Skip to main content
. 2022 Jul 8;11:e76095. doi: 10.7554/eLife.76095

Figure 1. Distinct adaptation to paraquat.

(A) Mean temporal adaptive response to paraquat and seven other stressors. y-axis shows log2 fold reduction in cell doubling time (h) from pre-stress, adjusting for plate, position and pre-culture effects. 96 populations for each stressor (n=6). Shade: S.E.M. (B) Loss of the acquired adaptation as a function of number of cell generations after release from the selection pressure. Colored lines: mean of 96 populations (each measured at n=5). Shade: S.E.M. The populations were released from stress after reaching 70–90% of their endpoint (t50) adaptation. (C) The difference in cell doubling time (h) in a no-stress environment between 96 populations (each measured at n=5) having achieved 70–90% of their endpoint adaptation to paraquat, arsenic and glycine, respectively, and the founder population. The difference reflects the selective advantage of losing the acquired adaptations when the populations are no longer exposed to stress. p-values: one-sided t-test. Error bars: S.E.M. See also Figure 1—figure supplements 1 and 2.

Figure 1—source data 1. Doubling time data of 96 populations adapted to each of eight different environments over G generations; doubling times are in the respective selection environment.
Data are shown in Figure 1A and Figure 6D.
Figure 1—source data 2. Difference in doubling time in absence of stress and in the respective selection environment, for adapted populations having achieved 70-90% of their final adaptation.
Data are shown in Figure 1C.
Figure 1—source data 3. Doubling time data of 96 populations adapted to paraquat, arsenic and glycine over Gs generations and then released from selection for Gr generations; doubling times are in paraquat, arsenic, and glycine, respectively.
Data are shown in Figure 1B.
elife-76095-fig1-data3.xlsx (235.1KB, xlsx)

Figure 1.

Figure 1—figure supplement 1. Titration of the paraquat (PQ) dose and design of adaptation experiment.

Figure 1—figure supplement 1.

(A) Mean doubling time of wildtype yeast cell populations grown with and w/o (0-400 μg/mL) of paraquat. Error bars: S.E.M. (n=122-144). (B) Left panel: Color columns show the mRNA expression (FPKM; Fragments Per Kilobase Million) of CCP1, SOD1, and SOD2, during the first, second, and third growth cycle in the presence of 400 μg/mL paraquat. Note that the cells have not yet been exposed to paraquat at time, t=0 in Cycle 1. Right panel: mRNA expression in the founder population in a paraquat-free growth medium. x-axis: time (h) in each growth cycle. y-axis: Expression values are shown as a log2 ratio in relation to expression in a paraquat-free medium at t=0. Error bars: S.E.M (n=3). * = significant (Wald test, FDR q=0.05) difference. (C) Schematic representation of how vitamin C counters paraquat toxicity. Outside cells, paraquat remain in the colorless ionic Pq2+ state. Upon cellular and mitochondrial uptake, Pq2+ accepts electrons from OXPHOS complex III and assumes the damaging Pq+ free radical form, which turn cells slightly blue. Pq+ donates an electron to O2, forming O2∙− while resuming the Pq2+ state. When present, vitamin C, accepts electrons from Pq+, preventing it from generating O-2. This shifts paraquat back to the colourless Pq2+ state. Vitamin C may also accept electrons from the O2∙− that is formed, further reducing the intracellular pool of O2∙−. (D) Growth (mean) of wildtype (left panel; n=96) and sod2Δ (right panel; n=96) yeast cell populations in the absence and presence of 400 μg/mL of paraquat and/or 180mM of the antioxidant ascorbic acid. Shade=S.E.M. (E) Design of adaptation experiment. We adapted 96 initially homogeneous, asexually reproducing, haploid yeast populations to paraquat ( stress) and seven non-mitochondrial challenges (Supplementary file 1) over 50 growth cycles (t1-t50). Populations were maintained as an array of 96 colonies on solid agar medium in which the stressor had been imbedded. Each growth cycle corresponded to 72 h of growth from lag to stationary phase, in which ~5x104 cells were subsampled to seed the next growth cycle. We stored subsamples from the end of batch cycles 0-5, 7, 9, 12, 15, 20, 25, 30, 35, 40, 45, and 50 of all 96 populations as a frozen record. We revived and reanalyzed these (n=6) in a randomized design to accurately capture the adaptation kinetics for 768 populations. We counted cells in each population at 20 min intervals and extracted cell doubling times, (D), from the mid-exponential phase and estimated cell generations, (G), as the number of population doublings from the start to end of each batch cycle. We extracted cell doubling times, (D), and log2 normalized these to those of many founder controls, Dnorm. We subtracted the Dnorm before stress exposure, Dnorm,0, to estimate the doubling time adaptation achieved, which is annotated as Log2 (D) ratioadj.
Figure 1—figure supplement 1—source data 1. FPKM data of selected oxidative defense genes, obtained from RNA-sequencing of cells exposed to paraquat.
Data are shown in Figure 1—figure supplement 1.
Figure 1—figure supplement 1—source data 2. Doubling time data of WT, mip1Δ and sod2Δ populations, with and without paraquat and with and without vitamin C.
Data are shown in Figure 1—figure supplement 1.
Figure 1—figure supplement 1—source data 3. Doubling time data of WT in different concentrations of paraquat.
Data are shown in Figure 1—figure supplement 1A.
Figure 1—figure supplement 2. Comparison of predicted paraquat adaptation with the experimental data.

Figure 1—figure supplement 2.

The experimental adaptation data (green) on 96 populations (each measured at n=6) are the same as in Figure 1. The three prediction graphs generated by the numerical model are each based on 1152 replicate runs. Shade: S.D.
Figure 1—figure supplement 2—source data 1. Doubling time data for the BY4741 single gene deletion collection under paraquat exposure; used as input for simulations in Figure 1—figure supplement 2.
Figure 1—figure supplement 2—source data 2. Doubling time data of disomic strains growing in paraquat; used as input for simulations in Figure 1—figure supplement 2.