Viral protein instability enhances host-range evolvability - PubMed (original) (raw)
Viral protein instability enhances host-range evolvability
Hannah M Strobel et al. PLoS Genet. 2022.
Abstract
Viruses are highly evolvable, but what traits endow this property? The high mutation rates of viruses certainly play a role, but factors that act above the genetic code, like protein thermostability, are also expected to contribute. We studied how the thermostability of a model virus, bacteriophage λ, affects its ability to evolve to use a new receptor, a key evolutionary transition that can cause host-range evolution. Using directed evolution and synthetic biology techniques we generated a library of host-recognition protein variants with altered stabilities and then tested their capacity to evolve to use a new receptor. Variants fell within three stability classes: stable, unstable, and catastrophically unstable. The most evolvable were the two unstable variants, whereas seven of eight stable variants were significantly less evolvable, and the two catastrophically unstable variants could not grow. The slowly evolving stable variants were delayed because they required an additional destabilizing mutation. These results are particularly noteworthy because they contradict a widely supported contention that thermostabilizing mutations enhance evolvability of proteins by increasing mutational robustness. Our work suggests that the relationship between thermostability and evolvability is more complex than previously thought, provides evidence for a new molecular model of host-range expansion evolution, and identifies instability as a potential predictor of viral host-range evolution.
Conflict of interest statement
The authors have declared that no competing interests exist.
Figures
Fig 1. Experimental system and selection for thermostability.
A: To generate our experimental system, we began with an unstable OmpF+ genotype (7-mut) and edited out a critical mutation (N1107K), creating an OmpF—genotype that remained unstable and was on the verge of evolving OmpF+. Stability plots: n = 6 replicates for 6-mut, n = 3 replicates for ancestor, and n = 3 replicates for 7-mut. Comparisons of 6-mut and 7-mut to ancestor were made using paired t-tests corrected for multiple comparisons by Bonferroni method (ancestral λ to 6-mut: p = 8.55x10-4; ancestor to 7-mut: p = 9.80 x 10−4). Bonferroni corrected significance thresholds: ns: p > 0.0024, *: p < 0.0024, **: p < 0.00024, ***: p < 2.4x10-5. **B:** We then selected the 6-mut for enhanced thermostability, generating two naturally evolved thermostable genotypes: T987A and F1122L. Stability plots: n = 6 replicates for 6-mut, n = 3 replicates for T987A, and n = 3 replicates for F1122L. Comparisons of 6-mut and 7-mut to ancestor were made using paired t-tests corrected for multiple comparisons by Bonferroni method (6-mut to 6-mut T987A: p = 1.40 x 10−5; 6-mut to 6-mut F1122L: p = 2.73 x 10−5). Bonferroni corrected significance thresholds: ns: p > 0.0024, *: p < 0.0024, **: p < 0.00024, ***: p < 2.4x10-5.
Fig 2. Evolution experiment with naturally occurring thermostable genotypes.
A: A ten-day evolution experiment was performed to assess OmpF-use evolvability. B: Evolutionary trajectories of six replicate populations of each starting genotype are denoted by six parallel lines. When λ evolves the innovation or goes extinct is indicated by symbols indicated in legend. Brackets surround replicates from two different ways of running the coevolution, which did not appear to impact whether OmpF+ evolved. C: A single plaque from each replicate population was sequenced on the first day OmpF+ was detected. Mutations are indicated along the top. Boxes with colored fill indicate that the amino acid change occurred in an isolate. The fill color indicates the stability of the genotypic background in which the mutation evolved (teal = unstable, red = thermostable.) Population IDs are indicated by letters.
Fig 3. Evolution experiment with engineered library genotypes.
We generated additional variants of 6-mut differing only at the amino acid at position 987 in J. A: Most variants were more thermostable than 6-mut, but T987L remained as unstable as 6-mut. N = 3 replicates per genotype. Comparisons to 6-mut decay rate were made using paired t-tests corrected for multiple comparisons by the Bonferroni method (6-mut T987L: p = 0.510; 6-mut T987C: p = 7.58 x 10−8, 6-mut T987S: p = 1.02 x 10−5, 6-mut T987G: p = 1.26 x 10−4, 6-mut T987K: p = 8.55 x 10−4, 6-mut T987R: 2.96 x 10−6, 6-mut T987Y: p = 7.26 x 10−6.) B: We measured the evolvability of OmpF+ in each variant using a nearly identical evolution experiment as in Fig 2A and 2B. C: A single plaque from each replicate population was sequenced on the first day OmpF+ was detected. Mutations are indicated along the top. Boxes with colored fill indicate that the amino acid change occurred in an isolate. The fill color indicates the stability of the genotypic background in which the mutation evolved (teal = 6-mut, dark red = engineered codon 987 variants.) Population IDs are indicated by letters. Asterisks along the lines indicate significant differences in decay rate between the genotypes connected by the line (Bonferroni adjusted significance: ns: P > 0.05, *: P <0.05, **: P < 0.01, ***: P< 0.001, ****: P < 0.0001).
Fig 4. Mapping thermostabilizing and putative destabilizing mutations on a structural prediction of J’s reactive region.
We used Alphafold [31] to predict the structure of the reactive region of J (amino acids 960–1132). This structure corresponds to the 6-mut genotype, but the 6-mut prediction was nearly identical to the ancestor prediction (S2 Fig). We then mapped the surface binding mutations (dark blue residues) and the thermostabilizing and destabilizing mutations (light blue residues) onto the structure. Coloration of the backbone indicates model confidence.
Fig 5. Trajectories of evolution of OmpF+ in unmodified and stabilized backgrounds.
Evolutionary trajectories of selected isolates from the replay experiment, reconstructed with genomic engineering. In the 6-mut (teal), a single mutation led to an OmpF+ genotype. In three stabilized backgrounds (naturally evolved = red, engineered = dark red), an additional destabilizing mutation was required as a steppingstone to the OmpF+ genotype. Asterisks along the lines indicate significant differences in decay rate between the genotypes connected by the line, as compared by paired t-tests corrected for multiple comparisons using the Bonferroni method. First panel: 6-mut vs. 6-mut N1107K: p = 0.678; Second panel: 6-mut vs. 6-mut T987A: p = 1.88x10-6; 6 -mut T987A vs. 6-mut T987A S970Y: p = 0.0055; 6-mut T987A S970Y vs. 6-mut T987A S970Y N1107K: p = 0.3818; Third panel: 6-mut vs 6-mut F1122L: p = 9.25x10-5; 6-mut F1122L vs. 6-mut F1122L L122F: p = 5.13x10-5; 6-mut F1122L L122F vs. 6-mut F1122L L1122F S1049R: p = 0.667; Fourth panel: 6-mut vs. 6-mut T987S: p = 2.65x10-5; 6-mut T987S vs. 6-mut T987S T987L: p = 1.83x10-5; 6-mut T987S T987L vs. 6-mut T987S T987L S1011R: p = 0.143. (Bonferroni adjusted significance: *: p < 0.0167, **: p < 0.00167, ***: p < 0.000167, ****: p < 1.67e-5).
Fig 6. Growth rates of naturally occurring thermostable genotypes and engineered library genotypes.
Growth rates on REL606 in M9 glucose + MgSO4 media over four hours. Comparisons to 6-mut growth rate were made using paired t-tests corrected for multiple comparisons using the Bonferroni method, N = 3 per genotype. Significantly higher: T987A: p = 0.002; significantly lower: F1122L: p = 4.12x10-5; T987G: p = 0.0052; no difference: T987L: p = 0.695; T987S: p = 0.068; T987K: p = 0.105; T987R: p = 0.419; T987Y: tstat = p = 0.150 Bonferroni adjusted significance: ns: P > 0.0056, *: P <0.0056, **: P < 0.00056, ***: P< 0.000056.
Fig 7. Stability and evolvability of 5-mut and 5-mut T987A stable variant.
A: In a background that is further away from evolving OmpF+ (two mutations reverted compared to one mutation in 6-mut), the T987A mutation is still stabilizing. B: In the 5-mut background, T987A reduces evolvability to an even greater extent. Two sample t-test for unequal variance, N = 3 per genotype, **: P = 0.0069.
References
- Stern A, Andino R. Viral Evolution: it is all about mutations. In Katze MG, Law GL, Korth MJ, Nathanson N editors. Viral Pathogenesis (3rd edition). New York: Academic Press; 2016. pp. 233–240.
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