key: cord-0331500-yn1qxuvo
authors: Porter, Lauren L.; Kim, Allen K.; Looger, Loren L.; Majumdar, Anaya; Starich, Mary
title: Pervasive fold switching in a ubiquitous protein superfamily
date: 2021-06-16
journal: bioRxiv
DOI: 10.1101/2021.06.10.447921
sha: 6a61a8ba1138e45c15c10388683064b391b4a8c6
doc_id: 331500
cord_uid: yn1qxuvo

Fold-switching proteins challenge the one-sequence-one-structure paradigm by adopting multiple stable folds. Nevertheless, it is uncertain whether fold switchers are naturally pervasive or rare exceptions to the well-established rule. To address this question, we developed a predictive method and applied it to the NusG superfamily of >15,000 transcription factors. We estimate that a substantial population (25%) of the proteins in this family switch folds. Circular dichroism and nuclear magnetic resonance spectroscopies of 10 sequence-diverse variants confirmed our predictions. Subsequently, we leveraged family-wide predictions to determine both conserved contacts and taxonomic distributions of fold-switching proteins. Our results indicate that fold switching is pervasive in the NusG superfamily and that the one-sequence-one-structure protein folding paradigm significantly biases protein structure prediction strategies.

Main Text: Fold-switching proteins remodel their secondary and tertiary structures and change their functions in response to cellular stimuli (1) . Their large, sometimes reversible, conformational changes challenge the long-held paradigm that globular proteins have a single fold specified by their amino acid sequences (2) . Fold switchers regulate diverse biological processes (3) and are associated with human diseases such as cancer (4) , malaria (5) , and COVID-19 (6) .

Whereas computational approaches such as coevolutionary analysis (7) and deep learning (8) , have greatly improved rapid prediction of secondary and tertiary structure for single-fold proteins (9) , similar methods to classify fold switchers have lagged. This comparative lack of progress arises primarily from the small number of experimentally observed fold switchers (<100), hampering the discovery of generalizable characteristics that distinguish fold switchers from single folders. As a result, essentially all naturally occurring fold switchers have been discovered by chance (10) , leaving their natural abundance an open question.

To assess the natural abundance, evolutionary conservation, and taxonomic diversity of fold-switching proteins, we sought to predict them from their sequences. Previous work has shown that discrepancies between homology-based secondary structure predictions often indicate protein fold switching (11) (12) (13) . We leveraged these discrepancies to discover disparate fold-switching proteins in the NusG protein superfamily, the only family of transcriptional regulators known to be conserved from bacteria to humans (14) . Housekeeping NusGs (hereafter called NusGs) exist in nearly every known bacterial genome and associate with transcribing RNA polymerase (RNAP) at essentially every operon, where they promote transcription elongation. By contrast, specialized NusGs (NusG SP s), such as UpxY, LoaP, and RfaH, promote transcription elongation at specific operons only (15) . Atomic-level structures of RfaH and NusG have been determined (Fig. 1A) . They share a two-domain architecture with an N-terminal NGN domain that binds RNAP, and a C-terminal b-roll domain. By contrast, the C-terminal domain (CTD) of Escherichia coli RfaH switches between two disparate folds: an a-helical hairpin that inhibits RNAP binding except at operon polarity suppressor (ops) DNA sites and a b-roll that binds the S10 ribosomal subunit, fostering efficient translation (16) . This reversible change in structure and function is triggered by binding to both ops DNA and RNAP (17) .

We observed that JPred4 (18) secondary structure predictions discriminate between the sequences of RfaHs and NusGs with experimentally determined atomic-level structures (Figs. 1A&B). These sequence-based calculations consistently indicate that NusG CTD sequences fold into b-strands connected by coils, whereas the E. coli RfaH CTD assumes a mixture of a-helix, bstrand, and coil. Thus, our results suggest that JPred4 can distinguish between the sequences of single-folding NusGs and the fold-switching NusG SP , RfaH.

To test the generality of our secondary-structure-based approach, we collected 15,516 nonredundant NusG/NusG SP sequences from an iterative BLAST (19) search (Methods) and tested our predictive method on each hit from the search. In total, 25% of proteins in the NusG superfamily were predicted to switch folds (Figures 1C and S1 , Data S1), a considerable subpopulation with over 3500 sequences.

To determine the false-negative and false-positive rates of our predictions, we exploited known operon structures of NusG and several specialized orthologs (15) as an orthogonal method to annotate sequences as NusGs or NusG SP s. We mapped the sequences used for prediction to sequenced bacterial genomes (Ensembl; Methods) and analyzed each sequence's local genomic environment for signatures of co-regulated genes. Of our 15,516 total sequences, 5,435 mapped to Ensembl contexts consistent with housekeeping NusG function. Only 30 of these were predicted to switch folds (Figure 1C) , suggesting a false-positive rate of 0.6% for fold-switch predictions. Performing a similar calculation in previously identified RfaHs (15) , we found that of the 1,078 in Data S1, 31 were predicted not to switch folds ( Figure 1C) . These results suggest that fold switching is widely conserved among RfaHs, which, if correct, indicates a false positive rate of 3% (31/1078). Of the remaining sequences with high-confidence predictions (Methods), 30% were predicted to switch folds ( Figure 1C) Experimentally determined folds and secondary structures of single folder NusG and the autoinhibited/active NusG SP , RfaH (ahelical hairpin/b-roll folds, respectively). Dotted line represents the NTD-CTD linker missing in the RfaH crystal structure. NusG/RfaH CTDs are colored teal/red; NTDs are gray. (B). JPred4 secondary structure predictions discriminate between RfaH and NusGs with experimentally determined structures (teal and red, respectively). Gray box highlights secondary structure prediction discrepancies. Residue numbers are at each end of the secondary structure diagrams. (C). Of the sequences in the NusG family, 25% were predicted to switch folds. As expected, nearly all (99.5%) genomically verified housekeeping NusG sequences within our dataset were predicted to be single folders. Furthermore, 97% of RfaH-like sequences identified previously (15) and 30% of the remaining sequences with high-confidence predictions (Other) were predicted to switch folds.

A representative group of variants with dissimilar sequences was then selected for experimental validation. First, all NusG-superfamily sequences were clustered and plotted on a force-directed graph, hereafter called NusG sequence space (Figure 2A , Data S1, Figure S2 ). The map of this space revealed that some putative fold-switching/single-folding nodes cluster together within sequence space (upper/lower groups of interconnected nodes), while other regions had mixed predictions (left/right groups of interconnected nodes). Candidates selected for experimental validation came from distinct nodes, had diverse genomic annotations, and originated from different bacterial phyla (Table S1, Figure S3 ).

Circular dichroism (CD) spectra of 10 full-length variants were collected. We expected the spectra of fold switchers to have more helical content than single folders because their CTDs have completely different structures (RfaH: all a-helix, NusG: all b-sheet), while the secondary structure compositions of their single-fold NTDs are expected to be essentially identical. E. coli RfaH (variant #3) and E. coli NusG (variant #9) were initially compared because their atomiclevel structures have been determined previously (20, 21) . As expected, their CD spectra were quite different ( Figure S4 ): E. coli RfaH had a substantially higher a-helix:b-strand ratio (1.1, Figure 2B , variant #3) than E. coli NusG (0.54, Figure 2B , variant #9) -consistent with solved structures.

All 10 of our predictions were consistent with their corresponding CD spectra ( Figure 2B , Table S1 ). Specifically, in addition to E. coli RfaH, five other predicted fold switchers had RfaHlike CD spectra: two RfaHs (variants #2, #6), a LoaP (variant #1), an annotated NusG (variant #4), and an annotated "NGN domain-containing protein" (variant #5). Furthermore, the remaining three predicted single folders had NusG-like CD spectra: two annotated NusGs (variants #8, #10) and one UpbY/UpxY (variant #7).

We then assessed whether putative fold-switching CTDs could assume b-sheet folds in addition to the a-helical conformations suggested by CD. Previous work (16) has shown that the full-length RfaH CTD folds into an a-helical hairpin while its isolated CTD folds into a stable broll. Thus, we determined the CD spectra of five isolated CTDs: three from putative fold switchers and two from putative single folders. All of them had low helical content and high b-sheet content ( Figure S5 ), strongly suggesting that the CTDs of all three predicted fold switchers can assume both a-helical hairpin to b-roll topologies.

Two variants were then characterized at higher resolution using nuclear magnetic resonance (NMR) spectroscopy. Previous work (16) has shown that the isolated CTD of RfaH has a significantly different 1 H-15 N HSQC than full-length RfaH, whose CTD folds into an a-helical hairpin. Thus, we conducted similar experiments on one single-fold variant (variant #8) and one putative fold switcher (variant #5). We found that the backbone amide resonances of the fulllength and CTD forms of variant #8 were nearly superimposable, whereas the full-length and CTD forms of variant #5 shared only 7/58 common backbone amide peaks ( Figure 2C ). This result demonstrates that, as predicted, variant #8 does not switch folds. It is also consistent with the prediction that variant #5 switches folds because large backbone amide shifts indicate either refolding or a large change in protein interface. Both occur in fold-switching RfaH but not in single-folding NusG. Subsequently, we used assigned backbone amide resonances to characterize the secondary structures of both CTD variants at higher resolution ( Figure S6 , Table S2 ). Both were consistent with the b-roll fold, again indicating that the CTD of variant #5 may switch folds.

These results, though a very small proportion of the sequences in this superfamily, support the accuracy of our predictions and demonstrate that:

(1) Some but not all NusG SP s besides RfaH probably switch folds. Specifically, full-length LoaP (variant #1), which regulates the expression of antibiotic gene clusters (22) , had an RfaH-like CD spectrum, whereas full-length UpbY from B. fragilis (variant #7) appears to assume a NusG-like fold. (2) Some annotated NusGs have RfaH-like CD spectra (variant #4), the result of incorrect annotation. Indeed, the genomic environment of variant #4 (Methods) suggests that is a UpxY, not a NusG.

(3) The fold-switching mechanism is conserved among annotated RfaHs with low sequence identity (≤32%, variants #2, #3, and #6), a possibility proposed previously (23), though without experimental validation. Also, "NGN domain-containing protein" variant #5 is genomically inconsistent with being a NusG and is likely another RfaH.

To benchmark the performance of our secondary-structure-based method, we assessed whether coevolutionary and template-based methods could also distinguish between fold switchers and single folders in the NusG superfamily. Specifically, we tested Robetta (24) , EVCouplings (25) , and Phyre2 (26) on variants #1-6 ( Figure 3A ). All methods predicted only b-strand conformations ( Figure S7 ). These predictions included E. coli RfaH (variant #3), which assumes an a-helical hairpin in its experimentally determined structure (20) . The multiple sequence alignments used to generate these predictions contained mixtures of RfaH and NusG sequences, and the resulting residue-residue couplings from Robetta and EVCouplings corresponded with the NusG-like b-roll fold ( Figure 3A) . These results suggest that b-roll couplings present in both single-folding and fold-switching sequences might overwhelm any a-helical couplings unique to fold-switching sequences.

Residue couplings for E. coli RfaH predicted by EVCouplings (gray circles) and Robetta (yellow triangles) are biased toward the b-roll fold (PDB ID: 2LCL, red circles); no couplings unique to the experimentally determined a-helical hairpin (PDB ID: 2OUG, chain A, teal circles) were identified. Both sets of predictions were calculated from alignments with mixtures of single-folding and fold-switching sequences. Couplings that do not correspond to experimentally observed contacts are lighter. (B) Sequences with JPred4 predictions similar to E. coli RfaH yielded residue-residue couplings from both the b-roll and the a-helical hairpin folds (gray stars). Italicized letters correspond to individual couplings in the two folds. (C) Categories of residue-residue contacts from both folds using the alphabetically labeled contacts in (B), listed below each category.

We then performed coevolutionary analysis on a set of sequences that our method predicted to switch folds. Specifically, we clustered putative fold switchers by their JPred4 predictions and did coevolutionary analysis on the cluster containing the E. coli RfaH sequence using GREMLIN (27) . The residue-residue couplings generated from these sequences differed substantially from the NusG-like couplings generated before ( Figures 3A&B) . Furthermore, GREMLIN couplings calculated from the alignments used by EVCouplings and Robetta corresponded with the b-roll fold only (Figure S8) , demonstrating that the JPred-filtered sequence alignment-not the GREMLIN algorithm-was responsible for the discovery of alternative contacts.

The coevolutionary analysis of putative fold switchers suggests that their CTDs encode contacts unique to both the a-helical and b-roll folds -only one contact was shared between both (i/q, Figures 3B&C) . Several categories of contacts were identified. For the b-roll fold, eight hydrophobic and four Coulombic contacts were observed. Using residue pairs from all JPred4filtered sequences, we found that 97%/96% of residue pairs making strand contacts q and v were hydrophobic, and 76%/53% of contacts y and s could potentially form Coulombic interactions. For the a-helical fold, six intrahelical hydrophobic contacts and one set each of interhelical contacts, strand-helix contacts, and helix-capping contacts were observed ( Figure 3C) . Overall, 96% of interhelical contacts were hydrophobic, 94% of helix-capping residues could potentially form an i-4ài or iài backbone-to-sidechain hydrogen bond, 85% of residues in the helix-loop interaction had a charged residue in one position, but not both, and 80% of residues in intrahelical contact a were both hydrophobic. The remaining contacts gave more mixed results, perhaps due to hydrophobic residues contacting the hydrophobic portion of their hydrophilic partners. Previous work has shown that interdomain interactions also contribute significantly to RfaH fold switching (16) . Unfortunately, these interactions could not be identified by coevolutionary analysis ( Figure  S9 ), a likely result of the limited number of JPred-filtered sequences available.

Our results suggest that the sequences of fold-switching CTDs poise them to assume two disparate folds. Thus, it might be reasonable to expect these sequences to be relatively homogeneous, especially since variants of another fold switcher, human XCL1, lose their ability to switch folds below a relatively high identity threshold (60%, (28) ). The opposite is true. Sequences of putative fold-switching CTDs are significantly more heterogeneous (20.4% mean/19.4% median sequence identity) than sequences of predicted single folders (40.5% mean/42.5% median sequence identity, Figure 4A ). Accordingly, among the sequences tested experimentally, similar mean/median sequence identities were observed: 21.0%/21.1% (fold switchers), 43.2%/41.2% (single folders, Figure 4B ). Additionally, fold-switching CTDs were predicted in most bacterial phyla, and many were predicted in archaea and eukaryotes as well ( Figure 4C, Data S2) . These results suggest that many highly diverse CTD sequences can switch folds between an a-helical hairpin and a b-roll in organisms from all kingdoms of life.

Why might the sequence diversity of foldswitching CTDs exceed those of single folders? Functional diversity is one likely explanation (29) . Previous work has shown that NusG SP s drive the expression of diverse molecules from antibiotics to toxins (15) . Our method predicts that many of these switch folds. Furthermore, since helical contacts are conserved among at least some fold-switching CTDs, it may be possible that CTD sequence variation is less constrained in other function-specific positions. The fold-switching mechanism of RfaH allows it to both regulate transcription and expedite translation, presumably quickening the activation of downstream genes. NusG SP s are likely under strong selective pressure to conserve this mechanism when the regulated products control life-or-death events, such as the appearance of rival microbes or desiccation. Supporting this possibility, RfaH, LoaP, and UpxY usually drive operons controlling rapid response to changing environmental conditions such as macrolide antibiotic production (22) , antibiotic-resistance gene expression (15) , virulence activation (30) , and biofilm formation (31).

Our method was sensitive enough to predict fold-switching proteins, setting it apart from other state-of-the-art methods. These other methods assume that all homologous sequences adopt the same fold, as evidenced by their use of sequence alignments that contained both fold-switching Figure  2 . Numbers in each box represent the % identity of the two variants compared. Darker boxes represent higher identity levels. (C) Fold-switching CTDs are predicted in many bacterial phyla and other kingdoms of life. Numbers next to taxa represent #predicted fold switchers/#total sequences. Gray branches represent unidentified common ancestors, since the evolution of fold-switching NusGs is unknown. Dotted lines represent lower-confidence predictions since fold switching has not been confirmed experimentally in archaea and eukaryota. Fold-switching/single-folding predictions are represented by teal/red colorings; predictions in branches with fewer than 10 sequences are gray. and single-folding sequences. These mixed sequence alignments biased their predictions. While those predictions are partially true since both fold-switching and single-folding CTDs can fold into b-rolls, they miss the alternative helical hairpin conformation and its regulatory function (14) . Computational approaches that account for conformational variability and dynamics, a weakness in even the best predictors of protein structure (9) , could lead to improved predictions. This need is especially acute in light of recent work showing how protein structure is influenced by the cellular environment (32) , and it could inform better design of fold switchers, a field that has seen limited success (33-35).

Our results indicate that fold switching is a pervasive, evolutionarily conserved mechanism. Specifically, we predicted that 25% of the sequences within a ubiquitous protein family switch folds and found that residue-residue contacts unique to each fold-switching conformation are conserved through evolution. This sequence-diverse dual-fold conservation challenges the one-sequence-one-structure protein folding paradigm and indicates that foundational principles of protein structure prediction may need to be revisited.

The success of our method in the NusG superfamily suggests that it may have enough predictive power to identify fold switching in protein families believed to contain only single folders. Such predictions would be particularly useful since many fold switchers are associated with human disease (3) (4) (5) (6) . Given the unexpected abundance of fold switching in the NusG superfamily, there may be many more unrelated fold switchers to discover. 

L.L.P. thanks Drs. Marius Clore and Carolyn Ott for constructive input throughout this project and for many excellent suggestions concerning the text and figures. Thanks to Dr. Nico Tjandra for generously sharing his lab and office space and Dr. David Landsman for administrative support. We also thank Drs. Liskin Swint-Kruse, Gisela Storz, Nico Tjandra, David Nyenhuis, and Daniel Morris for helpful comments concerning the text, Dr. Christos Kougentakis for helping to collect NUS NMR data, Dr. Nicholas Fitzkee for sharing his isotope labeling protocol, Dr. Aaron Robinson for help with NMR samples, and Dr. Xiaofang Jiang for recommending TaxonKit and ITOL. This work utilized resources from the NHLBI Biophysics Core, the NHLBI Protein Expression Facility, and the NIH HPS Biowulf cluster (http://hpc.nih.gov), and it was supported in part by the Intramural Research Program of the National Library of Medicine, National Institutes of Health and Howard Hughes Medical Institute.

Identification of NusG-like sequences NusG-like sequences were identified from the October 2019 Uniprot90 (36) database using an iterative BLAST (19) approach. Specifically, the E. coli RfaH sequence (Uniprot ID Q0TAL4) was BLASTed against the database. All hits with a maximum e-value of 10 -4 were aligned using Clustal Omega (37), which generated their sequence identity matrices from the resulting alignment. Sequences were clustered by their identities using the agglomerative clustering algorithm from the python module scikit-learn (38). Sequence identity between proteins in each cluster was ≥ 78%. Randomly selected sequences from the 25 largest clusters were then individually BLASTed against the Uniprot90 database, and the resulting hits were combined; redundant identical hits from independent searches were removed. This procedure (search-align-cluster) was repeated two additional times to generate the full list of 15,516 sequences in 305 clusters.

Determination of CTDs Sequences of annotated RfaHs were aligned to the sequence of E. coli RfaH (Uniprot ID Q0TAL4) using Clustal Omega (37). CTDs were defined as up to 50 residues, but not shorter than 40 if the CTD region comprised <50 residues, beginning with the positions that aligned to the RfaH sequence KVIIT. Sequences of proteins not annotated as RfaH were aligned to the E. coli NusG sequence (Uniprot ID P0AFG0) using Clustal Omega. CTDs were defined as 50 residues beginning with positions that aligned the NusG sequence EMVRV. Because of their diversity, sequences from each individual cluster were aligned against the NusG sequence separately, each using Clustal Omega. The number of sequences with CTDs long enough to make these predictions totaled 15,195 (Data S1), 98% of all NusG-like sequences identified.

JPred4 predictions JPred4 (18) predictions were carried out as in (12), sections 2.4 and 2.6. In further detail, they were first performed on all 50-residue CTD sequences using two databases: the JPred database (http://www.compbio.dundee.ac.uk/jpred/about_RETR_JNetv231_details.shtml) from 2014 and the Uniprot90 database from January 2021. Sequences of each prediction were aligned against the E. coli NusG sequence (beginning with EMVRV) using Biopython (39) Bio.pairwise2.localxs with gap opening/extension scores of -1.0/-0.5. Secondary structure predictions of the sequence in question and of E. coli NusG were reregistered according to the resulting pairwise alignments and compared as in (12) . Predictions were considered high-confidence if at least 5 sequences were in the MView (40)-generated alignments used by JPred.

We found that the first 10 residues in these 50-residue sequences were similar enough to NusG CTDs that NusG-like sequences overwhelmed sequence alignments informing the predictions, and many likely fold-switching sequences were predicted to be single folders. To circumvent this problem, predictions from both databases were rerun on 40-residue sequences (starting with the first residue that aligned to ADFNG… for NusG sequences and FQAIF… for RfaH sequences). Predictions were made as with 50-residue sequences. All predictions reported in the main text were from 40-residue sequences, except those in Figure 1B .

The 305 clusters generated from all full-length NusG sequences were plotted on a force-directed graph using the spring_layout function from python NetworkX (41) with a spring constant of 0.3 and 1000 iterations. Nodes with ≥50% of sequences predicted to switch folds were colored teal; nodes with <50% of sequences predicted to switch folds were colored red. Nodes with no predictions were colored gray. Nodes 1 and 7 were colored differently from their average predictions (single folding, Node 1; fold-switching, Node 7) to highlight the prediction of the sequence validated experimentally, which differed from the average. Edges represented average pairwise identities between nodes ≥24%, a threshold taken from (42) for sequences of 162 residues (the length of E. coli RfaH).

The annotated genomes (protein .fasta and .gtf annotation) of 31,554 bacterial species were downloaded from Ensembl Bacteria in April 2021. Genomic annotation of NusG was defined as being within 10 kb of a gene annotated as either "SecE," "RplK," "RplA," or "ribosomal protein L11" by text matching. Most bacterial genomes are incompletely assembled and annotated -the genes were required to be within the same chromosome, contig, or plasmid. Each Uniprot sequence in the database of 15,516 was mapped to an Ensembl locus if the species was consistent, and if sequence identity was greater than 90%. Annotation was fetched from Ensembl, as well -this was usually, but not always, consistent with the Uniprot annotation.

Of the 15,516 Uniprot sequences, 7975 mapped to Ensembl genomes. Cursory analysis of some non-mapping sequences suggested that: 1) some Ensembl genomes had incomplete collation of all ORFs, and 2) there were frame-shifts and other errors in some Uniprot sequences and some Ensembl genomes. This was also the case for some of the sequences predicted to potentially be fold-switching NusGs: for instance, Uniprot entry A0A0T8ANM4 is frame-shifted relative to the Ensembl genome, producing a C-terminal sequence predicted to switch folds.

Of the 5,435 sequences that mapped to Ensembl loci with SecE/RplK/RplA within 10kb, only 22 had a separation of >1kb, and only 59 had a separation of >270bp -this set of 59 includes 4 proteins predicted to be fold-switching, one of which is a verified RfaH from (15) , indicating that a shorter threshold of distance to SecE/RplK/RplA, perhaps coupled with determining distance several other conserved NusG-SecE operon genes, could reduce the false-positive rate caused by mistakenly annotating NusG SP s as housekeeping NusGs.

For a small number of sequences that mapped to qualitatively dissimilar genes (e.g., one genomically consistent as being a NusG, another not), the 2 nd mapping is given in Data S1, beginning in column AH.

Additionally, of the 600 RfaH sequences that mapped to an annotated Ensembl locus, only one fell within a NusG-like operon (~7kb away).

Expression and purification of variants 1-16 All variants were ordered from IDT as gBlocks. Except for variant #8, these variants were digested with HindIII and EcoRI and ligated into the pPAL7 vector (Bio-Rad) with an N-terminal 6-His tag cloned using a Q5 mutagenesis kit (New England Biolabs). Variants were transformed into E. coli BL21-DE3 cells (New England Biolabs), grown in LB at 37° to an OD600 of 0.6-0.8, after which they were incubated at 20°C for 30 minutes, induced with 0.1 mM IPTG, and grown overnight, shaking at 225-250 rpm. Variant #8 was cloned into the same vector as the other variants using In-Fusion and expressed as the other variants but at 18°C instead of 20°C. The cells from all cultures were pelleted at 10,000xg for 10 minutes at 4°C, resuspended in 2 mL lysis buffer (50 mM Tris, 150 mM NaCl, 5% glycerol, 1 mM DTT, 10 mM imidazole, pH 8.7) and frozen at -80°C for later purification. Sequencing of all variants was verified by Psomagen.

Thawed cell pellets were resuspended in 25 mL lysis buffer per 1 L of culture grown. 100 mg of DNAseI, 5 mM CaCl2, 5 mM MgSO4 and 1/2 of a cOmplete EDTA-free protease cocktail inhibitor tablet (Roche) were added per 25 mL of lysis buffer. Cells were lysed by 2 passes through an EmulsiFlex-C3 homogenizer (Avestin). The homogenized lysate was centrifuged for 45 minutes at 40,000xg at 4°C, and its soluble fraction was loaded immediately onto either a 1 mL Ni column (GE HisTrap HP) or an Econo-Pac (Bio-Rad) gravity column with 0.5-1 mL IMAC Ni Resin (Bio-Rad). Soluble lysate was loaded on ice for the HisTrap column, and gravity columns were loaded and kept at 4°C. The HPLC Ni columns were washed with 100 mM phosphate and 500 mM NaCl, pH 7.4, equilibrated in 100 mM phosphate, pH 7.4, and eluted by gradient with 0.5 M imidazole, 100 mM phosphate, pH 8.0 at 2 mL/minute on an ÄKTA Avant. The gravity columns were washed and equilibrated with 10 column volumes each of the same buffers, and protein was eluted at 3 different imidazole concentrations: 100 mM, 500 mM and 2M, all in 100 mM phosphate, pH 7.4.

Nickel-purified samples were then loaded onto 1-or 5-mL Profinity eXact (43) columns (Bio-Rad), washed twice with one column-volume of 2M NaOAc, and eluted with 100 mM phosphate, 10 mM azide, pH 7.4 at 0.2 mL/minute. Cleavage kinetics for some variants (1, 4, and 6) were too slow to get adequate tagless protein. In these cases, columns were equilibrated with 100 mM phosphate, 10 mM azide, pH 7.4 overnight at 4°C. Tagless protein was concentrated in 10 kDa MWCO concentrators (Millipore), and the buffer was exchanged to 100 mM phosphate, pH 7.4. A small amount of high-molecular-weight impurity (<10% of the sample) from variants #1 and #4 was removed by running the tagless sample through a 50 kDa MWCO concentrator (Millipore) and keeping the low molecular weight fraction that passed through the filter. Sample purities were assessed by gel electrophoresis (Thermofisher NuPAGE 4-12% Bis-Tris gels, Thermofisher MES buffer, Bulldog Bio Coomassie Stain), and concentrations were measured on a NanoDrop OneC (Thermo Scientific).

Circular dichroism (CD) spectroscopy All CD spectra were collected on Chirascan spectrometers (Applied Photophysics) in 1 mm quartz cuvettes in 100 mM phosphate, pH 7.4. Protein concentrations ranged from 8-12 mM, and scan numbers ranged from 5-10. Scans were averaged, and averaged baselines of buffer-blank 1 mm cuvettes were subtracted from the spectra. The resulting spectra were entered into the BestSel (44) webserver (https://bestsel.elte.hu/index.php), so that their ratio of helix (helix+distorted helix):strand (parallel+antiparallel) could be computed.

Full-length variants #5 and #8 were shortened to 64 and 68 residues, respectively, using Q5 mutagenesis (New England Biolabs). Their sequences were confirmed by Sanger sequencing (Psomagen) and are reported in Table S2 .

Expression and purification of NMR samples Based on the protocols in (45-47), BL-21 DE3 cells (New England Biolabs) expressing all NMR samples were grown in LB to an OD600 of 0.6 and pelleted at 5000xg for 30 minutes at 4°C. The pellets were resuspended in 1X M9 at half of the initial culture volume and pelleted at 5000xg for 30 minutes at 4°C. Pellets were then resuspended at ¼ initial culture volume in 2X M9, pH 7.0-7.1, 1 mM MgSO4, 0.1 mM CaCl2, with 1 g 15 NH4Cl/L, and 4 g of either unlabeled or 13 C-labeled glucose (Cambridge Isotope Laboratory)/L and equilibrated at 20°C for 30 min, shaking at 225 rpm, then induced with 1 mM IPTG and grown overnight. Cells were pelleted at 10,000xg for 10 minutes at 4°C. All labeled variants were purified by FPLC (ÄKTA Avant 25) using the same methods as variants 1-16 above in 5 mL HisTrap HP columns (Cytiva) and 5 mL Profinity eXact columns (BioRad).

All spectra were collected on Bruker 600 MHz spectrometers equipped with z-gradient cryoprobes and processed with NMRPipe (48). Variant #8 (full-length and CTD) and variant #5 CTD HSQCs were collected in 100 mM phosphate, pH 7.4 at 298 K. Under those conditions the spectrum of full-length variant 5 was broad, even with 1 mM DTT added, but peaks narrowed upon changing the buffer conditions to 25 mM HEPES, 50 mM NaCl, 5% glycerol, 1 mM DTT, pH 7.5, and collecting the spectrum at 303K. Protein concentrations ranged from 100-300 uM.

Assignments of KCTD and TCTD 13 C-labeled 5CTD and 8CTD were expressed and purified as above. For each variant, HNCACB, CBCA(CO)NH, and HNCO experiments were collected on Bruker 600 MHz spectrometers with cryoprobes. Spectra of 8CTD (80 uM) were collected using nonuniform sampling and were processed with SMILE (49). All NMR spectra were processed using NMRpipe (48). Resonances were assigned manually with NMRfam Sparky (50), and secondary structures were determined using TALOS+ (51).

Coevolutionary analysis Structure predictions of the 6 fold-switching variants were calculated by entering their full-length sequences (Table S3 ) into the EVCouplings (25), Robetta (24) , and Phyre2 (26) webservers (https://evcouplings.org, https://robetta.bakerlab.org, http://www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index). EVCouplings predictions with the recommended e-value cutoffs for chosen: (Variant 1: e-3, 2: e-5, 3: e-5, 4: e-20, 5: E-5, 5: e-5). High-confidence predictions for shorter sequences of 40 or 50 residues could not be obtained from either EVCouplings or Robetta. Predicted residue-residue contacts of E. coli RfaH from EVCouplings/Robetta with probabilities ≥ 99%/92% were plotted in Figure 3A , and residueresidue contacts from GREMLIN (27) with probabilities ≥90% were plotted in Figure 3B . These thresholds were determined by maximizing the ratio of true positives to false positives. True positives were considered to be couplings with heavy atoms within 5.0 Å in either the 2OUG or the 2LCL crystal structures where at least one of the 2 heavy atoms was from a side chain; one additional contact between residues 140 and 151 was added because they were separated by 5.2 Å within the NMR structure and therefore likely within error of 5.0Å. Contacts were considered hydrophobic if both atoms in contact were hydrophobic, Coulombic if two atoms in contact had opposite charge and C-N-O/C-O-N angles ≥ 90°, and helix caps if the distance between sidechain donor/acceptor ≤4° and C-N-O/C-O-H angles ≥ 90° (52). All distances and angles were calculated using LINUS (53).

CTD sequences for GREMLIN webserver (http://gremlin.bakerlab.org/submit.php) analysis in GREMLIN webserver analyses were run on EVCouplings and Robetta multiple sequence alignments seeded with the sequence of E. coli RfaH. These alignments were taken from EVCouplings align and Robetta .msa.npz files. No additional iterations of HHPred were run on either alignment. Coverage and remove gaps filters were both set to 75.

Pairwise sequence identities Pairwise sequence identity matrices of predicted fold-switching/single-folding CTDs were calculated using Geneious. The alignments for these sequences were first manually curated to remove sequences that did not align well with the majority; manually curated alignments retained at least 98% of all sequences. The mean/median sequence identities of these two groups were determined from the upper triangular matrices of each matrix, excluding positions of identity, using numpy (55). Pairwise sequence identity matrices of the CTDs of the 10 variants were determined with Clustal Omega.

The tree in Figure 4C was generated by downloading the Interactive Tree of Life (56) (https://itol.embl.de/itol.cgi), loading it into FigTree (57), and collapsing branches at the phyletic level, except for Proteobacteria, which were left at the class level because of recent phylogenetic work on proteobacterial RfaH (15) .

Bacterial species from each NusG sequence were obtained from their Uniprot headers. These species were mapped to their respective phyla using TaxonKit (58) and matched with their predictions. Phyla with fold-switching/single-folding predictions were listed using a python script, and branches of the tree were then colored manually in Adobe Illustrator.

Eukaryotic and archaeal NusG homologs were obtained by running 3 rounds of PSI-BLAST on the nr database with the following seed sequences: L1IE32, A0A0N95N5M7, UPI0005F5777A, A0A2E6HKN0. Redundant sequences were removed using CD-HIT (59) at a 98% sequence identity threshold (at least 1 amino acid difference). Figures 1C, 2A, 2B , 3A, 3B, 4A, and 4B were generated using Matplotlib (60). The figures of all protein structures ( Figures 1A and 3C ) were generated using PyMOL (61).

Distributions of prediction discrepancies for Uniprot-annotated RfaHs (A) and sequences not annotated as RfaH (B). Black dotted line is the cutoff point for fold-switching and single-folding predictions: predictions with ≥5% discrepancy to the E. coli NusG sequence were predicted to switch folds. This cutoff was taken from Kim, et al. (12) . Because of the low threshold, experiments were performed on constructs just above/below the threshold (Constructs 1, 4, and 7, respectively, Table S1, Figure 2 ). For comparison, the y-axis of both plots was limited to 410 counts. All bins fell below that threshold except for the first bin of panel B, which had 11,032 counts (and thus is not shown to scale).

Sequence space diagram with cluster numbers labeled. Numbers correspond to the Cluster IDs (column 3) in Data S1.

All sequence space constructs tested. Constructs 1-10 are labeled as in Figure 2 . Constructs 11-16 were tested, but CD spectra could not be obtained because they did not express (Constructs 11-13 and 15-16) or because they were insoluble (Construct 14). With the exceptions of Constructs 8-10, all labels are directly below the nodes from which sequences were selected. Teal/red nodes: predicted to/not to switch folds on average; no high-confidence predictions were made for gray nodes. More information about each construct can be found in Table S1 . Nodes 1 and 7 were colored differently from their average predictions (single folding, Node 1; fold-switching, Node 7) to highlight the prediction of the sequence validated experimentally, which differed from the average.

Circular dichroism (CD) spectra of two different E. coli RfaH preps differ significantly from two different E. coli NusG preps. By contrast, CD spectra of the two different preps of both RfaH and NusG are nearly identical to one another.

TALOS+ secondary structure predictions of the assigned CTDs of Construct 8 (above) and Construct 5 (below). Plots suggest that both CTDs fold into structures with 5 b-sheets, consistent with the NusG b-roll fold. GREMLIN couplings calculated from EVCouplings (A) and Robetta (B) sequence alignments largely match contacts from the experimentally determined b-roll fold (red, PDB ID 2LCL) but did not match any contacts unique to the helical hairpin fold (teal, PDB ID 2OUG_A).

JPred-filtered couplings of putative full-length fold switchers calculated by GREMLIN. No interdomain contacts (found within red boxes) were consistent with the experimentally determined structure of full-length RfaH (PDB ID: 2OUG). 

Extant fold-switching proteins are widespread

Principles that govern the folding of protein chains

Functional and Regulatory Roles of Fold-Switching Proteins

CLIC1 Promotes the Progression of Gastric Cancer by Regulating the MAPK/AKT Pathways

Secondary structure reshuffling modulates glycosyltransferase function at the membrane

Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms

Protein structure prediction from sequence variation

Improved protein structure prediction using predicted interresidue orientations

Improved protein structure prediction using potentials from deep learning

Multiple stable conformations account for reversible concentration-dependent oligomerization and autoinhibition of a metamorphic metallopeptidase

Sequence-Based Prediction of Metamorphic Behavior in Proteins

A high-throughput predictive method for sequence-similar fold switchers

Inaccurate secondary structure predictions often indicate protein fold switching

Structural Basis for Transcript Elongation Control by NusG Family Universal Regulators

An alpha helix to beta barrel domain switch transforms the transcription factor RfaH into a translation factor

Reversible foldswitching controls the functional cycle of the antitermination factor RfaH

JPred4: a protein secondary structure prediction server

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

Structural basis for converting a general transcription factor into an operon-specific virulence regulator

Structural basis of transcription-translation coupling

LoaP is a broadly conserved antiterminator protein that regulates antibiotic gene clusters in Bacillus amyloliquefaciens

NusG, an Ancient Yet Rapidly Evolving Transcription Factor

Protein structure prediction and analysis using the Robetta server

The EVcouplings Python framework for coevolutionary sequence analysis

The Phyre2 web portal for protein modeling, prediction and analysis

Robust and accurate prediction of residueresidue interactions across protein interfaces using evolutionary information

Evolution of fold switching in a metamorphic protein

Protein dynamism and evolvability

RfaH enhances elongation of Escherichia coli hlyCABD mRNA

The transcriptional antiterminator RfaH represses biofilm formation in Escherichia coli

Quinary structure modulates protein stability in cells

Data S1. Annotations and predictions of all sequences identified in the NusG superfamily.Data S2. Additional annotations and predictions of archaeal and eukaryotic sequences used to determine the tree in Figure 4 .