Development of a systematic evolution platform
We began by developing a 96-well plate-based method, wherein 500-µl cultures of evolving M13 bacteriophage (Fig. 1a) are serially diluted with fresh host bacteria twice per hour using an automated liquid handler (Fig. 1b). To enable the pipetting speeds required to approximate continuous flow, we developed a robotic Python interface22 that precisely times the distribution of bacteria, the addition of chemical stimuli, the sampling of populations for real-time monitoring and historical sample preservation (Extended Data Fig. 1). Integrated real-time measurement of luminescence, fluorescence and turbidity enables activity-dependent fitness tracking, which we show is more precise than monitoring turbidity alone15 (Extended Data Fig. 2), Thus, a fluorescent or luminescent reporter can be coupled to either the presence of phage or to the direct activity of the evolving biomolecule itself. We refer to this platform as PRANCE.
Each evolution round is initiated by sterilizing a bacterial culture reservoir (Extended Data Fig. 3) and adding culture to each population (Fig. 1b and Extended Data Fig. 1b). Bacterial cultures can be sourced from an active turbidostat or chemostat, enabling high-volume experiments, or from preprepared bacterial stock stored at 4 °C, enabling experiments that use many bacterial cultures (Fig. 1b). Accessory molecules (for example, chemical mutagens, stimuli, small molecules) are then pinned to each population, which are monitored in real time by an integrated, automated plate reader that measures not only the population density, but also the fluorescence and luminescence of each population at discrete 30-min intervals. Samples are preserved in 96-well format and retained for downstream analyses such as sequencing of accumulated changes, or in vitro and in vivo activity measurements (Fig. 1b). The system also incorporates error handling, failure-mode prevention and wireless experimenter communication, (Extended Data Fig. 4), and is optimized for minimal human intervention (Extended Data Fig. 1c,d). The fast iteration time of PRANCE enables dozens of rounds of evolution per day, comparable to traditional PACE, with the ease and throughput of a plate-based format.
We first demonstrated the real-time activity-monitoring capability by propagating M13 bacteriophage encoding T7 RNA polymerase (RNAP) in place of the pIII phage coat protein using host bacteria expressing pIII and a luminescence reporter (luxAB) under the control of a T7 promoter in 48 independent populations (Fig. 1c). We observed T7 RNAP-dependent luminescence in all samples in less than 4 hours from both 37 and 4 °C culture (Fig. 1d), showing that PRANCE can reproducibly monitor real-time reporters of fitness.
Multiplexing identifies previously inaccessible genotypes
While current directed evolution methods suffice when the primary goal is to engineer a single functional protein, they are limited in their ability to probe the randomness and reproducibility of any given biomolecule evolution and characterize the ensemble of possible outcomes. We wondered if a well-studied evolution5,10,11 could provide new outcomes if sufficiently sampled. First, to measure the stochasticity of evolution, we evolved the T7 RNAP to initiate on the T3 promoter and performed the evolution in 90-plex. In this experiment, host bacteria contain an inducible mutagenesis plasmid24 and an accessory plasmid-containing pIII and luxAB under the control of the T3 promoter (Fig. 2a). With 500-µl populations typically harboring 108 infected cells per ml experiencing high mutagenesis, each population should traverse single-mutation fitness valleys to explore a large fraction of double mutants each day24. We inoculated 96 total populations with or without T7 RNAP-expressing ΔpIII phage (with six no-phage controls) and tracked their progress in real time with luminescence (Fig. 2b). We found that bacteria sourced from 4 °C and mutagenized on-deck perform similarly (Extended Data Fig. 5a) and tracked absorbance depression (Extended Data Fig. 5b). This high-throughput exploration of the evolution of the T7 RNAP, with >5× more parallel populations than the largest previously reported experiment10, allowed us to measure the frequency and reproducibility of the emergence of different genotypes. Both novel and previously reported mutations were observed. In addition, we quantified the elapsed evolution times and found the distribution to be logistically distributed (goodness of fit, CvM stat 0.017, Kolmogorov–Smirnov test 0.046) (Fig. 2c and Extended Data Fig. 5c,d), consistent with only a single mutation (N748D/S or M219R) being required for improved activity (Fig. 2d). The single M219R mutation, which exhibits substantially delayed emergence relative to N748D (chi-square P = 0.0037) (Fig. 2e), has not been previously reported despite the many previous iterations of the T7 RNAP evolution. This may be partly due to N748D/S resulting from a transition mutation (A → G), whereas M219R results from a transversion mutation (T → G), which occurs less frequently24. Thus, systematic high-replicate evolution allows for the extensive profiling of evolutionary reproducibility20 and enables deeper sampling of less accessible genotypes that cannot be readily identified from a single population.
a, Strategy for evolving T7 RNAP to recognize the T3 promoter, in which expression of pIII is driven by the T3 promoter on an accessory plasmid and the evolving T7 RNAP is encoded on the replicating phage genome. b, Real-time luminescence monitoring of 90 simultaneous populations with six no-phage controls. c, Histogram of times required to acquire mutations permitting the T7 RNAP to recognize the T3 promoter, obtained from the inflection point of logistic regressions of each population (Extended Data Fig. 5, Methods and Data analysis). Smoothed fit is calculated with a kernel density estimate (black dashed line) or logistical distribution fit (red). d, Mutations observed from 12 representative populations that exhibited evolution of early (−1σ, t < 22 h), mid (mean, t = 24 h) and late (+1σ, t > 25 h) time points. Three clonal phage from each population are shown, filled-in boxes indicate a mutation at a given location and are colored by ‘fraction’ referring to the mutational frequency within the given time window (t < 22, t = 24, t > 25), where red is 12/12 clones, blue is 1/12 of the clones. Genotypes of subclones are listed in Supplementary Table 2. e, Frequency of mutations arising that exhibited evolution of early (−1σ, t < 22 h), mid (mean, t = 24 h) and late (+1σ, t > 25 h) time points. *** indicates time-dependent chi-square P = 0.0037.
Source data
Miniaturization enables reagent-limited evolution
As traditional PACE uses continuous flow to constantly refresh host bacteria and consumes large quantities of media, it has previously been infeasible to evolve biomolecules in environments that require small molecules that are difficult to synthesize or are new25. PRANCE reduces each bioreactor volume by 100-fold, thus making small molecule-dependent environments more feasible and controllable. To demonstrate these capabilities, we modified an established evolution of the pyrrolysine aminoacyl-synthetase (PylRS) to incorporate noncanonical amino acids (ncAAs)26, using substantially lower quantities of ncAAs than previously reported. To enable multiplexing of diverse transfer RNA (tRNA)–PylRS pairs, we encoded a PylRS variant and a UAG-containing tRNAPyl within the M13 phage genome and inserted a UAG amber stop codon within the pIII phage coat protein along with a luciferase reporter expressed from host bacteria (Fig. 3a). Thus, phage proliferation and luminescence are both directly coupled to suppression of the UAG amber codon via ncAA incorporation (Fig. 3b).
a, Strategy for evolving AARSs and tRNAs to incorporate noncanonical amino acids. TAG amber codons are inserted into the pIII protein, and the evolving tRNAPyl and chPylRS are encoded in the evolving phage genome. b, Phage propagation and luminescence are contingent on the successful incorporation of ncAAs into pIII. c, Efficiency of unevolved versus evolved chPylRS variants (IP, IPYE mutations) at incorporating Boc-lysine into an inducible TAG-luxAB reporter, normalized to no-ncAA and no-IPTG controls. Data are presented as mean values ± s.e.m. for n = 8 biologically independent samples. d, Quantifying the selection stringency of incorporating one, two or three ncAAs into pIII, in either the presence or absence of Boc-lysine, using the evolved variant chPylRS-IPYE. Data are presented as mean values ± s.e.m. for n = 4 biologically independent samples. e, Real-time absorbance depression and luminescence monitoring beginning from either the unevolved state (chPylRS, blue) or an intermediate evolved state (chPylRS-IP, red). f, Genotypes of the evolved variants. Phage persisted in all of the chPylRS-IP populations, and clonal phage acquired novel mutations (P5L or E302A). Only half of the chPylRS populations resulted in persistent phage propagation at 36 h; each acquired a distinct mutation at the same N-terminal proline residue (P5L or P5T) within the conserved essential N-terminal domain of PylRS44,45. g, Efficiency of evolved variant mutations in both chPylRS and chPylRS-IP at incorporating Boc-lysine into an inducible TAG-luxAB reporter, compared to no-ncAA and no-IPTG controls. Data are presented as mean values ± s.e.m. for n = 8 biologically independent samples.
Source data
We used three pyrrolysine synthetases—chPylRS, an evolution intermediate (chPylRS-IP)26 and an evolved variant (chPylRS-IPYE)26—and quantified their ability to incorporate Boc-lysine as measured by ncAA-dependent kinetic luminescence activity (Fig. 3c) and amber codon-dependent phage enrichment (Fig. 3d). We then used PRANCE to evolve the PylRSs to incorporate Boc-lysine by inoculating eight populations with phage encoding either chPylRS and chPylRS-IP in quadruplicate. Aminoacyl-synthetase (AARS) evolution is prone to the emergence of ‘cheaters’, that is promiscuous charging of canonical amino acids27. To monitor the emergence of nonspecific AARSs, we included eight populations with phage encoding each variant but in the absence of ncAAs; phage propagation under these conditions would indicate the evolution of nonspecific charging of canonical amino acids. Together, we monitored luminescence and absorbance across a total of 24 populations over 36 h of evolution. We observed propagation of both chPylRS- and chPylRS-IP-encoding phage in the presence of Boc-lysine (Fig. 3e), and identified novel genotypes with previously unidentified mutations (Fig. 3f,g). The lack of luminescence in the absence of ncAA indicates that cheater AARSs are unlikely to emerge under the evolution conditions used (Fig. 3e). Thus, the inclusion of control populations—typically neglected in directed evolution experiments due to throughput limitations—enabled the extraction of additional information previously unobtainable. This capability can be used to determine whether or not negative selection against promiscuous activity26 is necessary. Additionally, the automated addition of Boc-lysine to 12 evolving populations over 36 h of PRANCE consumed less than 100 mg of total compound, nearly ten times less than what would have been required for a single population within a bioreactor. Given this substantial reduction in reagents, PRANCE enables multiplexed and well-controlled evolution experiments with fine control over the chemical environment using molecules that are too expensive (for example, 4-azido-Phe, $2,500 per gram28) or rare (for example, pyrrolysine29) to be used with traditional continuous-flow bioreactors.
Simultaneous evolution of dozens of biomolecules
Previously, we used PACE to evolve tRNAs30 capable of decoding quadruplet codons31,32 toward the goal of engineering a four-base codon translation system33,34. To evolve new quadruplet tRNAs (qtRNAs), we inserted a quadruplet codon (AGGG) into pIII and generated a variety of qtRNA-encoding, pIII-deficient phage (Fig. 4a). In the absence of a functional qtRNA, the quadruplet codon generates a frameshift, truncating pIII and precluding phage propagation (Fig. 4b). The success of qtRNA evolution can depend on which tRNA paralog is used to initiate evolution, highlighting the importance of studying a variety of starting genotypes. Here, we used PRANCE to simultaneously identify many functional qtRNAs by subjecting a full set of 20 different paralogs to evolution within a single experiment. We first replicated the evolution of six TAGA-decoding qtRNAs, and observed similar genotypes as previously described30 (Extended Data Fig. 6). Next, we initiated PRANCE by seeding 48 populations in an optimized configuration (Extended Data Fig. 7) with phage encoding 20 different qtRNA paralogs corresponding to every canonical amino acid containing a library of randomized anticodons (NNNN) (20 populations); phage encoding eight different qtRNA paralogs (Ala, Glu, Gly, His, Arg, Ser, Thr and Trp) each with directed AGGG frameshift anticodons (24 populations) or no-phage controls (four populations).
a, Strategy for evolving qtRNA to recognize quadruplet codons. AGGG quadruplet codons are inserted into the pIII protein and luxAB, and the evolving qtRNA are encoded in the evolving phage genome. AP, accessory plasmid. b, Phage propagation and luminescence are contingent on the successful decoding of the quadruplet codons in the pIII and luxAB proteins. Failure to decode a quadruplet codon results in premature termination and truncated protein. c, Efficiency of evolved versus unevolved qtRNA at incorporating amino acids compared to a triplet codon. d, Initial and evolved qtRNA genotypes. Data are presented as mean values ± s.e.m. for n = 3–8 biologically independent samples. e, Strategy for evolving qtRNAs with increasing stringency of selection (red/lenient, T7 RNAP; moderate/blue, pIII-1x; stringent/green, pIII-2x). f, The transfer function that determines the efficiency of phage propagation as a function of biomolecule activity for each AP, measured using phage-bearing qtRNAs at different starting activities (Phe, His, Ser, Arg). Starting activity is quantified as percentage of WT, or the luminescence generated by coexpressing the qtRNA and luxAB-357-TAGA, relative to an all-triplet luxAB. g, Evolution of four qtRNAs on APs with varying stringencies (successful evolution indicated by green checkmarks). h, In a feedback experiment, three bacterial strains with increasing stringency are added to phage populations and monitored in real time. The bacteria source for each well is adjusted in response to real-time luminescence measurements to automatically increase stringency of the environment. i, Real-time luminescence measurements of evolving qtRNAs with feedback-controlled selection stringency intervals.
Source data
We then tracked luminescence of all 48 populations over 36 h and found that phage encoding Gly, His, Ser, Arg, Thr and Trp qtRNA paralogs successfully decoded quadruplet codons (Extended Data Fig. 6e). Indeed, when subcloned, several of the isolated qtRNAs exhibited improved activity (Fig. 4c,d), although further characterization would be required to determine the amino acid identity of the evolved qtRNAs34. These results are consistent with the observation that only some tRNAs are capable of improvements to this biomolecular activity, highlighting the importance of genotype diversification in the success of evolution. Notably, a single PRANCE experiment evolved multiple AGGG-decoding qtRNAs, which would have previously required dozens of individual PACE experiments.
Feedback evolution of activity-diverse biomolecules
Although we successfully identified AGGG-decoding qtRNAs with improved activity, we also observed a high failure rate. Many of the qtRNAs with low initial activity (Ala, Cys, Asp, Phe and so on) never evolved, but rather experienced an experimental failure mode referred to as ‘washout’ in which the effective population size decreases to zero (Extended Data Fig. 6e). Additionally, we observed that qtRNAs with high initial activity (Arg, Trp) maintained population size and triggered luminescence but did not acquire mutations. These results indicate that selection was too stringent in some cases and too lenient in others—both common directed evolution failure modes. We hypothesized that the ability to dynamically tune selection stringency in accordance with population fitness would improve the likelihood of successfully evolving biomolecules from diverse starting points, by both reducing the possibility of phage washout and maintaining selection pressure on high-activity variants. To improve likelihood of evolution success, we developed a feedback control system35,36 that adjusts the stringency of selection by modifying the host bacterial strain in response to a real-time analysis of molecular activity-dependent luminescence. As a model system, we selected four qtRNA paralogs (Phe, His, Ser and Arg) that decode the TAGA quadruplet codon, are known to have improved variants and differ greatly in initial activity. We sought to use feedback control to evolve all four qtRNAs in a single experiment.
First, we characterized three bacterial APs that confer different levels of selection pressure. The most ‘lenient’ of these APs encodes T7 RNAP containing two quadruplet codons, with the T7 promoter driving production of pIII and luxAB (Fig. 4e). We also characterized more stringent APs containing either one (moderate) or two (stringent) quadruplet codons directly in pIII (Fig. 4e) and found that these APs adequately cover phage enrichment space (Fig. 4f). We next evolved these qtRNAs on each of the three individual bacterial sources separately, under static selection. The variant with the highest initial activity, qtRNAArgTAGA, only evolves under high selection pressure. Conversely, under lenient pressure all phage propagate, but only the qtRNAs with the lowest initial activity experience selection and acquire mutations (Fig. 4g). None of the three levels of stringencies could evolve all four qtRNAs. To customize selection pressure, we implemented automated feedback control in which the bacterial source of each population is adjusted in response to real-time measurements of fitness as measured by luminescence (Fig. 4h and Methods). This strategy successfully propagated phage populations encoding all four qtRNAs to the end of the 36-hour experiment (Fig. 4i). Additionally, by measuring clonal variant activity from each of the eight feedback-controlled populations using a luciferase reporter, we found that all eight populations had evolved qtRNA variants with improved translation efficiency (Fig. 5a). Thus, feedback control avoided phage washout in all cases while simultaneously exposing high-activity qtRNAs to more challenging evolution environments, in a short time window, without researcher intervention. These results demonstrate that feedback control is more robust and less failure prone, enabling the evolution of biomolecules with diverse activities.
a, Relative activity of the initial and evolved variants as measured by a kinetic luminescence assay. Data are presented as mean values ± s.e.m. for n = 3–8 biologically independent samples. b–e, Muller plots as abundance adjusted for population size for Arg-qtRNA (b), Phe-qtRNA (c), Ser-qtRNA (d) and His-qtRNA (e). The dashed line shows the introduction of moderate selection and the dotted line shows the introduction of stringent selection. f, Predicted phylogenetic relationship of the variants arising from evolution of each qtRNA, and their respective maximum population abundance between replicates. g, Location of mutations within the standard qtRNA secondary structure. The colors of variants arising in each evolution are consistent with the legends in Fig. 6b–e.
Source data
Evolution outcomes are determined by temporal dynamics
It is well established that selection stringency can affect the trajectory of evolution10,19, but the importance of the timing of those changes has remained largely unexplored. In nature, changes in the physical environment are complex, and can be random or even exhibit mutual dependence with population fitness (for example, in predator–prey dynamics37). Thus, we wondered how static versus dynamic selective environments would affect the trajectory of single-biomolecule evolution within the laboratory. Due to the small size of qtRNAs, we used next-generation sequencing to characterize the evolutionary history of 32 populations as they were subjected to different temporal perturbations to their selective environment. We tracked the genotypic abundance relative to population size of four qtRNA paralogs over 36 hours, under four selection schedules in duplicate as they underwent evolution under static (lenient or stringent), dynamic yet unresponsive (discrete) or feedback-controlled (responsive) stringency modulation.
We found that the selective environment affects whether and how quickly evolved variants reach fixation in a population. For example, the variant qtRNAArgTAGAU43 can only be evolved using stringent selection because the tRNA genotype initiating that evolution has high initial fitness (Fig. 5a,b). Accordingly, all qtRNAArgTAGA evolution experiments arrive at a convergent solution, but the speed of evolution depends on how quickly the stringent selective environment is introduced (Fig. 5b). Further, qtRNAPheTAGA, qtRNAHisTAGA, and qtRNASerTAGA are each vulnerable to washout at high stringency due to lower overall fitness (Fig. 5c–e); thus, evolution only occurs for these qtRNAs in environments that are initially lenient. During qtRNAPheTAGA evolution, an accessible and convergent single-point mutant (32 A) arises that is highly fit in lenient and moderate selective environments, resulting in purification and population size growth in those environments (Fig. 5d). The qtRNAHisTAGA evolution is more complex, containing several variants with elevated fitness composed of mutations to base 32 together with modifications in the variable loop (Fig. 5e,g). Finally, the synergistic epistasis between mutations in qtRNASerTAGA (Fig. 5a) makes purification of the highly improved qtRNASerTAGAA32-C38 mutant31 less robust: only one responsive environment completely purified this variant (Fig. 5c). Together, these data show how the unique fitness landscape of each biomolecule determines the dynamics of its evolution in different selective environments.
We also observed that the dynamics of environmental changes can affect the phylogenetics of evolution. Unlike Arg and Phe-qtRNA evolution, which each appear to deterministically converge on particular high-activity variants irrespective of changes in stringency timing (Fig. 5b,d), we found that the genotypes resulting from qtRNAHisTAGA evolution are particularly sensitive to historical changes in the environment. The discrete selection schedule resulted in wide genotypic variety, with seven unique genotypes each reaching >10% of phage population share at some point during evolution (Fig. 5f). In this schedule, the arbitrary introduction of moderate stringency (t = 12 h) reproducibly enriches intermediately active variants (C32 or G32) and their phylogenetic descendants with variable loop mutations (G32-Δ48, C32-A48, C32-Δ48, C32-Δ47) (Fig. 5g), before converging on a globally optimal variant. Conversely, we see that during responsive evolution, where moderate stringency is delayed until the population is sufficiently fit (t = 18 h), a single active point mutant (Δ45) emerges as the predominant variant without widely exploring other genotypes at high population abundance (Fig. 5e,f). These data show that seemingly small perturbations to the historical selective environment, whether arbitrary or in response to a changing ecosystem, can drive purification of distinct genetic variants that are either moderately or highly fit38. Collectively, these results demonstrate that although single-biomolecule evolution may appear deterministic on simple fitness landscapes with a sharp peak, more complex landscapes may produce outcomes contingent on seemingly inconsequential events21.
Long-running evolution with PRANCE
The longevity of most PACE experiments (>100 hours) requires the platform to be capable of performing long-running, multi-trajectory evolution experiments. Due to the large quantities of consumables used by liquid-handling robots, the need for frequent researcher intervention (for tip-replenishing) and the ongoing tip shortage resulting from the COVID-19 pandemic39, we developed an optimized method capable of sterilizing and reusing tips on the robot deck (Supplemental Video 1). This optimized method uses approximately five boxes of tips per day, and can be run for over a week at a time with user intervention only once every 24 hours. During method optimization, we observed that different robotic configurations introduce varying amounts of cross-contamination when propagating highly active phage (Extended Data Fig. 8a,b). To demonstrate the capabilities of this method, we first validated that tip reuse and sterilization introduced no quantifiable cross-contamination within 12 hours (Extended Data Fig. 8c), indicating that tips could be replenished once or twice per day.
We then used this technique to enable a 10-day evolution in which we evolved T7 RNAP to bind eight new promoters (Fig. 6a,b). During this experiment, we tested three techniques to maintain large population sizes during long-running experiments: allowing the evolution to proceed without intervention (no pulse); spiking the population with bacteria expressing pIII under the phage shock promoter (psp) that enable activity-independent phage propagation periodically every 12 h (12 h pulse) or spiking only before transitions to new evolution stringency (pretransition pulse). We evolved 32 populations for 240 hours (10 days) in a single, uninterrupted experiment (Fig. 6c). During this time, no cross-contamination in the eight no-phage control wells was detected. We found that the phage titer maintenance schemes affected the genotypes that evolved (Fig. 6d). To quantify activity, individual variants containing all of the dominant mutations from each replicate (Fig. 6d and Supplementary Table 3) were subcloned into plasmid reporter constructs in which LuxAB was driven by the TP6, −3 variant or −5 variant promoter. The activities of 24 total subclones were then quantified by luminescence and compared to wild-type (WT) T7 RNAP on each respective promoter (Fig. 6e and Extended Data Fig. 9). Most variants obtained in the T7 → T3 → −3/−5 trajectories were found to exhibit between 10 and 20-fold higher activities than WT T7 RNAP on the same promoter. In addition, we found that the stringency conditions interacted with the evolution goals; for example, the reduced population size of ‘No pulse’ in the SP6 trajectory was the only condition that converged on mutations to E222, a residue associated with nonspecific promoter binding11 (Fig. 6e). The highest activity variant obtained from −3 variant evolution (prepulse, population no. 2, Fig. 6e) was also the only population to reach saturation with a novel E218A mutation even though many populations obtained the M219R/K solutions described above (Fig. 6f). Thus, PRANCE enables the seamless exploration of complex, multi-mutational pathways that evolve over the course of many days and require several intermediate evolution goals.
a, Thirty-two populations of phage encoding T7 RNAP were evolved to bind new promoters. Evolution proceeded first along two different paths, being challenged to bind either SP6 or T3-derived promoters. All populations were then evolved to bind the TP6 promoter. The 16 populations that traversed the T3 path were then split in half and challenged to bind novel promoters with mutations at highly conserved −3 or −5 locations. b, Genotypes of the promoters used in this evolution. Changes from the WT T7 promoter are highlighted. c, Real-time monitoring of the 48 populations undergoing three different stringency management schemes in which psp-pIII bacteria are periodically spiked into populations for 3-h intervals (dark gray bars) to increase population size. d, Genotypes of subclones obtained from each population (replicate populations labeled 1–4) from each evolution trajectory with each of the three stringency management schemes. Dominant (>50% of population) variants are highlighted and colored by their AA mutation. Nondominant (that is background mutations) are shown in light gray. The x axis is annotated by dominant mutations that appear within a given trajectory. e, Normalized luciferase activity of individual subclones from populations (1–4) from each trajectory, compared to WT T7 RNAP (blue). Luciferase reporter vectors are driven by the TP6 promoter, −3 variant promoter and −5 variant promoters. Data are presented as mean values ± s.e.m. for n = 3 biologically independent samples. Genotypes of subclones are listed in Supplementary Table 3. f, E218, M219 and E222 in the WT T7 RNAP structure (PDB 1CEZ, ref. 46), near the promoter specificity loop.
Source data
