribution of delay times from MMS removal until response is deactivated (dotted line threshold).

Fig. 4. Increased binding of mismatch recognition protein MutS in cells with delayed Ada response

Photoactivated single-molecule tracking of MutS-PAmCherry and Ada-mYPet fluorescence in single cells treated with 10 mM MMS for 1 hour. (A) Tracks of bound (red) and mobile MutS (blue). Cell outlines drawn; scale bars, 2 µm. (B) Percentage of bound MutS molecules vs. Ada-mYPet fluorescence per cell. Native strain with (yellow) and without MMS (black); Δada with MMS (gray).