We systematically made genetic variants in four windows of interest in the kinase domain of PKR (Figure 1D). The four windows were selected based on having sites within five angstroms of eIF2α or K3 and sites under positive selection across vertebrate PKR homologs as identified by Rothenburg et al., 2009. Our windows of interest include helix αD and αG, as well as the glycine-rich loop and activation loop surrounding the ATP-binding site. In these windows, we focused on testing 426 variants that could be acquired with a single nucleotide change from the predominant human PKR allele (Genbank M85294.1; Figure 1—figure supplement 1), as those are the most likely to be evolutionarily sampled.

Overexpression of PKR in the budding yeast Saccharomyces cerevisiae is toxic, as PKR auto-activates and shuts down protein synthesis by phosphorylating yeast eIF2α, which is highly conserved between yeast and humans (Chong et al., 1992; Dever et al., 1993). This toxicity can be partially counteracted by co-expression of vaccinia K3 (Kawagishi-Kobayashi et al., 1997). Thus, yeast provides a useful experimental system to test the functionality of PKR variants: variants that maintain the ability to phosphorylate eIF2α while escaping K3 inhibition will further arrest growth, while variants that lose eIF2α kinase activity or become more susceptible to K3 will improve growth.

We sought to leverage this assay in a high-throughput manner to determine the functionality of PKR variants by tracking their abundances in a pool over time. We generated the 426 single-residue variants of PKR on a single-copy plasmid with a galactose-inducible promoter in a plasmid pool (Figure 1E). Each unique plasmid in the pool carried a DNA barcode randomly generated during cloning. We used long-read circular consensus sequencing to pair DNA barcodes with PKR variants, identifying an average of 43 barcodes per variant (Figure 1—figure supplement 1). We then created three libraries by combining the PKR variant library with wild-type K3, nonfunctional K3, or the enhanced mutant allele K3-H47R (Kawagishi-Kobayashi et al., 1997; Elde et al., 2012). The K3 alleles were expressed from a constitutive TDH3 promoter. We transformed the three PKR-K3 paired libraries in duplicate into yeast grown in glucose media, such that PKR expression was repressed. We then inoculated the libraries in liquid galactose media to induce PKR expression, and sampled cells at 0, 12, 16, and 20 hr post-inoculation. We quantified the abundance of the PKR variants at each timepoint using high-throughput short-read sequencing of the DNA barcodes. For each PKR variant we calculated a functional score against each K3: PKR variants that evade K3 inhibition and reduce yeast growth have high functional scores, while PKR variants that are non-functional or are inhibited by vaccinia K3, and thus are associated with good yeast growth, have low functional scores (Figure 1—figure supplement 2). The correlation of functional scores between replicates 1 and 2 was very strong (Pearson correlation coefficient >0.98 for each K3 allele, Figure 1—figure supplement 3), so we combined the reads from replicates 1 and 2 to generate PKR functional scores for subsequent analyses.

We first examined how each PKR variant performed against wild-type K3. We were encouraged to find that variants previously characterized as resistant to K3-H47R (Seo et al., 2008) were resistant to wild-type K3 in our screen (Figure 2A). We found many additional K3-resistant variants across all four tested windows and validated select PKR variants using serial dilution to measure yeast growth (Figure 2—figure supplement 1). Notably, every variant made at Glu375 increased evasion of K3, with the exception of Glu375Asp. In the AlphaFold2-predicted complex, Glu375 forms an attractive electrostatic interaction with Lys45 of K3 (Figure 2B). Consistent with our findings, this predicted interaction would be disrupted by all tested variants at site 375 aside from the negatively charged aspartic acid. Interestingly, Glu375 is the only site under positive selection in vertebrates that was proximal to K3 but not eIF2α in the AlphaFold2 models, making it a prime candidate for disrupting K3 inhibition without affecting eIF2α phosphorylation.

We found a large number of K3-resistant variants in the vicinity of PKR’s helix αG (Figure 2C and D). Compared to other protein kinase structures, eIF2α kinases have a noncanonical helix αG that is extended by one full turn and rotated 40° counterclockwise with a 5 angstrom translation relative to its C-terminus, owing to a reduced αF-αG linker (Dar et al., 2005). The noncanonical orientation of helix αG contributes to both eIF2α binding specificity and Ser51 presentation to PKR (Dar et al., 2005). It has been proposed that mutations causing movement in helix αG might be especially capable of disrupting K3 binding due to the rigid structure of K3 between its contact points on helix αG and the PKR active site. In contrast, PKR mutations that move helix αG could be tolerated in the context of eIF2α binding because eIF2α contacts PKR’s active site using a flexible loop (Dar et al., 2005). We observe a gradient of PKR functional scores along the helix αG region, starting with highly resistant or susceptible variants (positions 480–492) and shifting to neutral wild-type-like scores (493-500) (Figure 2A). We identified four sites within or near the N-terminus of helix αG for which many variants evade K3: Glu480, Val484, Glu490, and Thr491 (Figure 2C).

We looked at what features of PKR were associated with sites of K3-resistant variants and were excited to find that sites under positive selection in vertebrates were strongly enriched for K3-resistant variants relative to sites conserved across vertebrate PKRs (Figure 2E). Comparing K3 contact and non-contact sites, we find significantly lower functional scores at K3 contact sites (Figure 2F). However, functional scores at K3 contact sites form a bimodal distribution (Hartigan’s dip test statistic = 0.105, p<0.0001). Considering only functional variants (PKR functional score > –2) we find that variants at K3 contact sites have significantly higher functional scores than those at non-contact sites (Figure 2—figure supplement 2). Thus, variants at K3 contact sites tend towards large effects either improving or diminishing PKR function versus K3.

To understand the constraint placed on the PKR kinase domain, we examined variants that failed to maintain PKR function. We screened our PKR variant library against a nonfunctional K3 (hereafter referred to as K3∆58) in which the first 173 bases were deleted, removing the first 58 residues, including the initial methionine. When paired with K3∆58, most PKR variants were comparable to wild-type PKR (Figure 3A), suggesting the tested regions were not highly functionally constrained for kinase activity despite their proximity to eIF2α during its phosphorylation. The few highly constrained sites include Gly276 and Gly277, which compose the glycine-rich loop above the ATP-binding site; Gly450 and Thr451 in the activation loop; and Thr487 in helix αG, which stabilizes helix αG (Dar et al., 2005) and induces the conformational change in eIF2α required for its phosphorylation (Figure 3B; Dey et al., 2011). We also found proline variants to generally disrupt PKR function (Figure 3C). We found nonfunctional variants of varying degrees in all four windows of interest, but with very few in helix αD and the C-terminus of helix αG (Figure 3C), consistent with these regions having pliable secondary structures in which variants can evade K3 while not disrupting eIF2α recognition.

More PKR variants had low functional scores in the presence of functional K3 (Figure 2A) than in its absence (Figure 3C). We plotted the functional scores against each other (Figure 4A), and found that variants with low PKR functional scores versus K3 separated into two classes: some switched to high functional scores in the absence of K3, indicating they caused enhanced susceptibility to K3 but otherwise retained PKR function, while others had low functional scores in both conditions, indicating they had diminished eIF2α kinase activity irrespective of K3 antagonism. We quantified this effect by calculating residuals from the line connecting PKR nonsense variants to PKR-WT, which highlights variants whose functional scores diverged between the K3 conditions. We find that the activation loop and the start of helix αG, which were less tolerant of mutation when paired with wild-type K3 (Figure 2D), contain a mix of variants that lose function outright or that increase susceptibility to K3 (Figures 3B–C–4B–C). Variants at five sites were especially susceptible to K3 inhibition: Phe278, Thr373, Arg453, Phe489, and Ser492 (Figure 4B). None appear under positive selection across vertebrates, and Phe278 is conserved across vertebrate PKR homologs. Interestingly, Phe278 is predicted to form a pi interaction with His47 of K3, which aligns to Arg52 of eIF2α (Figure 4—figure supplement 1; Kawagishi-Kobayashi et al., 1997). Mutation of K3-H47 to arginine, matching eIF2α, is known to improve K3’s antagonism of PKR (Kawagishi-Kobayashi et al., 1997; Elde et al., 2012), suggesting PKR can discriminate against K3 based on its difference from eIF2α at this position. This is consistent with our observation of the importance of Phe278 specifically in the presence of K3.

We also characterized PKR variants in the presence of an enhanced mutant allele of K3, K3-H47R (Figure 5). This mutant allele was first identified in a genetic screen of K3 mutants as an enhanced antagonist of PKR (Kawagishi-Kobayashi et al., 1997) and independently identified in a directed evolution screen (Elde et al., 2012). We sought to understand the resilience of improved PKR variants to alternative K3 alleles by examining the concordance between beneficial PKR variants against wild-type K3 and K3-H47R. We found strong correlation between PKR functional scores versus K3 and K3-H47R (Spearman correlation = 0.832, Figure 5A). Indeed, many of the K3-resistant variants are also resistant to K3-H47R (Figure 5B–D), suggesting resilience of PKR to allelic variation in K3. A general change is the struggle for PKR to overcome the enhanced inhibition of K3-H47R, compressing the functional score range between wild-type-like and nonfunctional scores. This nonlinear relationship between the functional scores in the two K3 conditions (Figure 5—figure supplement 1) led to some differences in the patterns of resistance to the two K3 alleles. For instance, positively selected PKR sites did not have significantly higher PKR functional scores versus K3-H47R than conserved sites (Figure 5E), a sharp contrast to the PKR functional scores versus wild-type K3 (Figure 2E). This result appears to be caused by the many wild-type-like scores at positively selected sites now being similar to the many nonsense-like scores at conserved sites. We also noted that variants at sites proximal to K3 had slightly higher functional scores than those at non-contact sites (Figure 5F), the opposite of what we observed against wild-type K3 (Figure 2F). This could result from wild-type-like PKR variants being enriched at non-contact sites. Overall, the strong correlation of functional scores versus K3 and K3-H47R suggests K3-resistant variants would often be resilient against alternate K3 alleles.

Previous work identified twelve PKR variants with enhanced resistance to K3-H47R (Seo et al., 2008), nine of which were included in our experiment (Figure 5—figure supplement 2). We examined the other nonsynonymous variants introduced at these sites and found that most sites contained additional novel resistant variants, indicating the previously uncovered individual mutants reflect sites of general opportunity for pseudosubstrate evasion.

One might naively expect a PKR pseudosubstrate inhibitor to be a closer mimic of the natural PKR substrate, eIF2α, which would make it more difficult for PKR to distinguish it from eIF2α. One possibility is that K3 pseudosubstrate divergence from eIF2α has been selected to allow the inhibitor to bind PKR with even higher affinity than eIF2α does. But mutations that improve binding to one species’ PKR homolog might decrease binding to the divergent PKR homologs from other species (Park et al., 2019; Park et al., 2021; Peng et al., 2016). Thus, pseudosubstrate inhibitors of generalist poxviruses may need to evolutionarily balance improving PKR binding for one host against maintaining PKR binding of multiple hosts. Interestingly, the structural component most diverged between K3 and eIF2α, a rigid helix in K3 in place of eIF2α’s flexible phospho-acceptor site, primarily interacts with the residues around the activation loop of PKR (Figure 6C), which we found to be highly functionally constrained. In contrast, amino acids 72–83 of K3 are highly identical to eIF2α and interact primarily with PKR’s divergent helix αG (Figure 4—figure supplement 1). Thus, vaccinia K3 may well have been evolutionarily constrained to avoid limiting host range. While the host range of vaccinia is not fully understood (Smith, 2007), current evidence suggests vaccinia is a generalist (Haller et al., 2014; Park et al., 2021). Poxviruses as a whole infect a very wide range of species, which suggests the ancestral K3 needed to be compatible with a wide host range.

Despite its pliability, PKR helix αG is believed to play a critical role in eIF2α binding and phosphorylation, as it induces a conformational shift in eIF2α that moves the Ser51 phospho-acceptor site into PKR’s ATP-binding site. Based on our findings and positive selection analyses, this conformational shift is apparently amenable to variation in the PKR kinase domain. Perhaps the resilience of the binding surface between PKR and eIF2α could be informative for the budding field of de novo protein design, as resilient design is a critical consideration for vaccines and therapeutics faced with rapidly evolving infectious agents.

We generated the plasmid MSp508_MCS as the base plasmid for all experiments by inserting a multiple-cloning site (MCS) into the single-copy plasmid YCp50, a gift from Mark Rose (Rose et al., 1987). The MCS contained seven unique restriction enzyme cut sites: AgeI, BsiWI, BstEII, NotI, MluI, PvuII, and SacI. YCp50 was digested using restriction enzymes EcoRI-HF (NEB Cat#R3101S) and BspDI (NEB Cat#R0557S) with rCutSmart buffer, followed by purification and size selection on a 1% agarose gel with 0.6 µg/mL ethidium bromide (BioRad Cat#1610433), selecting for the 7,961 bp band. The extracted band was purified using a QIAquick Gel Extraction kit (Qiagen Cat#28706) and eluted with 30 µL of water. For Gibson Assembly the purified band was combined with a single-stranded DNA oligonucleotide containing the MSC and homology arms spanning the digest site, named Oligo 1 (Supplementary file 1), in a 1:5 molar ratio in a total volume of 5 µL, along with an additional 5 µL 2 x Gibson Assembly Master Mix (NEB Cat#E2611L). The reaction mixture was incubated at 50 °C for 1 hr. One microliter of the Gibson Assembly reaction was transformed into 10 µL 5-alpha competent E. coli (NEB Cat#C2987I) and plated onto 10 cm LB-AMP plates (IPM Scientific Cat#11006–016) and incubated overnight at 37 °C. Colonies were selected for overnight outgrowth in 3 mL LB-AMP (IPM Scientific Cat#11006–004), followed by a QIAprep spin miniprep (Qiagen Cat#27106) and Sanger sequencing to validate the plasmid sequence using the primer Oligo 2. This produced the plasmid MSp508_MCS.

We cloned wild-type PKR, wild-type K3, and K3-H47R into the MCS of MSp508_MCS to produce the MSp509_PKR-WT, MSp510_K3-WT, and MSp511_K3-H47R plasmids, respectively. The plasmid p1419 (Kawagishi-Kobayashi et al., 1997) contains the PKR gene (standard name EIF2AK2) under the control of the galactose-inducible pGAL10/CYC1 promoter for yeast expression. We PCR-amplified the PKR expression construct using primers (Oligos 3 and 4) to place pGAL10/CYC1-PKR on MSp508_MCS between AgeI and BstEII. Oligo 4 incorporated a synthetic terminator for PKR, Tsynth1 (Curran et al., 2015), a 28 bp spacer sequence, and a 26 bp barcode (CGCTTAATATGCAATGAAATTGCTTA); the primers added 20 bp homology arms for cloning onto the MSp508_MCS plasmid. PCR was performed using the polymerase PfuUltraII (Agilent Technologies Cat#600674) for 30 cycles with an annealing temperature of 55 °C, followed by gel purification. MSp508_MCS was digested with restriction enzymes AgeI-HF (NEB Cat#R3552S) and BstEII-HF (NEB Cat#R3162S), followed by gel purification. The digested MSp508_MCS and pGAL10/CYC1-PKR fragments were joined via Gibson Assembly in a 1:5 molar ratio, followed by transformation into 5-alpha competent E. coli and plating onto LB-AMP. A resultant clone, validated by Sanger sequencing, was designated MSp509_PKR-WT.

To produce MSp510_K3-WT, the K3L coding sequence was amplified from the plasmid pC140 (Kawagishi-Kobayashi et al., 1997) using primers Oligo 5 and Oligo 6. Similarly, to produce MSp511_K3-H47R, the K3L-H47R coding sequence was amplified from the plasmid pC407 using primers Oligo 6 and Oligo 7. pC140 and pC407 were gifts from Thomas Dever. We note that the K3L alleles on these plasmids carry a Val2Leu mutation relative to the VACV-WR K3L (Genbank AAO89313.1), which was introduced during the cloning of K3L on the original plasmid pTM1 (Carroll et al., 1993). Oligos 5 and 7 incorporated a synthetic terminator (T_synth8) for the K3 allele (Curran et al., 2015), a 28 bp nucleotide spacer sequence, a 26 bp barcode (ATCGTAATAGGTTTCCGGCTTGTTCG and ACAGGAAATGCTTTCGGGGTTGTATT, respectively), and a 20 bp homology arm to MSp508_MCS. The pTDH3 promoter, also known as pGPD, was amplified from genomic DNA of the yeast strain BY4742 (Brachmann et al., 1998) using primers Oligo 8 and Oligo 9. K3-WT, K3-H47R, and pTDH3 were amplified using PfuUltraII, followed by gel purification. MSp508_MCS was digested with restriction enzymes NotI-HF (NEB Cat#R3189S) and PvuII-HF (NEB Cat#R3151S). Each K3 allele (K3-WT and K3-H47R) was joined with a pTDH3 promoter onto the digested MSp508_MCS via Gibson Assembly in a 1:5:5 molar ratio, followed by transformation into 5-alpha competent E. coli and plating onto LB-AMP. Resultant clones, validated by Sanger sequencing, were designated as MSp510_K3-WT and MSp511_K3-H47R.

MSp512_K3∆58 was made by removing nucleotides 1–173 of the K3L sequence of YCp50_K3, leaving codons 59–88 to generate a nonfunctional K3L allele (denoted K3∆58) under the pTDH3 promoter. The K3∆58 sequence was amplified from the MSp510_K3-WT plasmid using primers Oligo 10 and Oligo 11. MSp510_K3-WT was digested with restriction enzymes NotI-HF and MluI-HF (NEB Cat#R3198S), followed by gel purification and size selection for the 8684 bp band. The K3∆58 allele was joined with the MSp508_MCS digested fragment via Gibson Assembly in a 1:5 molar ratio, followed by transformation into 5-alpha competent E. coli and plating onto LB-AMP. A resultant clone was validated by Sanger sequencing and designated as MSp512_K3∆58.

We made the PKR variant library by 15 Gibson Assembly reactions using pairs of PCR amplicons targeting 4 windows of PKR protein sequence: 255–278 (5 pairs of reactions), 371–385 (3 pairs of reactions), 448–455 (2 pairs of reactions), and 480–506 (5 pairs of reactions). In each pair, one of the PCR reactions, PCR-1, utilized a pool of forward primers, termed a variant primer tile set, containing single-base deviations from the PKR sequence to generate all SNP-accessible variants in a stretch of X to Y consecutive codons (Figure 1—figure supplement 4). Each forward primer in a tile set was composed of a 20 bp homology arm, the variant region, and a priming region with a melting temperature of 50 °C. The reverse primer of all PCR-1 reactions had a constant 20 bp homology arm, a barcode region with 20 fully mixed bases, and a constant PCR-priming region homologous to the end of PKR with a melting temperature of 55 °C (Figure 1—figure supplement 5). Mixed bases in the barcodes were limited to 5-nucleotide stretches to prevent the unintended generation of restriction sites, spacing these stretches with ‘AA’ or ‘TT’ sequences (Liu et al., 2019). The forward PCR-1 primer tile sets are listed in the Supplementary file 1 as Oligos 12–26, and the reverse PCR-1 barcode primer is listed as Oligo 27. The paired PCR-2 reaction was an inverse PCR that generated the remainder of the PKR gene and plasmid backbone, with overlaps to the homology arms of PCR-1; the forward primer for PCR-2 reactions was Oligo 28, and the reverse primers were Oligos 29–43. Thus, Gibson Assembly of these PCR products would generate sets of PKR variants in defined segments of PKR along with random barcodes at the end of the gene (Figure 1—figure supplement 6).

We used custom Python (v3.8.18) scripts to design each variant-introducing primer, utilizing IUPAC degenerate base symbols (e.g. ‘D’ represents a mix of ‘A’, ‘G’, and ‘T’; Cornish-Bowden, 1985; Guido and Drake, 2009). The introduced variant amino acids were all within a single base change from the canonical human PKR coding sequence (Genbank M85294.1:31–1686); we note the PKR sequence encoded on MSp509_PKR-WT differs somewhat from the canonical sequence through synonymous substitutions. Primers were synthesized by Integrated DNA Technologies, then were pooled manually into variant primer tiles sets.

PCR-1 reactions were amplified from the MSp509_PKR-WT plasmid using PfuUltraII polymerase with an annealing temperature of 45 °C. Each reaction generated a pool of PKR gene fragments containing a single nonsynonymous variant paired with a unique barcode sequence. In parallel, PCR-2 reactions amplified vector fragments from MSp509_PKR-WT plasmid using Herculase II polymerase (Agilent Technologies Cat#600677) using cycling conditions for vector targets >10 kb. PCR-1 and PCR-2 amplicons were digested with DpnI (NEB Cat#R0176S) for 2 hr at 37 °C to remove the MSp509_PKR-WT template DNA, followed by gel purification. Each PCR-1 amplicon was paired with its corresponding PCR-2 amplicon for Gibson Assembly in a 1:5 molar ratio.

Two µL of each Gibson Assembly was transformed into 50 µL of 5-alpha competent E. coli and all cells were plated on LB-AMP and incubated overnight at 37 °C. Colonies were counted on each plate and plates were bottlenecked at approximately 30 colonies per selected nonsynonymous variant (i.e. each nonsynonymous variant would be linked to approximately 30 unique barcode sequences). Plates were washed with 15 mL LB-AMP, cell densities were measured as the optical density at 600 nm (OD₆₀₀), and an equal number of cells (approximately 5×10⁹ cells) from each reaction were pooled to form a single PKR variant library. A 200 mL LB-AMP outgrowth was grown to an OD₆₀₀ measurement of approximately 3, followed by a Qiagen MAXI plasmid prep (QIAGEN Cat#12963).

The PKR variant library was sequenced using the PacBio Sequel II instrument to identify the barcodes that were linked to each nonsynonymous variant. Sixteen micrograms of the PKR variant library were digested with restriction enzymes AgeI-HF and NotI-HF to create linear fragments of approximately 2100 bp for sequencing. The digest was incubated for 2 hr at 37 °C then purified using a QiaQuick PCR purification kit (Qiagen Cat#28106). Fragments of 2100 bp were size-selected using a SageELF instrument (Sage Science) before PacBio circular consensus sequencing (CCS) HiFi sequencing on a Sequel II instrument (Pacific Biosciences). From the CCS reads we generated a table of PKR barcodes paired with genetic variants using alignparse v0.2.6 and custom Python scripts (Crawford and Bloom, 2019).

We next cloned the three K3 alleles (K3, K3-H47R, and K3∆58) onto the PKR variant library plasmids. The PKR variant library was digested with NotI-HF and PvuII-HF to generate a 10,270 bp receiver DNA fragment, while the K3 alleles were separately digested with BstEII-HF and SacI-HF (NEB Cat#R3156S) to generate a 1130 bp insert DNA fragment with 20 bp homology arms with homology to the receiver fragment for Gibson Assembly. For each of the reactions, 10 µg of plasmid DNA was digested with 5 µL of each restriction enzyme in a 50 µL reaction to generate a linear fragment, followed by gel purification. The PKR and K3 fragments were combined in three separate Gibson Assembly reactions in a 1:5 molar ratio with 100 ng of the PKR vector fragment in a reaction volume of 20 µL and incubated at 50 °C for 1 hr. A standard ethanol precipitation was performed on each reaction, adding 100 µL of 100% ETOH and incubating overnight at –20 °C before resuspending the pellets in 2 µL of water (Sambrook and Russell, 2006).

We transformed each of the three concentrated reactions into E. cloni 10 G SUPREME electrocompetent cells (Lucigen Cat#60080–2) using a MicroPulser Electroporator (BioRad), with 2 µL of the concentrated reaction combined with 25 µL of competent cells. Following the electroporation and recovery, cells were plated onto two 15 cm LB-AMP plates. A 1:1000 dilution was plated with 100 µL of water on a 10 cm plate to estimate the number of transformed colonies across the two 15 cm plates, which produced an estimate of approximately 2 million colonies per electroporation. Plates were washed with 25 mL LB-AMP, combining the two plates for each of the reactions. Each library was expanded in 200 mL LB-AMP to an OD₆₀₀ measurement of approximately 3, followed by a Qiagen MAXI plasmid prep.

All yeast growth was at 30 °C in CSM-Ura (Sunrise Science Products Cat#1004–010), and liquid cultures were shaken at 200 revolutions per minute. We transformed each of the three paired libraries (PKR +K3, PKR +K3∆58, and PKR +K3 H47R) into yeast in duplicate. The paired plasmid libraries were transformed into the yeast strain BY4742 (MATα ura3∆0 leu2∆0 his3∆1 lys2∆0; strain name MSY2; Brachmann et al., 1998) using a standard large-scale high efficiency lithium acetate transformation protocol (Gietz and Schiestl, 2007) and plated onto 15 cm plates with 2% dextrose, using 1:1000 and 1:10,000 dilutions on 10 cm plates to estimate colony counts, which produced approximately 100,000 colonies. Colonies were washed off plates with 25 mL media with 2% dextrose.

To start the yeast growth assay, six cultures were seeded at low density (OD₆₀₀ measurement of 0.01) in 40 mL media with 2% dextrose and grown overnight for 16 hr. The following morning cultures were moved from 30°C to 4°C to pause growth, then restarted at an OD₆₀₀ of 0.25 in 40 mL media with 2% dextrose 3 hr prior to GAL induction. After 3 hr, once all cultures were in a log growth phase, approximately 1×10⁸ cells were taken from each culture as the starting timepoint sample (designated as ‘0 hours’). All timepoint samples were spun down in a 1.5 mL Eppendorf tube at 5000 rpm for 1 min, after which supernatant was removed and the pellet was frozen at –80 °C. Approximately 2×10⁸ cells from the remaining cultures were pelleted in 50 mL conical tubes at 3000 rpm, supernatant was removed, and cells were resuspended in 80 mL CSM-Ura media with 2% galactose (OD₆₀₀ measurement of 0.125 OD₆₀₀) to induce PKR expression. Cultures were incubated overnight at 30 °C, 200 rpm. Additional samples were harvested at 12, 16, and 20 hr post-PKR induction, with approximately 1×10⁸ cells taken at each timepoint. The culture density was monitored and back diluted to maintain a log growth phase (OD₆₀₀ measurement less than 1). With three K3 allele conditions (K3, K3∆58, and K3-H47R), four timepoints (0, 12, 16, and 20 hr) and two replicates, a total of 24 samples were taken across the yeast growth assay.

To quantify changes in barcode abundance between timepoints in the yeast growth assay, we harvested plasmids from the four timepoints for each K3 allele, then amplified and sequenced the adjacent PKR and K3 barcodes in each plasmid. Plasmids were harvested from the yeast samples using a modified QIAprep spin miniprep protocol (Singh and Weil, 2002). Sampled cell pellets were first thawed at room temperature, followed by the addition of 250 µL QIAprep P1 buffer and 2 µL zymolyase (2.5 units per µL), and incubation at 37 °C for 30 min, followed by adding 250 µL P2 buffer and following the manufacturer instructions for the remainder of the protocol.

To identify and quantify the abundance of each PKR variant paired with each of the three K3 alleles, we performed Illumina sequencing of the PKR barcodes from the plasmids. We used a two-step PCR protocol, the first to amplify the PKR barcode from the plasmids and the second to attach Illumina adapters and Nextera indices for downstream sequencing and sample demultiplexing. For the first PCR reaction, we designed forward and reverse primers as a pool of five primers each, that had 0–4 ‘N’ bases between the Nextera transposase adapter sequence and the priming sequence to stagger the base signal per cycle and maintain sequence diversity across the flow cell (Wu et al., 2015). The forward primers (Oligos 44–48) with a melting temperature of 60 °C were pooled together and used for all PCR-1 reactions, annealing immediately upstream of the PKR barcode locus. Five reverse primers were designed and pooled for amplification from each of the three K3 alleles that annealed within the three distinct K3 barcode sequences (Oligos 49–53 for K3, Oligos 54–58 for K3∆58, and Oligos 59–63 for K3-H47R). One microliter of each primer pool was combined with 50 ng of sample plasmid DNA and 25 µL Kapa Hifi Hotstart ReadyMix (Kapa Biosystems Cat# KK2602), and topped off to a total volume of 50 µL with water. PCR cycling was performed as follows: (1) 95 °C for 3 min, (2) 98 °C for 20 s, (3) 65 °C for 15 s, (4) 72 °C for 1 min, repeat steps 2–4 for a total of 18 cycles, (5) 72 °C for 1 min, (6) 12 °C hold. PCR products were purified using a MinElute PCR purification kit (QIAGEN Cat#28006) using 11 µL water for the final elution, then quantified using a Qubit dsDNA High Sensitivity (HS) kit (Thermo Fisher Scientific Cat#Q32851).

For the second PCR reaction, 10 ng of amplicon DNA from the first PCR reaction was combined with 10 µL of Nextera adapter index primers (Illumina Cat#20027213) and 25 µL Kapa HiFi Hotstart ReadyMix, and topped off to a total volume of 50 µL with water. PCR cycling was performed as follows: (1) 100 °C for 45 s, (2) 100 °C for 15 s, (3) 60 °C for 30 s, (4) 72 °C for 30 s, repeat steps 2–4 for a total of 8 cycles, (5) 72 °C for 1 min, (6) 12 °C hold. PCR products were purified using a MinElute PCR purification kit using 11 µL of water for the final elution, then quantified using a Qubit dsDNA Broad Range (BR) kit (Thermo Fisher Scientific Cat#Q32850). 500 ng of the second PCR reaction amplicons were gel purified on a Size Select II E-Gel (Thermo Fisher Scientific Cat#G661012) for approximately 13 min to extract the approximately 250 bp amplicon band, followed by quantification with a Qubit dsDNA HS kit. Amplicon samples were diluted to 4 nM before being pooled together, followed by manufacture denature and dilution protocols (Illumina Document#15039740 v10) before sequencing on an Illumina NextSeq 2000 instrument.

Next, we extracted PKR barcode sequences from the Illumina reads and mapped the barcodes back to their corresponding select nonsynonymous variants using the table of PKR barcodes paired with genetic variants generated from the PacBio CCS HiFi reads. Paired reads were assembled into contiguous sequences using PEAR v0.9.11 (Zhang et al., 2014), followed by Bartender v1.1 (Zhao et al., 2018) to extract and cluster PKR barcodes using the barcode search pattern ‘CAAGG[25-27]GGTGA’.

We wrote Python v3.8.18 scripts to tally the PKR barcodes and map them back to genetic variants using the table generated from the PacBio CCS HiFi reads. Barcode counts were normalized to the total read count for each of the four timepoints across each of the K3 alleles, followed by a fold change calculation for each PKR barcode across timepoints 0, 12, 16, and 20 hr:FCTP=−log2(NormalizedReadsTPNormalizedReads0)

where FC_TP is the fold change in normalized reads for a PKR barcode from 0 hr to a subsequent timepoint (TP), Normalized Reads_TP is the read count for a given barcode divided by the total number of reads at the given timepoint, and Normalized Reads₀ is the read count for a given barcode divided by the total number of reads at the 0 hr timepoint. Of note, the log₂ of the fold change is inverted such that functional PKR variants that inhibit yeast growth and decreased in abundance were assigned positive fold change value. We then calculated PKR functional scores for each PKR barcode in each of the K3 alleles by calculating the area under the curve using the composite trapezoidal rule. We calculated the PKR functional score for each variant for each K3 allele by averaging the PKR functional score across all representative barcodes for a given variant. As we found a strong correlation between replicates (Pearson correlation coefficient >0.98 for each K3 allele, Figure 1—figure supplement 3), we proceeded by combining all reads from the two replicate experiments for each K3 allele and recalculating the fold changes and PKR functional scores for each barcode as described above.

All molecular graphics and analyses were performed using USCF ChimeraX v1.5 and PyMol v2.5.4. To define PKR residues contacting K3 and eIF2α we used the AlphaFold2 structure prediction tool (ColabFold v1.5.5) in UCSF ChimeraX v1.5 (Meng et al., 2023; Mirdita et al., 2022; Figure 1—figure supplement 7; Supplementary file 6, Supplementary file 7). We aligned these predictions to existing crystal structures (PDB 2A1A and 1LUZ) and found the AlphaFold2 predictions to largely represent the crystal structures RMSD <1 angstrom for both alignments (Figure 1—figure supplement 7; Supplementary file 5; Dar et al., 2005; Dar and Sicheri, 2002). We note the low confidence score (pLDDT <50) of the eIF2α flexible loop containing Ser51, which adopts a compact helical conformation in the predicted model and closely matches the conformation observed in the crystal structure of unbound yeast eIF2α (PDB 1Q46) (Dhaliwal and Hoffman, 2003). As Ser51 of eIF2α would need to travel approximately 17 Å to reach PKR’s active site (Dar et al., 2005), this predicted structure is likely reflective of a pre-phosphorylation complex, and thus would not capture contacts between PKR and eIF2α made during phosphorylation. The corresponding loop is unresolved in the crystal structure of human PKR in complex with eIF2α (PDB 2A1A). Note that we opted not to use the existing structure for defining contact residues, both for consistency with the K3 contact definitions, as there is no PKR-K3 co-crystal, as well as for the potential to capture interactions mediated by residues unresolved in the crystal structure (PDB 2A1A, PKR Asp338-Asn350 and eIF2α Glu49-Lys60).

To identify potential PKR contact sites from the predicted complex structures, we used PyMol v2.5.4 to select all PKR residue branches within 5 Å of K3 or eIF2α using the command: ‘sele contacts, br. /{pdb file name}//A within 5 of /{pdb file name}//B’ with chain ‘A’ being PKR and chain ‘B’ being either K3 or eIF2α. Predicted PKR sites that contact K3 were: 275, 276, 278, 304, 339, 343, 345, 375, 379, 382, 414, 416, 435, 448, 449, 450, 451, 452, 453, 455, 460, 485, 486, 487, 488, 489, 490, 492, 493, and 496. Predicted PKR sites that contact eIF2α were: 274, 275, 276, 279, 335, 337, 338, 339, 340, 341, 342, 379, 382, 451, 452, 453, 483, 486, 487, 488, 489, 490, 491, 492, and 493.

PKR sites in the kinase domain under positive selection across vertebrate species were identified by Rothenburg et al., 2009: 261, 269–272, 307, 314, 322, 360, 368, 375, 378, 379, 382, 385, 389, 394, 405, 428, 448, 449, 462, 471, 483, 486, 488, 491, 493, 500, 502, 504, 505, 514, 520, and 524. Sites conserved across vertebrate PKR homologs were also identified by Rothenburg et al., 2009 which were used for supplementary analysis: 263, 267, 276–279, 281, 283, 296, 298, 308, 309, 312, 315, 317, 319, 320, 323, 327, 362, 364–367, 369, 374, 377, 397, 401, 404, 406, 407, 410–417, 419, 420, 429–433, 437, 444–446, 450, 451, 454, 455, 457–459, 465, 469, 470, 474–477, 480, 490, 511, 519, 523, and 526.