Structural Transitions in Ancient Chaperonins Illustrate Pathways to Protein Complexity

Structural Transitions in Ancient Chaperonins Illustrate Pathways to Protein Complexity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Structural Transitions in Ancient Chaperonins Illustrate Pathways to Protein Complexity Rita Severino, Jorge Cuellar, Jorge Gutiérrez-Seijo, Moisés Maestro-López, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7270162/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Nov, 2025 Read the published version in Molecular Biology and Evolution → Version 1 posted You are reading this latest preprint version Abstract Chaperonins are essential protein-folding machines that can be categorized into three groups based on their structure and phylogeny: Group I (bacterial GroEL), Group II (archaeal thermosome and eukaryotic CCT), and Group III (bacterial thermosome-like). We used ancestral sequence reconstruction (ASR) and protein resurrection (PR) to infer and experimentally test ancestral chaperonins (ACs) from the last common ancestors of these groups (ACI, ACII, and ACIII). The reconstructions exhibited ATPase activity (except for ACII) and client protein heat protection. Electron microscopy and Cryo-EM showed that ACI formed single 7-mer rings, while ACII formed a mix of single/double 8-mer rings, indicating a gradual evolution from simple single-ring to more complex double-ring structures. We also found a unique cochaperonin-independent closing mechanism in ACII. Together, our results illustrate the early stages of molecular complexity evolution and demonstrate how ancestral proteins can inform models of early cellular life. Biological sciences/Evolution Biological sciences/Structural biology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Protein folding is a cornerstone of cellular function and overall organismal health, as misfolded or aggregated proteins can cause various cellular malfunctions. At the core of this process are a large group of proteins known as molecular chaperones. Among them, chaperonins (also known as Hsp60 chaperones) are a ubiquitous family across all life kingdoms. These large, barrel-shaped complexes act as molecular machines, providing a protected environment for newly synthesized proteins to fold efficiently, a critical aspect of protein homeostasis 1 – 3 . Beyond folding, chaperonins also defend against stress (e.g., temperature fluctuations, oxidative stress, or chemical exposure) by preventing aggregation and assisting in refolding misfolded proteins 4 – 7 . Chaperonins likely evolved from a multifunctional ancestor within the thioredoxin superfamily, specifically a peroxiredoxin-like protein with both antioxidant and chaperone activities 4 , 8 . This dual functionality persists in modern thioredoxin-domain containing chaperedoxins (which associate with GroEL in vivo ) and peroxiredoxins, highlighting their role in shielding proteins and DNA from oxidative and thermal stress 9 – 11 . This evolutionary origin suggests that extreme environmental pressures (e.g., high temperature, acidity, variable salinity) shaped early chaperonins. The widespread presence and persistence of chaperonins and thioredoxins in bacterial genomes, often under positive selection, underscores their evolutionary importance and adaptability 12 . All chaperonin monomers share a common three-domain structure ( Supplementary Fig. 1 ): an apical domain involved in substrate recognition, an equatorial domain containing the ATP-binding site that drives the conformational changes that occur during the chaperonin functional cycle, and an intermediate domain linking the two by relaying signals. Despite this conserved framework ( Supplementary Fig. 1a ), chaperonins diverge into three structurally distinct groups (Group I-III) based on their unique architecture and phylogeny 1 – 4 . This structural diversity raises intriguing questions about their evolutionary origins, including how their common ancestor emerged and how they diverged. Group I chaperonins, found in bacteria and eukaryotic organelles (e.g., mitochondria and chloroplasts), are exemplified by the well-studied GroEL/GroES system of Escherichia coli . GroEL consists of two stacked rings, each comprising seven identical subunits (~ 60 kDa), while GroES (~ 10 kDa) forms a homoheptamer that caps the GroEL folding chamber, acting as a cochaperonin. Group II chaperonins, present in archaea and the eukaryotic cytosol (e.g., the thermosome in archaea and the CCT/TRiC complex in eukaryotes), feature a built-in "lid" mechanism, eliminating the need for a separate cochaperonin. Group II chaperonins have evolved from rings composed of 1–3 different subunits in the archaeal thermosome, to 8 distinct subunits in the eukaryotic CCT (CCT1-CCT8) 2 . Group III chaperonins, found in some bacteria, resemble Group II but lack the nucleotide-sensing loop present in Groups I and II 13 , 14 ( Supplementary Fig. 1b ). This conserved amino acid sequence directly influences the rate of nucleotide hydrolysis, thereby controlling the timing of the folding cycle. The nucleotide-sensing loop undergoes conformational changes that regulate the opening and closing of the chaperonin rings and facilitates communication by transmitting ATP hydrolysis signals between subunits 15 . The structural differences between these groups suggest different evolutionary paths, yet their shared function and homology indicate a common ancestral origin 8 . The evolutionary relationships between these groups remain unresolved. Some researchers propose that Group III chaperonins represent an ancient form from which Groups I and II originated, with GroES possibly arising from the excision of the lid region of a Group III chaperonin 13 . Others argue that Group III chaperonins emerged later, possibly through horizontal gene transfer from an ancestral archaeon to a bacterial Firmicute 14 , 16 . These competing hypotheses highlight the complexity of chaperonin evolution and the need for new approaches to unravel their history. Ancestral Sequence Reconstruction (ASR), first proposed in 1963 by Pauling and Zuckerkandl 17 , is a powerful tool to address these questions. By inferring the sequences of ancient chaperonins and then "resurrecting" them in the laboratory, we can gain insights into the structural and functional properties of these molecular machines in early life 18 , 19 . ASR followed by protein production, also known as “protein resurrection” (PR), has been successfully applied to other ancient proteins, revealing trends such as increasing promiscuity, greater conformational diversity, higher thermal stability, and improved heterologous expression 20 , 21 . For example, ASR studies of ancient thioredoxins, nitrogenases, β-lactamases, V-ATPases, elongation factor Tu, and RuBisCO, have provided valuable insights into the evolution of protein complexity and function 22 – 29 . In this study, we apply ASR-PR to chaperonins to explore their evolutionary origins and structural diversification. By rebuilding ancestral chaperonin (AC) sequences and examining their oligomeric structures, we aim to answer key questions: which group of chaperonins evolved first, and how did the structural differences between Groups I, II, and III emerge over evolutionary time? Beyond shedding light on chaperonin evolution, these findings are expected to offer insights into how early life may have adapted to extreme environments on Earth and potentially on other planets 30 . Results Reconstruction and characterization of ancestral chaperonins To better understand the evolutionary history of chaperonins – one of the oldest protein families found across of all life forms – we reconstructed their phylogenetic history using 96 representative prokaryotic chaperonin sequences ( Supplementary Fig. 2 ). In the absence of an outgroup, the precise location of the Last Unknown Common Ancestor (LUCA) cannot be identified, although it is reasonable to assume that it is situated somewhere on the branch connecting bacterial and archaeal populations. We selected several AC nodes for PR, including the last common ancestors of Group I (ACI), Group II (ACII), and Group III (ACIII), along with the ancestor of the Fibrobacteres-Chlorobi-Bacteroidetes (FCB) Group (AFCB) (Fig. 1 , Supplementary Fig. 2 ). The FCB Group is notable for being the only known prokaryotic group capable of synthesizing both bacterial and archaeal membrane lipids. This suggests that LUCA might have had mixed archaeal/bacterial membranes, possibly a remnant from before bacteria and archaea diverged 31 . The predicted AC sequences showed a sequence identity of 60–81% when compared with modern homologs, and were dated using data from the TimeTree project 32 ( Table I ). E. coli BL21 (DE3) cells were transformed with plasmids encoding four ancestral sequences, and the recombinant proteins were expressed and purified as described in Methods ( Supplementary Fig. 4 ). We first studied how these purified AC proteins assembled using transmission electron microscopy. ACI formed a 7-subunit single-ring oligomer, but only in the presence of ATP-Mg2+. ACII formed a heterogeneous mixture of 8-subunit oligomers, including both single and double rings, even without ATP. However, adding ATP-Mg² + increased the overall number of oligomers compared with individual monomers. ACIII assembled as 8-subunit double rings without ATP-Mg² + , and AFCB formed 7-subunit double rings (Figs. 2 – 6 ). Structural characterization of ancestral chaperonins by cryoelectron microscopy To investigate the structural details of the new proteins, we used cryoelectron microscopy (CryoEM) to determine their high-resolution 3D structures. We vitrified aliquots of the purified ACs, and the best grids were used for CryoEM data acquisition using the parameters described in Supplementary Table I . Image processing and subsequent 3D reconstruction procedures are detailed in the Methods section and Supplementary Figs. 5–8 . The 2D classification of particles of the four ACs revealed that whereas ACI and AFCB formed heptameric rings, ACII and ACIII assembled into octameric rings, mirroring their modern counterparts (Figs. 2 – 6 ). Regarding their overall structure, a typical chaperonin double-ring structure was observed for ACIII and AFCB. By contrast, ACI showed single-ring structures, and ACII displayed a mixture of double rings (majority) and single rings. Detailed 3D analysis of ACI confirmed its assembly into stable, single heptameric rings (Fig. 2 a and Supplementary Fig. 5 ). While the “open state” structure provided valuable insights, its resolution was likely limited by the inherent structural flexibility of the chaperonin, particularly in the apical domain. This flexibility is evident in the lidless ACI map (Fig. 2 a and Supplementary Fig. 5 ), which shows well-resolved α-helices in the equatorial domain but less defined features in the apical and intermediate domains (EMD-54342). Although these regions are typically harder to resolve, the increased dynamics of the apical domains might have been crucial in the early evolution of Group I chaperonins. To further investigate the ACI single-ring architecture, we compared its sequence and structure with the well-characterized E. coli single-ring mutant (SR1) 33 . Four amino acid substitutions (R452E, E461A, S463A, and V464A) distinguish SR1 from canonical E. coli GroEL, and are known to disrupt double-ring assembly 33 (Fig. 2 c). We found three of these four substitutions in ACI (E→D, S→A, and V→E), which likely interfere with the inter-subunit interfaces needed for double-ring formation. Ancestral sequence reconstruction for these four residues yielded high posterior probabilities: R (0.89), D (0.95), A (0.82), and E (0.48). Their evolutionary trajectories further highlighted dynamic shifts ( Supplementary Table II ): the probability of residue R increases in probability from 0.89 to 1 by node 121, indicating fixation; Residue D, initially highly probable (0.95), decreases to 0.75 at node 108 and is gradually replaced by E from node 113, reaching fixation by node 128; Residue A decreases in probability to 0.44 at node 104, and is then replaced by S from node 109, becoming fixed by node 121; Residue E increases in probability up to node 107, but is ultimately replaced by V with probability 1 at node 108. ACII was purified as a mixture of monomers and oligomers, and the presence of ATP triggered the typical conformational changes typical of chaperonins, transitioning between open and closed states. The 2D and 3D analysis of the particles revealed both single- and double-ring structures in both open and closed configurations ( Fig. 3 b and Supplementary Fig. 6 ). However, only the closed double-ring structure, the most abundant oligomeric state (35% of all particles), yielded a map with sufficient resolution for atomic modeling ( Supplementary Fig. 6c ) (PDB 9RWP). When comparing this structure with modern chaperonins such as E. coli GroEL (Group I) or the group II eukaryotic chaperonin CCT (Fig. 4 ), we found that ACII possesses a built-in helical lid protrusion, similar to CCT. This feature allows ACII to close its cavity without needing a separate co-chaperonin like GroES, which GroEL requires. This structural element suggests that ACII developed an early mechanism for cavity closure. This mechanism is independent of a GroES-like co-chaperonin and predates the more complex mechanisms seen in modern Group II chaperonins, with CCT being the most complex example (Fig. 4 b). An interesting observation was that the closed conformation of ACII is less tightly locked than that of CCT (compare central and right structures in Fig. 4 a, respectively), indicating distinct closure mechanisms between the two chaperonins. To understand the atomic-level changes that drive CCT-like closure, we first analyzed the structural changes observed within the apical, intermediate, and equatorial domains of ACII and CCT subunits. By calculating the root-square-mean deviation (RSMD), which measures differences in protein backbones, we found that the main changes occur in the arrangement of the apical region, including the intermediate domain (Fig. 4 b). Further examination of the intra-subunit interactions highlighted several notable aspects. In the built-in lid, CCT contacting-subunits exhibited somewhat different interactions. For example, a salt bridge forms between H312 of CCT5 (the CCT subunit most similar to ACII in the apical region) and E330 of CCT2. These interactions are further stabilized by hydrogen bonds between H312 and Q316 of CCT5 with T334 and E330 of CCT2, respectively (Fig. 4 c). In ACII, a similar salt bridge exists between H299 and E334. However, due to a lack of interactions in the tip of the apical region, E334 forms a stronger interaction with K303. The positive charge of K303 allows for an additional interaction, similar to that observed with Q316 of CCT5 (Fig. 4 c). In the central part of the helical protrusion, CCT forms strong interactions between K282 of CCT5 and D336 of CCT2, generating a salt bridge in the middle of the helix. At the end of the protrusion, these interactions are reinforced by the hydroxyl group of Y274, which interacts with K74 and E271 of CCT2. In ACII, these interactions are absent. Only a hydrogen bond is formed by P258 and Q267 (Fig. 4 c, left ). Additionally, potential repulsive forces along the helical protrusion in ACII further support this (Fig. 4 c, right ). Altogether, these observations suggest that while ACII possesses a built-in lid that reduces reliance on a GroES-type cochaperonin for cavity closure, the resulting closure is less complete than that of CCT subunits, where total sealing prevents solute entry or exit. In the case of ACIII, oligomeric structures were visible in the absence of ATP, and they all formed double-ring structures ( Supplementary Fig. 7 ). The structure obtained (Fig. 5 ) (PDB 9RWQ) resembles that of the modern thermosomes 34 ( Supplementary Fig. 1 ), although the flexibility observed in the apical domains ( Supplementary Fig. 7c ) prevented us from modeling these regions (Fig. 5 b). Finally, our structural characterization of AFCB (Ancestral FCB Chaperonin) revealed a strikingly modern architecture (Fig. 6 and Supplementary Fig. 8 ). There was no need for the addition of ATP to generate a stable, homogeneous population of double-ring oligomers ( Supplementary Fig. 8a and b ). This enabled us to obtain a 3.4 Å resolution map (Fig. 6 a) and build the corresponding atomic model (Fig. 6 c) (PDB: 9RWR). Unsurprisingly, AFCB closely resembles E. coli GroEL, sharing a 71% sequence identity (see Fig. 6 b). Although resurrecting the GroES-type cochaperonin was beyond the scope of this study, an analysis of key residues involved in the GroEL-GroES interaction showed that all three essential residues are conserved in AFCB (Fig. 6 d). This strongly suggests that AFCB likely interacts with a GroES-type cochaperonin, hinting at the co-evolution of the chaperonin and its cochaperonin counterpart within the FCB lineage. Functional evaluation of ancestral chaperonins We next compared the activity of ACs with that of modern E. coli (Group I, Uniprot: P0A6F5) and Carboxydothermus hydrogenoformans (Group III, UniProt: Q3AF10), expressed and purified under identical conditions. ATPase activity was monitored in 10°C increments from 30°C and 60°C using BIOMOL GREEN™ Reagent, which detects phosphate released during ATP hydrolysis (see Methods) 35 ( Fig. 7 a). The Group III chaperonin from C. hydrogenoformans , a thermophile, showed the highest rate of ATP hydrolysis, followed by AFCB. The remaining chaperonins E. coli GroEl, ACI and ACIII exhibited similar hydrolysis patterns. C. hydrogenoformans ATPase hydrolysis peaked at 60ºC, while the others peaked at 50ºC. No ATP hydrolysis was detected for ACII. ATPase activity for C. hydrogenoformans and E. coli was consistent with previous reports 13 , 36 . To evaluate chaperonin function, we assessed their ability to protect lactate dehydrogenase (LDH) from heat-induced inactivation. LDH catalyzes the conversion of pyruvate to lactate while reducing NAD + to NADH, which can be monitored spectrophotometrically at 340 nm. When incubated at 48°C, LDH lost 50% its activity within 15 minutes and almost all activity by 35 minutes. However, LDH activity was preserved in the presence of ancestral or modern chaperonins (Fig. 7 b). The modern C. hydrogenoformans chaperonin initially boosted LDH activity after 5 minutes, followed by a return to baseline levels at 15 minutes and a slight decrease to 75% of the initial activity by 35 minutes. AFCB and ACIII showed similar patterns, with a small initial increase in LDH activity before stabilizing at ~ 75% activity after 35 minutes. By contrast, ACI and ACII provided sustained protection: LDH activity remained at ~ 150% with ACII throughout the experiment, while ACI caused a 2.5-fold increase in activity within the first 5 minutes before returning to baseline levels by the end of the incubation. Evolutionary trends in electrostatic potential and folding energy To further characterize ACs and identify potential features, we analyzed their electrostatic properties using the APBS method 37 (implemented in PyMol), and calculated variations in folding energies with FoldX (see Methods) (Table II ). Electrostatic map calculations revealed that the most ancestral reconstructions (ACI and ACII) predominantly displayed a negative surface electrostatic potential (Fig. 8 ). Computational analysis of free folding energies revealed significant correlations between ancestrality and key structural parameters – hydrogen bonds, entropy, electrostatic interactions, solvation effects, Van der Waals interactions and torsion energy – all of which contribute to protein stability ( Table II ). Group I ancestors showed significant positive (≥ 0.5) correlations with backbone hydrogen bonds (r = 0.94), side-chain hydrogen bonds (r = 0.77) and ionization energy (r = 0.59); and significant negative (≤-0.5) correlations with main-chain entropy (r = -0.86) and torsion energy (r = -0.60). Group II ancestors showed significant positive correlations with backbone hydrogen bonds (r = 0.90), side-chain hydrogen bonds (r = 0.54) and charge-charge interaction (r = 0.70); and significant negative correlations with side- (r = -0.70) and main-chain (r = -0.50) entropy, and ionization energy (r = -0.51). Group III ancestors showed significant positive correlations with total stability (r = 0.54), Van der Waals interaction (r = 0.63), nonpolar solvation (r = 0.55), and torsion energy (r = 0.86); and significant negative correlations with polar solvation (r = -0.55), backbone Van der Waals clashes (r = -0.51) and helix dipole effects (r = -0.68). These divergences suggest that different chaperonin lineages developed specialized strategies, using diverse physicochemical mechanisms, to optimize protein stability. Discussion Intermediate single-ring structures in ancestral chaperonins support a stepwise oligomerization model Our phylogenetic analysis, based on 96 modern sequences, produced a topology consistent with previous studies 16 , 38 – 41 , and allowed us to resurrect and characterize four ancestral nodes (ACI, ACII, ACIII, and AFCB) ( Supplementary Fig. 2 ). We observed that the earliest ancestors – ACI (bacterial GroEL) and ACII (archaeal thermosome) – are single-ring structures. In Group I systems, double-ring structures are known to dissociate upon ATP hydrolysis, increasing folding capacity for larger substrates, and single-ring structures have been observed in bacteriophage-encoded chaperonins (e.g., φ-EL and OBP), the human mitochondrial chaperonin, and bacterial GroEL/ES systems 42 . To our knowledge, ACII represents the first reported single-ring structure for a Group II chaperonin. The evolutionary progression from an exclusively single-ring structure in ACI, to a mix of single and double rings in ACII, and finally to an exclusively double-ring assembly in ACIII (Fig. 1 ), suggests a gradual, step-by-step evolution from single- to double-ring chaperonins. This pattern supports a timeline where ACI is the oldest ancestor, followed by ACII and then ACIII – with the latter likely arising through horizontal gene transfer between an ancestral archaeon and a Firmicutes bacterium 14 , 16 rather than being a direct descendent from LUCA 13 . Sequence divergence patterns ( Table I ) further corroborate this timeline, showing ACI as the most divergent, followed by ACII, ACIII, and finally AFCB. Structurally, ACII features a unique build-in helical protrusion that acts as a lid, eliminating the need for a GroES-type cochaperonin for cavity closure ( Supplementary Fig. 6 ). This feature may reflect an intermediate evolutionary stage between the architectures of modern Group I and II chaperonins. Another key difference lies in their subunit structure: ACI and has seven subunits while ACII has eight – a stoichiometry that mirrors their modern counterparts (Figs. 2 and 3 ). These differences could stem from the presence of multiple assembly types in LUCA, or reflect lineage-specific changes in ring size over evolutionary time. Such evolutionary divergence in subunit stoichiometry is also observed in modern complexes: for example, archaeal peroxiredoxins (a thiol-dependent peroxidase that protects cells from oxidative damage) often form pentameric rings, whereas bacterial homologs adopt hexameric forms 10 , 43 . Functionally, chaperonins operate through two major conformational states: an open state for substrate recognition, and a closed state that traps and facilitates protein folding. The ACs appear to have developed two distinct mechanisms for cavity closure. Bacterial chaperonins co-evolved with a small capping oligomer (the cochaperonin), whereas archaeal and eukaryotic chaperonins developed an extra sequence, a lid-like protrusion that fulfils the same locking role. These functional variations suggest that the conserved folding chamber of chaperonins adapted to distinct functional and environmental pressures. While the evolutionary relationships between Bacteria, Archaea, and Eukarya are still debated (and may never be fully clarified), our findings align with the classical model in which Bacteria are evolutionarily closer to LUCA 44 . The evolution of protein complexity – from simpler to more structurally and functionally elaborate proteins (such as from monomers to oligomers or through the acquisition of additional domains) – has been explored using ASR in previous works 18 . In particular, multimerization has been investigated in the ATPase complex 28 and RuBisCO 27 , 29 protein families. Thornton and colleagues have shown that such transitions can occur naturally through just one or a few mutations 18 , 45 . Building on this work, our study reveals an evolutionary trajectory within the chaperonin family. We found that ACI likely transitions between monomeric and single-ring states, representing an early stage in oligomerization. By contrast, ACII and ACIII predominantly form stable double-ring assemblies, suggesting that the molecular framework for full oligomeric complexity was already established in these groups. The coexistence of both single- and double-ring assemblies in ACII illustrates an evolutionary intermediate in which the molecular architecture for oligomerization had emerged but was not yet fully optimized – likely lacking one or a few key mutations needed to substantially enhance binding affinity and stabilize the double-ring state 18 , 45 . While we did not explicitly test mechanistic models for the evolution of molecular complexity, our analysis of the posterior probabilities of the amino acids at positions known to disrupt double-ring assembly (R452E, E461A, S463A, V464A) in E. coli GroEL 33 showed that the ancestral sequence (ACI) retained three of these substitutions with high confidence ( Supplementary Table II ). Tracking these probabilities across nodes revealed dynamic shifts: residues that potentially prevent double-ring formation in ACI gradually gave way to substitutions that favor stable double-ring interfaces. Together, these patterns further support a gradual evolutionary transition from a single-ring to a double-ring architecture in early Group I chaperonins – a shift predicted to have reached completion by node 128 ( Supplementary Fig. 3 ), corresponding to the divergence time of the FCB group. ATP-dependent stability and activity in ancestral chaperonins ATP played an essential role in the assembly of ACI oligomers and often enhanced the assembly of ACII by increasing the number of oligomers. By contrast, ACIII and AFCB did not require ATP for either assembly or stability. This suggests that ATP dependency was strongest in the most ancestral nodes, particularly ACI. Some modern thermosomes exhibit ATP-dependent oligomer formation, which could be an evolutionary remnant from ancestral times 34 . Under neutral conditions, ATPase activity was detected in all ancestral chaperonins tested, with the exception of ACII (Fig. 7 a). The absence of detectable activity in ACII could indicate a requirement for specific cofactors, such as ammonium salts, as observed in certain methanogenic archaea 46 and bacterial thermosome-like systems 14 . Despite its lack of detectable ATPase activity, ACII proved to be highly effective at protecting LDH from heat inactivation (Fig. 7 b). Indeed, it outperformed the other chaperonins in maintaining LDH stability at 48°C, sustaining 150% of its activity throughout the experiment. Although we initially attempted to assess the ability of these ACs to assist in refolding of chemically denatured proteins, technical challenges prevented these assays from being carried out. Specifically, we were unable to detect successful refolding even with E. coli GroEL as a control, likely due to the absence of its essential co-chaperonin GroES under our experimental setup. Consequently, we shifted our focus to a more limited, but still insightful, protective assay (LDH heat inactivation), which provided valuable insights into the stress-response capacity of the ACs. While molecular crowding could theoretically explain this effect, the variations seen among the different chaperonins suggest it was not the primary cause. Although the closest modern sequences to our reconstructions (in the NCBI nr-database) were from thermophilic organisms ( Table I ), the activity of our ancestral proteins was comparable with that of the mesophile GroEL from E. coli 36 . This contrasts with other proteins reconstructed through ASR, which often display high thermostability 21 . This suggests that ACs might be a unique case where extreme thermal stability was not a defining ancestral trait or a functional requirement. However, our results on ATP-dependent stability and activity do not necessarily rule out thermal adaptation. Some modern thermophilic chaperonins also exhibit ATP-dependent oligomerization, and ATPase activity alone may not fully reflect thermal robustness 14 , 34 , 46 . Predicted electrostatic features suggest ancient environmental pressures The electrostatic potential on the surface of a protein is crucial for molecular interactions, and changes in this potential can indicate how proteins adapt to environmental pressures. Our analysis revealed that ACI and ACII, likely the earliest ancestral proteins, have highly negative surface charges (Fig. 8 ). This suggests that ACs in Groups I and II evolved in conditions where negative surface charges were advantageous. For example, these changes could have helped stabilize proteins in acidic or high-salt conditions 47 , or increased thermal stability at high temperatures 48 . Interestingly, the closest modern homolog to ACI is an acidophilic thermophile ( Table I ) 49 , echoing the adaptation of ancestral thioredoxins to acidic environments 50 . Given the proposed evolutionary link between chaperonins and thioredoxins 4 , 8 , this parallel supports the idea that both families may have originated in harsh primordial environments, where electrostatic surface properties were crucial for protein stability. Specifically, positive surface charges could have counteracted proton-driven destabilization in low-pH conditions, while surface charges might have been essential in maintaining solubility and preventing aggregation in high-salinity habitats 47 . As environmental conditions fluctuated over evolutionary time, increasing positive charges may have been selectively favored to balance protein stability and function, highlighting their adaptive versatility. While the electrostatic profiles and modern homologs suggest that ACs may have been adapted to high-temperature, low-pH, or high-salinity environments, these hypotheses remain speculative. We did not experimentally test activity under extreme conditions, and so direct validation of these proposed environmental adaptations will require further research. Energetic trends and environmental adaptations of ancestral chaperonins Trends in energy variation reveal distinct evolutionary paths among the three chaperonin groups, driven by environmental pressures ( Table II ). In Groups I and II, overall stability remained relatively constant. However, we observed a significant increase in hydrogen bonds and a decrease in the entropy term (calculated by FoldX encompassing main-chain and side-chain conformational entropy) 51 , 52 . This suggests that ACs in these groups could have evolved more ordered and rigid structures, to maintain stability under stress. This pattern aligns with observations in thermophilic proteins, which enhance stability through stronger intramolecular forces rather than significant changes in global stability 48 . In Group II, the inferred increase in charge-charge interactions and decrease in ionization energy point to adaptations to high-salt environments, where balancing electrostatic interactions is crucial for solubility and function. Similar adaptations are found in halophilic proteins, which optimize surface charges to prevent aggregation in saline conditions 53 . Conversely, the increasing ionization energy in Group I suggests adaptations to acidic environments, where stabilizing charged residues is essential for maintaining structural integrity – a common characteristic of acidophilic proteins 54 . For Group III ancestors, a notable increase in total stability appears to be driven by strengthened Van der Waals forces and reduced backbone clashes, indicating enhanced hydrophobic packing. This is a well documented adaptation in thermophilic proteins, where compact hydrophobic cores provide resilience to high temperatures 47 , 48 . Additionally, a decrease in polar solvation and increase in nonpolar solvation suggest reduced hydrophilicity. This could reflect adaptations to low-water-activity environments, such as hypersaline, acidic, or thermophilic habitats 48 , 55 – 57 . Together, these trends suggest that environmental pressures were a significant factor in shaping the evolution of chaperonins, driving structural adaptations to extreme conditions. This supports the hypothesis that early chaperonins likely evolved in halo-acidophilic, possibly thermophilic environments, similar to those thought to exist on early Earth 58 , gradually adapting as Earth’s environment became more neutral over time. This perspective differs from previous analyses of ancestral nucleoside diphosphate kinases and ribosomal protein uS8s, which proposed a primitive alkaline habitat 59 . However, these scenarios are not mutually exclusive, and the selective pressures that shaped one protein family may have differed from those acting on another. Nonetheless, previous 60 and recent 61 advances in prebiotic chemistry support the idea that life could have formed in acidic hydrothermal environments. This notion is reinforced by studies on ancestral thioredoxins 50 , which add to the idea that early life flourished in hot, acidic conditions. These remain open questions, inviting further research. Although these structural trends might suggest adaptations to extreme environments, we recognize that our experimental support for this hypothesis is limited, and computational estimates given by programs such as FoldX have known limitations and should be interpreted with caution 62 . Furthermore, ATPase activity assays suggest that the reconstructed proteins exhibit limited activity at temperatures above 50°C, although these two properties are not necessarily correlated. To gain a more complete understanding of the environmental preferences of these ancestral proteins, future studies should examine a broader range of physicochemical conditions, including low-pH and high-salinity. Concluding remarks This study demonstrates that ASR, despite its inherent challenges and the practical limitations of our own implementation, can reveal unexpected structural features in ACs. Our findings support a model where chaperonins evolved gradually from single-ring to double-ring assemblies, with ACII potentially representing an evolutionary intermediate. These structural changes, coupled with shifts in ATP dependence and stability, suggest an overall trend toward greater molecular complexity 45 . Although the energetic patterns we describe were inferred computationally and rely on structural models rather than direct measurements – thus requiring cautious interpretation – they nonetheless indicate adaptations to acidic, high-salinity environments. These environmental pressures may have shaped early protein evolution 58 . While some of these insights remain to be experimentally validated, they align with findings from their closely related thioredoxin family 4 , 8 , 50 . Overall, our work contributes to the growing evidence on how complexity emerges in molecular systems. It also highlights evolutionary patterns that could guide future research into key transitions in early cellular life and the development of modern protein architectures, particularly within the chaperonin family. Methods Phylogenetic analysis and ancestral sequence reconstruction The chaperonin GroEL sequence from E. coli (P0A6F5) was used as query in a blast search on the KEGG (Kyoto Encyclopedia of Genes and Genomes) server ( https://www.genome.jp/tools/blast ). Searches were performed individually for major taxonomic groups to ensure broad representation, and hits were filtered using a similarity threshold (10 − 6 ) 63 . The resulting FASTA sequences were downloaded and curated to generate a manageable and taxonomically-balanced dataset for ancestral sequence reconstruction. We selected 96 sequences based on the following criteria: (1) broad taxonomic coverage, (2) sequence completeness and quality – excluding partial or poorly annotated entries – and (3) removal of redundancy using CD-HIT ( http://weizhong-lab.ucsd.edu/cdhit_suite ) 64 . Multiple sequence alignment was performed with MAFFT (L-INS-i strategy; https://mafft.cbrc.jp/alignment/server ) 65 , followed by manual inspection and curation. Insertions and deletions ( indels ) were carefully reviewed using a conservative approach: clade-specific indels were retained, while individual or sporadic indels were removed. This strategy aimed to reduce alignment noise while preserving phylogenetically informative features. We note that sequence selection and indel treatment can significantly influence phylogenetic tree topology and ancestral sequence inference. Although we did not compare results across different, independently curated, datasets, our curation strategy was designed to reflect the best practices in the field, as recommended in previous studies 66 . ProtTest 3.4 was used to estimate a model of amino acid substitutions 67 . The model chosen, according to the Akaike information criterion (AIC), was the Le Gascuel 2008 model, with gamma distribution and a proportion of invariable sites (LG + I + G model, alpha: 1.40) 68 . The phylogenetic history of the 96 chaperonin sequences was reconstructed using the Bayesian method, implemented in MrBayes 3.2.7 69 . The analysis used two independent Markov-chain Monte Carlo runs, each with two chains, performed over 800,000 generations until convergence was obtained, which was confirmed by the following indicators: (i) the standard deviation of split frequencies was less than 0.01; (ii) stationarity was checked by plotting likelihood scores (lnL) against a number of generations; and (iii) for each parameter in the model, a value of 1.000 for the potential scale reduction factor (PSRF) was obtained. Trees were sampled every 100 generations. Each run produced 8501 trees, from each 6376 were included, totaling 12,752 trees from which a consensus tree with high probabilities at the nodes was obtained. Marginal reconstruction of ancestral sequences was done with PAML 4.9 CodeML, using the LG substitution model with gamma-distributed rates across sites 68 , 70 . The most probable ancestral sequences of the four nodes were selected and modified manually to match the closest modern sequence, as determined by branch length 71 . The sequences corresponded to the last common ancestor nodes of Group I (ACI, for ancestor group I, aged ~ 4.1 Ga), Group II (ACII, ~ 3.9 Ga), Group III (ACIII, divergence time approximately 3.0-2.5 Ga corresponding to divergence times of firmicutes and cyanobacteria), and the last common ancestor of FCB Group (AFCB, ~ 3.0-2.5 Ga). Divergence times were gathered from various sources and synthesized using the TimeTree project 32 Cloning, expression and purification of ancestral enzymes The amino acid sequence of each protein included a C-terminal His-tag and was translated into the corresponding DNA nucleotide sequence, codon-optimized for E. coli using the OptimumGene™ Codon Optimization Analysis and Algorithm (GenScript Biotech, Rijswijk, Netherlands). The optimized genes were synthesized by the GenScript Recombinant Protein Expression Service (GenScript Biotech) and ligated into plasmid pET-30a(+) using the CloneEZ method. Plasmids were cloned, amplified in E. coli DH5α (DE3), and purified from kanamycin-resistant cells using the QIAprep® Miniprep Kit (Qiagen GmbH, Hilden, Germany). The integrity of the plasmid preparations was verified by agarose gel electrophoresis. E. coli BL21 (DE3) cells were transformed with the purified plasmids and selected by kanamycin resistance. Recombinant protein expression was induced with 1 mM IPTG for 4 h at 37°C. After centrifugation, the cell pellet was resuspended in nickel nitrilotriacetic acid (Ni-NTA) binding buffer (NiBB) (20 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid [HEPES] pH 7.4, 20 mM imidazole, 500 mM KCl, 1 mM DTT and 15% glycerol [v/v]) supplemented with a protease inhibitor cocktail (Roche Holding AG, Basel, Switzerland). The resuspended solution was sonicated three times for 1 min each time (cycles of 10 sec on , 50 sec off ), with an amplitude of 50% in a Branson Digital Sonifier 250, and centrifuged at 15.000 × g in a Beckman Coulter ultracentrifuge with a Type 50.2 Ti rotor (40 min at 4°C). The supernatant was filtered (0.45 µm) and loaded onto a Ni-NTA agarose column (HisTrap FF 5 ml, GE Healthcare, Chicago, IL) using a fast protein liquid chromatography (FPLC) apparatus (GE Healthcare). The loaded column was then washed with 5 column volumes of NiBB and eluted with Ni-NTA elution buffer (NiEB) (same as NiBB but with 500 mM imidazole) using a gradient of 50% over 15 min. Fractions (2 ml) were collected and analyzed by SDS-PAGE, and those containing the corresponding protein were pooled and concentrated by centrifugation (4.000 × g, in a Hitachi centrifuge with a R15A rotor, at 4°C) using 50 kDa or 100 kDa cut-off Amicon Ultra 15 filters (Merck Millipore, Darmstadt Germany). The concentrated fractions containing the protein of interest were loaded onto size exclusion chromatography (SEC) Superose® 6 Increase 10/300 GL (GE Healthcare) columns, previously equilibrated in SEC buffer (SECB) (20 mM HEPES pH 7.4, 150 mM KCl, 10% glycerol [v/v]). Proteins were eluted in SECB and fractions (0.5 ml) were analyzed by SDS-PAGE and by negative staining electron microscopy. When necessary, complex formation was induced with 25 mM MgCl 2 and 5 mM ATP 34 . Fractions with proteins forming the typical ring complex were supplemented with 5% glycerol, snap frozen in liquid nitrogen and stored at -20°C. ATPase activity assay The ATP hydrolysis rates of ancestral chaperonins (ACI, ACII, ACIII, and AFCB) and C. hydrogenoformans (UniProt: Q3AF10) were calculated as the amount of phosphate (Pi) released (nanomol/min/nanomol chaperonin) based on the theoretical molecular weight of each oligomeric complex. The theoretical molecular weight was determined from the protein amino acid sequence using ProtParam ( https://web.expasy.org/protparam/ ). A single-ring oligomer was assumed for ACI, whereas a double-ring oligomer was assumed for the other chaperonins. Chaperonin proteins at concentrations of 0.35 µg•µl − 1 or 0.5 µg•µl − 1 were incubated in 50 µl of buffer containing 50 mM HEPES pH 7.4, 150 mM KCl, 5 mM MgCl 2 and 0.5 mM ATP. Reactions without chaperonin served as negative controls, and subtracted from the results. Incubations were carried out on a thermoblock with gentle agitation (300 rpm) across a range of temperatures (30°C, 40°C, 50°C and 60°C). The reaction was stopped with BIOMOL GREEN™ Reagent. Following a 20-minute incubation at room temperature (RT), absorbance at 650 nm was measured using a SpectraMax® iD3 spectrophotometer. The amount of phosphate released was estimated using a standard curve generated from phosphate dilutions ranging from 2 to 0 nmol. Chaperone activity assay with lactate dehydrogenase The chaperone activity of the resurrected chaperonins was assessed as described 72 , with minor modifications. The assay measures the ability of each chaperonin to preserve LDH activity under thermal stress. Enzyme inactivation was induced at 48°C in 50 µl of HEPES buffer (50 mM HEPES, pH 7.4, 150 mM KCl, 5 mM MgCl 2 ) containing 0.1 µM LDH, 0.4 µg•µl − 1 chaperonin, and 1 mM ATP. Reactions without chaperonin served as negative controls. Incubations were performed on a thermoblock with gentle agitation (300 rpm). At each time point, 5 µl of the incubation mixture was transferred to a cuvette containing 495 µl of assay buffer (20 mM HEPES, pH 7.4, 50 mM KCl, 0.3 mM NADH, and 1.6 mM sodium pyruvate). The cuvette was immediately sealed with parafilm and mixed by inversion. The decrease in absorbance at 340 nm, reflecting NADH consumption, was monitored for 3 minutes at RT, with readings taken every 15 seconds. All assays were performed in duplicate. The slope of each reaction was calculated using Microsoft® Excel, and the mean and standard deviation were determined for each sample. Results were normalized to the enzyme activity prior to thermal stress. Sample preparation for cryogenic electron microscopy Samples were vitrified in a Vitrobot Mark IV (FEI, Eindhoven, Netherlands) at 4°C and 100% humidity. A drop of 3 µl of sample was absorbed onto Quantifoil R 2/2 300 mesh and glow-discharged (25 mA, 15 seconds) grids. The force and blotting time were − 2 and 2 s, respectively. Vitrified grids were stored in liquid nitrogen before screening. The vitrified samples were checked, and data from the best sample was acquired in a 200 kV FEI Talos Arctica equipped with a Falcon III direct electron detector at the Spanish National Center for Biotechnology CryoEM facility (CryoEM CNB-CSIC). The images of last common ancestors of Group I and Group III (ACI, ACIII) proteins were acquired at a nominal magnification of ×120000 (corresponding to a pixel size of 0.85 Å/pixel) and the AFCB Group images at ×73000 (corresponding to a pixel size of 1.42 Å/pixel) with a defocus range of -1.2 to -3.0 µm in all samples. The ACII protein was first checked on a 200 kV FEI Talos Arctica at the CNB followed by data acquisition on a FEI Titan Krios electron microscope operated at 300 kV, equipped with a Gatan Quantum K3 Summit direct electron detector at Diamond Light Source (Oxford, UK). Data collection was carried out with a ×130000 nominal magnification (yielding a pixel size of 0.921 Å/pixel) and a defocus range of -1.0 to -2.4 µm. Image processing and three-dimensional reconstruction Image processing of all samples was performed following a similar workflow. All programs used for image processing to obtain the different 3D maps were implemented in Scipion 73 . First, the movies were aligned using MotionCor 74 and the outputs were subjected to CTF determination using Gctf 75 . Particles were automatically picked with Xmipp3 76 and were subjected to several 2D classifications using Relion 2.0 77 and Cryosparc 78 to exclude bad particles and ice contamination. Some of the more superior 2D classes were used as a template to generate an initial model using both CryoSPARC and RANSAC 79 . The initial models were low-pass filtered to 50 Å and used for 3D classifications. The classes with the best structural features were used for the reconstruction of the different chaperonins using Relion 5.0 and CryoSPARC, applying C7 and D8 symmetry for chaperonins ACI and ACII, respectively, and no symmetry (C1) for chaperonins ACIII and AFCB. The resulting maps were visualized with ChimeraX 80 . The resolution of the final maps was estimated by the Fourier shell correlation method, with a cut-off of 0.143 and local resolution was calculated by Xmipp3-MonoRes 81 Model building Models for each AC were generated with the AlphaFold3 server 82 using the sequence of each chaperonin as a reference. The resulting models were docked into each cryo-EM density map by rigid body fitting with the Fit in Map tool of ChimeraX. Subsequently, the models were refined through multiple rounds of PHENIX 1.20.1-4487 83 real-space refinement and manually adjusted using Coot 0.9.8.96 84 to improve structural restraints, including Ramachandran plot outliers, geometry, and rotamer restraints (Supplementary Table III). The restraints used in PHENIX real-space refinement included both standard restraints (bond, angle, planarity, chirality, dihedral, and nonbonded repulsion) and additional restraints (Ramachandran plot, C-beta deviations, rotamer, and secondary structure). The refinement process also combined morphing, simulated annealing, and rigid-body strategies. A local grid search-based fit was incorporated into the refinement strategy to correct side-chain outliers, such as rotamers or regions with poor map fitting. Validation of the final models was done using the phenix.validation cryoem module in PHENIX. FoldX-based stability prediction of AlphaFold3 models Protein stability predictions were performed using FoldX 5.1 52 with AlphaFold3-generated structural models 82 as input. The structural models used for these calculations correspond to the ancestral sequences at the nodes highlighted in Supplementary Fig. 3 . The analysis was conducted via the command-line tool using the Stability function (foldx -c Stability --pdb), which calculates: (1) the total energy (kcal/mol), reflecting overall structural stability; (2) the Gibbs free energy change (ΔG, kcal/mol), representing the energy difference between folded and unfolded states; and (3) individual energy contributions, including backbone hydrogen bonds, sidechain hydrogen bonds, Van der Waals clashes, electrostatics, and solvation energy (polar/apolar components). Default FoldX parameters (pH 7.0, 298 K, 0.05 M ionic strength) were applied without further refinement of the input models. Declarations Data availability Cryo-EM data generated in this study have been deposited in the Electron Microscopy Data Bank under accession codes EMD-54342 for ACI, EMD-54339 for ACII closed-state double ring, EMD-54343 for ACII open-state double ring, EMD-54344 for ACII closed-state single ring, EMD-54345 for ACII open-state single ring, EMD-54340 for ACIII, and EMD-54341 for AFCB, respectively. The associated models have been also deposited in the Protein Data Bank under accession codes 9RWP for ACII closed state double ring, 9RWQ for ACIII and 9RWR for AFCB. All other data generated in this study are provided in the Supplementary Information/Source Data file with this paper. Acknowledgements We thank José Manuel Sánchez Ruiz (Granada University, Spain) and José Berenguer (Autonomous University of Madrid, Spain), for critical insights and discussion. This research was supported by the Spanish Ministry of Science and Innovation and Agencia Estatal de Investigación MCIN/AEI/10.13039/501100011033 and “ESF Investing in your future” through the grants PID2021-126746NB-I00 and RTI2018-094368-B-I00 to V.P., and PID2022-137175NB-I00 through the “Severo Ochoa” Program for Centers of Excellence in R&D (CEX2023-001386-S) to J.M.V. and J.C. The support the grant CaixaResearch Health 2023 (HR23-00837) to J.M.V. is also acknowledged. R.S. is funded by a Ph.D. fellowship from INTA, by the fellowship “Ford-Apadriña la Ciencia”, and by MCIU/AEI/10.13039/501100011033 and FSE+ through the grant PTA2022-022084-I. The authors acknowledge the technical support of the cryoEM CNB-CSIC facility. Author information Authors and Affiliations Centro de Astrobiología (CAB), INTA-CSIC, Torrejón de Ardoz, Madrid, Spain Rita Severino, Luis Sánchez-Pulido, Mercedes Moreno-Paz and Víctor Parro National Center for Biotechnology (CNB), CSIC, Madrid, Spain Jorge Cuéllar, Jorge Gutiérrez-Seijo, Moisés Maestro-López, César Santiago and José María Valpuesta University of Alcalá (UAH), Alcalá de Henares, Madrid, Spain Rita Severino Unidad de Nanobiotecnología, CNB-CSIC-IMDEA Nanociencia Associated Unit, Madrid, Spain José María Valpuesta Contributions Conceived the study, R.S. and V.P. Phylogenetic analysis, ancestral reconstruction, R.S. Cryo-EM, data acquisition, data processing, structural reconstruction, J.C., J.G-S., M.M-L., C.S. Biochemical experiments, R.S., M.M-L., J.G-S., M.M-P. Computer simulations, R.S., L.S-P. Original draft, R.S. Wrote the manuscript, R.S., J.C., J.M.V., V.P. All authors reviewed and approved the final manuscript. Corresponding authors Correspondence to Rita Severino or Jorge Cuéllar . Ethics declarations Competing interests The authors declare no competing interests. References Horwich AL, Fenton WA (2020) Chaperonin-assisted protein folding: a chronologue. Q Rev Biophys 53:1–127 Horovitz A, Reingewertz TH, Cuéllar J (2024) María Valpuesta, J. Chaperonin Mechanisms: Multiple and (Mis)Understood? Annu Rev Biophys 53:53 Stan G, Lorimer GH, Thirumalai D (2022) Friends in need: How chaperonins recognize and remodel proteins that require folding assistance. Front Mol Biosci 9 Rowland SE, Robb FT, Structure (2017) Function and Evolution of the Hsp60 Chaperonins. in Prokaryotic Chaperonins, Heat Shock Proteins, vol 11 (eds. Kumar, C. & Mande, S.) 3–20Springer Nature Singapore. 10.1007/978-981-10-4651-3_1 Llorca O, Galán A, Carrascosa JL, Muga A, Valpuesta JM (1998) GroEL under heat-shock: Switching from a folding to a storing function. J Biol Chem 273:32587–32594 Santra M, Dill KA, de Graff AMR (2018) How Do Chaperones Protect a Cell’s Proteins from Oxidative Damage? Cell Syst 6:743–751e3 Storey JM, Storey KB (2023) Chaperone proteins: universal roles in surviving environmental stress. Cell Stress Chaperones 28:455–466 Dekker C, Willison KR, Taylor WR (2011) On the evolutionary origin of the chaperonins. Proteins Struct Funct Bioinforma 79:1172–1192 Muñoz-Villagrán C et al (2024) The Thioredoxin Fold Protein (TFP2) from Extreme Acidophilic Leptospirillum sp. CF-1 Is a Chaperedoxin-like Protein That Prevents the Aggregation of Proteins under Oxidative Stress. Int J Mol Sci 25 Stroobants S et al (2019) Structure of the Prx6-subfamily 1-Cys peroxiredoxin from sulfolobus islandicus. Acta Crystallogr Sect F Struct Biol Commun 75:428–434 Goemans CV, Vertommen D, Agrebi R, Collet JF (2018) CnoX Is a Chaperedoxin: A Holdase that Protects Its Substrates from Irreversible Oxidation. Mol Cell 70:614–627e7 Bresell A, Persson B (2007) Characterization of oligopeptide patterns in large protein sets. BMC Genomics 8:1–15 An YJ et al (2017) Structural and mechanistic characterization of an archaeal-like chaperonin from a thermophilic bacterium. Nat Commun 8:827 Techtmann SM, Robb FT (2010) Archaeal-like chaperonins in bacteria. Proc. Natl. Acad. Sci. U. S. A. 107, 20269–20274 Pereira JH et al (2012) Mechanism of nucleotide sensing in group II chaperonins. EMBO J 31:731–740 Rebeaud ME, Mallik S, Goloubinoff P, Tawfik DS (2021) On the evolution of chaperones and cochaperones and the expansion of proteomes across the Tree of Life. Proc. Natl. Acad. Sci. U. S. A. 118, e2020885118 Pauling L, Zuckerkandl E (1963) Chemical Paleogenetics. Molecular ‘Restoration Studies’ of Extinct Forms of Life. Acta Chem. Scand. 17 supl., 9–16 Hochberg GKA, Thornton JW (2017) Reconstructing Ancient Proteins to Understand the Causes of Structure and Function. Annu Rev Biophys 46:247–269 Kaçar B (2024) Reconstructing Early Microbial Life. Annu Rev Microbiol 26:56 Gamiz-Arco G et al (2021) Combining Ancestral Reconstruction with Folding-Landscape Simulations to Engineer Heterologous Protein Expression. J Mol Biol 433:167321 Wheeler LC, Lim SA, Marqusee S, Harms MJ (2016) The thermostability and specificity of ancient proteins. Curr Opin Struct Biol 38:37–43 Ingles-Prieto A et al (2013) Conservation of protein structure over four billion years. Structure 21:1690–1697 Harris DF et al (2024) Ancient nitrogenases are ATP dependent. MBio 15:e0127124 Shih PM et al (2016) Biochemical characterization of predicted Precambrian RuBisCO. Nat Commun 7:10382:1–11 Risso VA et al (2015) Mutational studies on resurrected ancestral proteins reveal conservation of site-specific amino acid preferences throughout evolutionary history. Mol Biol Evol 32:440–455 Gaucher EA, Thomson JM, Burgan MF, Benner SA (2003) Inferring the palaeoenvironment of ancient bacteria on the basis of resurrected proteins. Nature 425:285–288 Amritkar K, Cuevas-Zuviría B, Kaçar B (2025) Evolutionary Dynamics of RuBisCO: Emergence of the Small Subunit and its Impact Through Time. Mol Biol Evol 42 Finnigan GC, Hanson-Smith V, Stevens TH, Thornton JW (2012) Evolution of increased complexity in a molecular machine. Nature 481:360–364 Schulz L et al (2022) Evolution of increased complexity and specificity at the dawn of form I Rubiscos. Sci (80-). 378 Severino R et al (2023) Immunoanalytical Approach for Detecting and Identifying Ancestral Peptide Biomarkers in Early Earth Analogue Environments. Anal Chem 95:5323–5330 Villanueva L et al (2021) Bridging the membrane lipid divide: bacteria of the FCB group superphylum have the potential to synthesize archaeal ether lipids. ISME J 15:168–182 Kumar S et al (2022) TimeTree 5: An Expanded Resource for Species Divergence Times. Mol Biol Evol 39:msac174 Chatellier J, Hill F, Foster NW, Goloubinoff P, Fersht AR (2000) From minichaperone to groel 3: Properties of an active single-ring mutant of groel. J Mol Biol 304:897–910 Chaston JJ et al (2016) Structural and Functional Insights into the Evolution and Stress Adaptation of Type II Chaperonins. Structure 24:364–374 Geladopoulos TP, Sotiroudis TG, Evangelopoulos AE (1991) A malachite green colorimetric assay for protein phosphatase activity. Anal Biochem 192:112–116 Mendoza JA, Warren T, Dulin P (1996) The ATPase activity of chaperonin GroEL is highly stimulated at elevated temperatures. Biochem Biophys Res Commun 229:271–274 Jurrus E et al (2018) Improvements to the APBS biomolecular solvation software suite. Protein Sci 27:112–128 Ward LM, Cardona T, Holland-Moritz H (2019) Evolutionary Implications of Anoxygenic Phototrophy in the Bacterial Phylum Candidatus Eremiobacterota (WPS-2). Front Microbiol 10:534180 Cavalier-Smith T, Chao EE (2020) Y. Multidomain ribosomal protein trees and the planctobacterial origin of neomura (eukaryotes, archaebacteria). Protoplasma 257:621–753 Cavalier-Smith T (2006) Rooting the tree of life by transition analyses. Biol Direct 1:1–83 Gupta RS (2004) The phylogeny and signature sequences characteristics of Fibrobacteres, Chlorobi, and Bacteroidetes. Crit Rev Microbiol 30(2):123–143 Bhatt JM et al (2018) Single-Ring Intermediates Are Essential for Some Chaperonins. Front Mol Biosci 5:42 Himiyama T, Oshima M, Uegaki K, Nakamura T (2019) Distinct molecular assembly of homologous peroxiredoxins from Pyrococcus horikoshii and Thermococcus kodakaraensis. J Biochem 166:1:89–95 Gribaldo S, Brochier-Armanet C (2006) The origin and evolution of Archaea: A state of the art. Philos Trans R Soc B Biol Sci 361:1007–1022 Pillai AS, Hochberg GKA, Thornton JW (2022) Simple mechanisms for the evolution of protein complexity. Protein Sci 31 Andra S, Frey G, Jaenicke R, Stetter KO (1998) The thermosome from methanopyrus kandleri possesses an NH4+-dependent ATPase activity. Eur J Biochem 255:93–99 Reed CJ, Lewis H, Trejo E, Winston V, Evilia C (2013) Protein adaptations in archaeal extremophiles. Archaea 2013:37327 Vieille C, Zeikus GJ, Hyperthermophilic Enzymes (2001) Sources, Uses, and Molecular Mechanisms for Thermostability. Microbiol Mol Biol Rev 65:1–43 Tsuruoka N et al (2003) Alicyclobacillus sendaiensis sp. nov., a novel acidophilic, slightly thermophilic species isolated from soil in Sendai, Japan. Int J Syst Evol Microbiol 53:1081–1084 Perez-Jimenez R et al (2011) Single-molecule paleoenzymology probes the chemistry of resurrected enzymes. Nat Struct Mol Biol 18:592–596 Schymkowitz J et al (2005) The FoldX web server: An online force field. Nucleic Acids Res 33:W382–W388 Delgado J et al (2025) FoldX force field revisited, an improved version. Bioinformatics 41:btaf064 Madern D, Ebel C, Zaccai G (2000) Halophilic adaptation of enzymes. Extremophiles 4:91–98 Garcia-Moreno B (2009) Adaptations of proteins to cellular and subcellular pH. J Biol 8 Kraml J, Kamenik AS, Waibl F, Schauperl M, Liedl KR (2019) Solvation Free Energy as a Measure of Hydrophobicity: Application to Serine Protease Binding Interfaces. J Chem Theory Comput 15:5872–5882 Benison KC, O’Neill WK, Blain D, Hallsworth JE (2021) Water Activities of Acid Brine Lakes Approach the Limit for Life. Astrobiology 21:729–740 Tadeo X et al (2009) Structural basis for the aminoacid composition of proteins from halophilic archea. PLoS Biol 7 Sugisaki R, Horiuchi Y, Adachi M, Yamasaki K, Sugitani K (1995) Acid character of Archean ocean waters revealed by 3.3 Ga-old ferruginous chert compositions. Proc. Japan Acad 71(B), 170–174 Fujikawa T, Sasamoto T, Zhao F, Yamagishi A, Akanuma S (2024) Comparative analysis of reconstructed ancestral proteins with their extant counterparts suggests primitive life had an alkaline habitat. Sci Rep 14 Kitadai N, Maruyama S (2018) Origins of building blocks of life: A review. Geosci Front 9:1117–1153 Šponer JE et al (2024) Phosphoric acid salts of amino acids as a source of oligopeptides on the early Earth. Commun Chem 7 Buß O, Rudat J, Ochsenreither K (2018) FoldX as Protein Engineering Tool: Better Than Random Based Approaches? Comput Struct Biotechnol J 16:25–33 Kanehisa M, Goto SKEGG (2000) Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 28:27–30 Huang Y, Niu B, Gao Y, Fu L, Li W (2010) CD-HIT Suite: A web server for clustering and comparing biological sequences. Bioinformatics 26:680–682 Katoh K, Rozewicki J, Yamada K (2018) D. MAFFT online service: Multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform 20:1160–1166 Ross CM, Foley G, Boden M, Gillam EMJ (2022) Enzyme Engineering Methods and Protocols. Methods in Molecular Biology, vol 2397. Humana Darriba D, Taboada GL, Doallo R, Posada D (2011) ProtTest 3: Fast selection of best-fit models of protein evolution. Bioinformatics 27:1164–1165 Le SQ, Gascuel O (2008) An improved general amino acid replacement matrix. Mol Biol Evol 25:1307–1320 Hall BG (2006) Simple and accurate estimation of ancestral protein sequences. Proc. Natl. Acad. Sci. U. S. A. 103, 5431–5436 Yang Z, Paml (1997) A program package for phylogenetic analysis by maximum likelihood. Bioinformatics 13:555–556 Boucher JI, Jacobowitz JR, Beckett BC, Classen S, Theobald DL (2014) An atomic-resolution view of neofunctionalization in the evolution of apicomplexan lactate dehydrogenases. Elife (2014) Hristozova N, Tompa P, Kovacs D (2016) A novel method for assessing the chaperone activity of proteins. PLoS ONE 11:1–14 de la Rosa-Trevín JM et al (2016) Scipion: A software framework toward integration, reproducibility and validation in 3D electron microscopy. J Struct Biol 195:93–99 Zheng SQ et al (2017) MotionCor2: Anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat Methods 14:331–332 Zhang K, Gctf (2016) Real-time CTF determination and correction. J Struct Biol 193:1–12 Vargas J et al (2013) Particle quality assessment and sorting for automatic and semiautomatic particle-picking techniques. J Struct Biol 183:342–353 Fernandez-Leiro R, Scheres SH (2017) W. A pipeline approach to single-particle processing in RELION. Acta Crystallogr Sect D Struct Biol 73:496–502 Punjani A, Rubinstein JL, Fleet DJ, Brubaker MA (2017) CryoSPARC: Algorithms for rapid unsupervised cryo-EM structure determination. Nat Methods 14:290–296 Vargas J, Álvarez-Cabrera AL, Marabini R, Carazo JM, Sorzano CO (2014) Efficient initial volume determination from electron microscopy images of single particles. Bioinformatics 30:2891–2898 Pettersen EF et al (2021) UCSF ChimeraX: Structure visualization for researchers, educators, and developers. Protein Sci 30:70–82 Vilas JL et al (2018) MonoRes: Automatic and Accurate Estimation of Local Resolution for Electron Microscopy Maps. Structure 26:337–344e4 Abramson J et al (2024) Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630:493–500 Adams PD et al (2010) PHENIX: A comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr Sect D Biol Crystallogr 66:213–221 Emsley P, Lohkamp B, Scott WG, Cowtan K (2010) Features and development of Coot. Acta Crystallogr Sect D Biol Crystallogr 66:486–501 Tables Table I . Best NCBI BLAST Matches for Resurrected Ancestral Chaperonin Sequences Best hits (nr-NCBI Database) Estimated age (Ga) Identity Taxon ACI – Last Common Ancestor of Group I, GroEL 4.1 60% Alicyclobacillus sendaiensis (WP_062305661.1) ACII – Last Common Ancestor of Group II, thermosome 3.9 64% Thermococcus alcaliphilus (WP_252742870.1) ACIII – Last Common Ancestor of Group III, thermosome-like >3.0 67% Thermosinus carboxydivorans (WP_007289467.1) AFCB – Last Common Ancestor of FCB Group, GroEL ~3.0-2.5 81% Rhodothermaceae bacterium (GIV58090.1) Table II . Correlation between folding energies and ancestrality, for each group Group I Group II Group III FoldX energy terms -0.44 0.05 ▲ 0.54 Total stability ▲ 0.94 ▲ 0.90 0.43 Backbone hydrogen bonds ▲ 0.77 ▲ 0.54 -0.17 Side-chain hydrogen bonds 0.11 0.46 ▲ 0.63 Van der Waals 0.13 ▲ 0.70 -0.26 Electrostatic (charge-charge) 0.11 -0.13 ▼-0.52 Polar solvation -0.07 0.47 ▲ 0.55 Nonpolar solvation 0.41 -0.47 0.15 Van der Waals clashes -0.42 ▼-0.71 -0.44 Side-chain entropy ▼-0.86 ▼-0.50 -0.41 Main-chain entropy ▼-0.60 -0.47 ▲ 0.86 Torsion energy -0.25 0.03 ▼-0.51 Backbone Van der Waals clashes 0.12 -0.29 ▼-0.68 Helix dipole effects ▲ 0.59 ▼-0.51 0.41 Ionization energy ▲ – significant positive correlation (> 0.50) ▼ – negative significant correlation (< -0.50) Additional Declarations There is NO Competing Interest. 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Severino","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-9102-6270","institution":"Centro de Astrobiología (INTA-CSIC)","correspondingAuthor":true,"prefix":"","firstName":"Rita","middleName":"","lastName":"Severino","suffix":""},{"id":495610688,"identity":"44511188-3771-4cbc-9c02-3bab577e90d8","order_by":1,"name":"Jorge Cuellar","email":"","orcid":"https://orcid.org/0000-0002-7789-807X","institution":"Centro Nacional de Biotecnología","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Cuellar","suffix":""},{"id":495610689,"identity":"6e4e8c5a-7d39-416e-aa74-7111970648a4","order_by":2,"name":"Jorge Gutiérrez-Seijo","email":"","orcid":"https://orcid.org/0009-0000-9045-8282","institution":"National Center for Biotechnology (CNB), CSIC","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Gutiérrez-Seijo","suffix":""},{"id":495610690,"identity":"16e23288-1229-4b67-9e51-1d50fa1201d9","order_by":3,"name":"Moisés Maestro-López","email":"","orcid":"https://orcid.org/0000-0002-7955-9135","institution":"Centro Nacional de Biotecnología","correspondingAuthor":false,"prefix":"","firstName":"Moisés","middleName":"","lastName":"Maestro-López","suffix":""},{"id":495610691,"identity":"4e5b73ff-6028-4b20-9685-373695445988","order_by":4,"name":"Luis Sánchez-Pulido","email":"","orcid":"","institution":"Centro de Astrobiología (CAB), INTA-CSIC","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"","lastName":"Sánchez-Pulido","suffix":""},{"id":495610692,"identity":"699525f9-fc22-460c-a65d-73cf0ff7fcd2","order_by":5,"name":"César Santiago","email":"","orcid":"https://orcid.org/0000-0002-5149-1722","institution":"Centro Nacional de Biotecnología (CSIC)","correspondingAuthor":false,"prefix":"","firstName":"César","middleName":"","lastName":"Santiago","suffix":""},{"id":495610693,"identity":"37806b48-e2ca-4198-83cc-c40b5439d487","order_by":6,"name":"Mercedes Moreno-Paz","email":"","orcid":"https://orcid.org/0000-0003-1245-3253","institution":"Centro de Astrobiología","correspondingAuthor":false,"prefix":"","firstName":"Mercedes","middleName":"","lastName":"Moreno-Paz","suffix":""},{"id":495610694,"identity":"3745af36-008d-46ab-b8ba-ff79b5a26d57","order_by":7,"name":"José Valpuesta","email":"","orcid":"https://orcid.org/0000-0001-7468-8053","institution":"CNB, CSIC","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"","lastName":"Valpuesta","suffix":""},{"id":495610695,"identity":"cd6bba0a-eb82-438b-b9f1-6653102770d3","order_by":8,"name":"Victor Parro","email":"","orcid":"https://orcid.org/0000-0003-3738-0724","institution":"Centro de Astrobiología (CAB), INTA-CSIC","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"","lastName":"Parro","suffix":""}],"badges":[],"createdAt":"2025-08-01 10:20:47","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7270162/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7270162/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1093/molbev/msaf314","type":"published","date":"2025-11-28T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88514084,"identity":"293d9fc4-9820-4df9-bed9-cf8ab2789005","added_by":"auto","created_at":"2025-08-07 08:34:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34746,"visible":true,"origin":"","legend":"\u003ch3\u003eEvolutionary history of prokaryotic chaperonins.\u003c/h3\u003e\n\u003cp\u003eHypothetical evolutionary trajectory of ancestral chaperonins from single- to double-ring structures. Nodes ACI (single-ring), ACII (single- and double-ring), ACIII (double-ring) and AFCB (double-ring) are shown. Divergence times are approximate and based on data from the TimeTree project\u003csup\u003e26\u003c/sup\u003e. H – Hadean.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/662341c4bb9f3745b7a0c6eb.jpg"},{"id":88514085,"identity":"fa60dd4a-dd80-432b-886c-326434a985de","added_by":"auto","created_at":"2025-08-07 08:34:30","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":87255,"visible":true,"origin":"","legend":"\u003ch3\u003eCryo-EM structure of ACI.\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Top and side view of the 3D reconstruction of ACI (cornflower blue) at 5.4 Å resolution (EMD-54342). \u003cstrong\u003eb \u003c/strong\u003eDocking of the ACI atomic model, generated by AlphaFold3, into the ACI 3D reconstruction.\u003cstrong\u003e c \u003c/strong\u003eConservation of residues R460, D461, A463, and E464 in ACI (blue) compared with the \u003cem\u003eE. coli\u003c/em\u003esingle-ring mutant (SR1), where these residues are present. By contrast, these residues are absent in \u003cem\u003eE. coli\u003c/em\u003e GroEL (yellow). The presence of these residues in ACI prevents the formation of the inter-subunit interface, and thus disrupts the double-ring formation.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/b19b34d929b76ee8c41be85c.jpg"},{"id":88515101,"identity":"c0d91ebd-1395-463c-af5e-9eb4b3f92174","added_by":"auto","created_at":"2025-08-07 08:42:30","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":71870,"visible":true,"origin":"","legend":"\u003ch3\u003eCryo-EM structure of the ACII double and single rings\u003cstrong\u003e.\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003ea-b \u003c/strong\u003eLeft: Top and side view of the 3D reconstruction of ACII in a closed (a) (EMD-54344) and open (b) (EMD-54345) single-ring conformation (yellow). Right: Docking of the ACII atomic model, generated by AlphaFold3, into the 3D reconstruction of the open (a) and closed (b) ACII single ring. \u003cstrong\u003ec\u003c/strong\u003e Top, side, and tilted view of the 3D reconstruction of ACII in a double-ring shape (purple) at 3.6 Å resolution (EMD-54339). \u003cstrong\u003ed \u003c/strong\u003eDocking of the ACII atomic model, generated by AlphaFold3, into the 3D-reconstruction of the ACII double-ring (PDB 9RWP).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/c82709706c424db666a7d858.jpg"},{"id":88514087,"identity":"7a35a5a4-8cf0-4d29-8e9b-4e3ab8c2b3f8","added_by":"auto","created_at":"2025-08-07 08:34:30","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":122525,"visible":true,"origin":"","legend":"\u003ch3\u003eStructural comparison of ACII with GroEL and CCT.\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e 3D reconstructions in two orthogonal orientations of \u003cem\u003eleft\u003c/em\u003eGroEL-GroES complex (Group I chaperonin); \u003cem\u003ecenter\u003c/em\u003eACII; and \u003cem\u003eright\u003c/em\u003e CCT (group II chaperonin). The upper row shows top views, while the lower row displays the side views. The complexes are color-coded: red and cyan for \u003cem\u003eE. coli\u003c/em\u003eGroEL (PDB: 8WUX), purple for ACII (PDB: 9RWP), and blue for CCT (PDB ID: 8SHG). \u003cstrong\u003eb \u003c/strong\u003eStructural analysis of ACII and CCT. The two views depict the root-mean-square deviation (RMSD) comparison between the ACII subunit and CCT5 of the CCT complex, with a color gradient indicating structural differences. \u003cstrong\u003ec \u003c/strong\u003eThree different views highlighting differences in the atomic interactions within the apical regions of ACII (pink) and CCT (blue). The top panel shows the tip of the helical protrusion, the middle panel displays the base of the helical protrusion, and the bottom panel focuses on the apical domain helix. Orange residues represent salt bridges, while purple residues indicate hydrogen bonds.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/b2a3cf025029486b96a23377.jpg"},{"id":88514088,"identity":"e233362f-3d1f-487d-ab8b-1156e5a5eefe","added_by":"auto","created_at":"2025-08-07 08:34:30","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":90142,"visible":true,"origin":"","legend":"\u003ch3\u003eCryo-EM structure of ACIII.\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Top, side, and tilted view of the 3D reconstruction of ACIII (light green) at 3.2 Å resolution (EMD-54340). \u003cstrong\u003eb \u003c/strong\u003eDocking of the ACIII atomic model, generated by AlphaFold3, into the ACIII 3D reconstruction (PDB: 9RWQ). Note that only the equatorial domains were modeled.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/f97a5dfccdaac830d0214ef0.jpg"},{"id":88515105,"identity":"f9c5b45a-7fef-4589-9d39-d4570a06037f","added_by":"auto","created_at":"2025-08-07 08:42:30","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":142417,"visible":true,"origin":"","legend":"\u003ch3\u003eCryo-EM structure of AFCB.\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Top and side view of the 3D reconstruction of AFCB (light steel blue) at 3.5 Å resolution (EMD-54341). \u003cstrong\u003eb \u003c/strong\u003eDocking of the \u003cem\u003eE. coli\u003c/em\u003e GroEL atomic model (PDB: 8WUX) into the AFCB 3D-reconstruction.\u003cstrong\u003e c \u003c/strong\u003eDocking of the AFCB atomic model, generated by AlphaFold3, into the AFCB 3D-reconstruction (PDB: 9RWR).\u003cstrong\u003e d \u003c/strong\u003eConservation of L233, L236 and V263 as key residues for interaction with the cochaperonin GroES in AFCB (purple) and \u003cem\u003eE. coli\u003c/em\u003eGroEL (yellow).\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/393e130176501158ffd690fc.jpg"},{"id":88516496,"identity":"8c6f5e04-f0b8-488b-98a7-f5c8cf6582fc","added_by":"auto","created_at":"2025-08-07 08:58:30","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":48430,"visible":true,"origin":"","legend":"\u003ch3\u003eChaperonin activity assays.\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e ATP hydrolysis activity: Average ± SD (n=3) phosphate released by chaperonins at 30°C, 40°C, 50°C, and 60°C, normalized to control without chaperonin. \u003cstrong\u003eb\u003c/strong\u003eThermal protection assay: Average ± SD (n=2) activity of lactate dehydrogenase (LDH) after heat stress (48°C) in the presence of ancestral (ACI, ACII, ACIII, AFCB) and modern (E. coli – \u003cem\u003eEscherichia coli\u003c/em\u003e, C. hyd. – \u003cem\u003eCarboxydothermus hydrogenoformans\u003c/em\u003e) chaperonins, normalized to the activity of LDH alone before heat stress.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/6cd427da9c9aa68db21151f9.jpg"},{"id":88514098,"identity":"5baf2d1f-ab41-465d-8111-48f3567c0e31","added_by":"auto","created_at":"2025-08-07 08:34:30","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":53071,"visible":true,"origin":"","legend":"\u003ch3\u003eStructural and electrostatic potential of ancestral chaperonins.\u003c/h3\u003e\n\u003cp\u003eThe distribution of the electrostatic potentials calculated with the APBS method, implemented in PyMol (http://www.pymol.org/pymol), on the molecular surface of AlphaFold3-generated structural models of ACI, ACII, ACIII and AFCB chaperonins. Color-coding scale ranges from most negative potential (red) to most positive potential (blue).\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/7d81922be3cbc4940a024c85.jpg"},{"id":99819179,"identity":"dbf07f6a-0265-4e8f-ab93-e8da2f4ee586","added_by":"auto","created_at":"2026-01-08 15:05:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1921338,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/062edb3a-ec6c-4783-8860-9555d1ce7817.pdf"},{"id":88514089,"identity":"318266d1-adb4-4eba-9015-97df62883975","added_by":"auto","created_at":"2025-08-07 08:34:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":7260653,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7270162/v1/36a10225cebada9dabe07ac4.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Structural Transitions in Ancient Chaperonins Illustrate Pathways to Protein Complexity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProtein folding is a cornerstone of cellular function and overall organismal health, as misfolded or aggregated proteins can cause various cellular malfunctions. At the core of this process are a large group of proteins known as molecular chaperones. Among them, chaperonins (also known as Hsp60 chaperones) are a ubiquitous family across all life kingdoms. These large, barrel-shaped complexes act as molecular machines, providing a protected environment for newly synthesized proteins to fold efficiently, a critical aspect of protein homeostasis\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Beyond folding, chaperonins also defend against stress (e.g., temperature fluctuations, oxidative stress, or chemical exposure) by preventing aggregation and assisting in refolding misfolded proteins\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eChaperonins likely evolved from a multifunctional ancestor within the thioredoxin superfamily, specifically a peroxiredoxin-like protein with both antioxidant and chaperone activities\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. This dual functionality persists in modern thioredoxin-domain containing \u003cem\u003echaperedoxins\u003c/em\u003e (which associate with GroEL \u003cem\u003ein vivo\u003c/em\u003e) and peroxiredoxins, highlighting their role in shielding proteins and DNA from oxidative and thermal stress\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. This evolutionary origin suggests that extreme environmental pressures (e.g., high temperature, acidity, variable salinity) shaped early chaperonins. The widespread presence and persistence of chaperonins and thioredoxins in bacterial genomes, often under positive selection, underscores their evolutionary importance and adaptability\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAll chaperonin monomers share a common three-domain structure (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e): an apical domain involved in substrate recognition, an equatorial domain containing the ATP-binding site that drives the conformational changes that occur during the chaperonin functional cycle, and an intermediate domain linking the two by relaying signals. Despite this conserved framework (\u003cb\u003eSupplementary Fig.\u0026nbsp;1a\u003c/b\u003e), chaperonins diverge into three structurally distinct groups (Group I-III) based on their unique architecture and phylogeny\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. This structural diversity raises intriguing questions about their evolutionary origins, including how their common ancestor emerged and how they diverged.\u003c/p\u003e\u003cp\u003eGroup I chaperonins, found in bacteria and eukaryotic organelles (e.g., mitochondria and chloroplasts), are exemplified by the well-studied GroEL/GroES system of \u003cem\u003eEscherichia coli\u003c/em\u003e. GroEL consists of two stacked rings, each comprising seven identical subunits (~\u0026thinsp;60 kDa), while GroES (~\u0026thinsp;10 kDa) forms a homoheptamer that caps the GroEL folding chamber, acting as a cochaperonin. Group II chaperonins, present in archaea and the eukaryotic cytosol (e.g., the thermosome in archaea and the CCT/TRiC complex in eukaryotes), feature a built-in \"lid\" mechanism, eliminating the need for a separate cochaperonin. Group II chaperonins have evolved from rings composed of 1\u0026ndash;3 different subunits in the archaeal thermosome, to 8 distinct subunits in the eukaryotic CCT (CCT1-CCT8)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Group III chaperonins, found in some bacteria, resemble Group II but lack the nucleotide-sensing loop present in Groups I and II\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e (\u003cb\u003eSupplementary Fig.\u0026nbsp;1b\u003c/b\u003e). This conserved amino acid sequence directly influences the rate of nucleotide hydrolysis, thereby controlling the timing of the folding cycle. The nucleotide-sensing loop undergoes conformational changes that regulate the opening and closing of the chaperonin rings and facilitates communication by transmitting ATP hydrolysis signals between subunits\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The structural differences between these groups suggest different evolutionary paths, yet their shared function and homology indicate a common ancestral origin\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe evolutionary relationships between these groups remain unresolved. Some researchers propose that Group III chaperonins represent an ancient form from which Groups I and II originated, with GroES possibly arising from the excision of the lid region of a Group III chaperonin\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Others argue that Group III chaperonins emerged later, possibly through horizontal gene transfer from an ancestral archaeon to a bacterial Firmicute\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. These competing hypotheses highlight the complexity of chaperonin evolution and the need for new approaches to unravel their history.\u003c/p\u003e\u003cp\u003eAncestral Sequence Reconstruction (ASR), first proposed in 1963 by Pauling and Zuckerkandl\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, is a powerful tool to address these questions. By inferring the sequences of ancient chaperonins and then \"resurrecting\" them in the laboratory, we can gain insights into the structural and functional properties of these molecular machines in early life\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. ASR followed by protein production, also known as \u0026ldquo;protein resurrection\u0026rdquo; (PR), has been successfully applied to other ancient proteins, revealing trends such as increasing promiscuity, greater conformational diversity, higher thermal stability, and improved heterologous expression\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. For example, ASR studies of ancient thioredoxins, nitrogenases, β-lactamases, V-ATPases, elongation factor Tu, and RuBisCO, have provided valuable insights into the evolution of protein complexity and function\u003csup\u003e\u003cspan additionalcitationids=\"CR23 CR24 CR25 CR26 CR27 CR28\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this study, we apply ASR-PR to chaperonins to explore their evolutionary origins and structural diversification. By rebuilding ancestral chaperonin (AC) sequences and examining their oligomeric structures, we aim to answer key questions: which group of chaperonins evolved first, and how did the structural differences between Groups I, II, and III emerge over evolutionary time? Beyond shedding light on chaperonin evolution, these findings are expected to offer insights into how early life may have adapted to extreme environments on Earth and potentially on other planets\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eReconstruction and characterization of ancestral chaperonins\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo better understand the evolutionary history of chaperonins \u0026ndash; one of the oldest protein families found across of all life forms \u0026ndash; we reconstructed their phylogenetic history using 96 representative prokaryotic chaperonin sequences (\u003cb\u003eSupplementary Fig.\u0026nbsp;2\u003c/b\u003e). In the absence of an outgroup, the precise location of the Last Unknown Common Ancestor (LUCA) cannot be identified, although it is reasonable to assume that it is situated somewhere on the branch connecting bacterial and archaeal populations. We selected several AC nodes for PR, including the last common ancestors of Group I (ACI), Group II (ACII), and Group III (ACIII), along with the ancestor of the Fibrobacteres-Chlorobi-Bacteroidetes (FCB) Group (AFCB) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cb\u003eSupplementary Fig.\u0026nbsp;2\u003c/b\u003e). The FCB Group is notable for being the only known prokaryotic group capable of synthesizing both bacterial and archaeal membrane lipids. This suggests that LUCA might have had mixed archaeal/bacterial membranes, possibly a remnant from before bacteria and archaea diverged\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The predicted AC sequences showed a sequence identity of 60\u0026ndash;81% when compared with modern homologs, and were dated using data from the TimeTree project\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e (\u003cb\u003eTable I\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e BL21 (DE3) cells were transformed with plasmids encoding four ancestral sequences, and the recombinant proteins were expressed and purified as described in Methods (\u003cb\u003eSupplementary Fig.\u0026nbsp;4\u003c/b\u003e). We first studied how these purified AC proteins assembled using transmission electron microscopy. ACI formed a 7-subunit single-ring oligomer, but only in the presence of ATP-Mg2+. ACII formed a heterogeneous mixture of 8-subunit oligomers, including both single and double rings, even without ATP. However, adding ATP-Mg\u0026sup2;\u003csup\u003e+\u003c/sup\u003e increased the overall number of oligomers compared with individual monomers. ACIII assembled as 8-subunit double rings without ATP-Mg\u0026sup2;\u003csup\u003e+\u003c/sup\u003e, and AFCB formed 7-subunit double rings (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStructural characterization of ancestral chaperonins by cryoelectron microscopy\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo investigate the structural details of the new proteins, we used cryoelectron microscopy (CryoEM) to determine their high-resolution 3D structures. We vitrified aliquots of the purified ACs, and the best grids were used for CryoEM data acquisition using the parameters described in \u003cb\u003eSupplementary Table I\u003c/b\u003e. Image processing and subsequent 3D reconstruction procedures are detailed in the Methods section and \u003cb\u003eSupplementary Figs.\u0026nbsp;5\u0026ndash;8\u003c/b\u003e. The 2D classification of particles of the four ACs revealed that whereas ACI and AFCB formed heptameric rings, ACII and ACIII assembled into octameric rings, mirroring their modern counterparts (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Regarding their overall structure, a typical chaperonin double-ring structure was observed for ACIII and AFCB. By contrast, ACI showed single-ring structures, and ACII displayed a mixture of double rings (majority) and single rings.\u003c/p\u003e\u003cp\u003eDetailed 3D analysis of ACI confirmed its assembly into stable, single heptameric rings (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea \u003cb\u003eand Supplementary Fig.\u0026nbsp;5\u003c/b\u003e). While the \u0026ldquo;open state\u0026rdquo; structure provided valuable insights, its resolution was likely limited by the inherent structural flexibility of the chaperonin, particularly in the apical domain. This flexibility is evident in the lidless ACI map (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea \u003cb\u003eand Supplementary Fig.\u0026nbsp;5\u003c/b\u003e), which shows well-resolved α-helices in the equatorial domain but less defined features in the apical and intermediate domains (EMD-54342). Although these regions are typically harder to resolve, the increased dynamics of the apical domains might have been crucial in the early evolution of Group I chaperonins. To further investigate the ACI single-ring architecture, we compared its sequence and structure with the well-characterized \u003cem\u003eE. coli\u003c/em\u003e single-ring mutant (SR1)\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Four amino acid substitutions (R452E, E461A, S463A, and V464A) distinguish SR1 from canonical \u003cem\u003eE. coli\u003c/em\u003e GroEL, and are known to disrupt double-ring assembly\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). We found three of these four substitutions in ACI (E\u0026rarr;D, S\u0026rarr;A, and V\u0026rarr;E), which likely interfere with the inter-subunit interfaces needed for double-ring formation. Ancestral sequence reconstruction for these four residues yielded high posterior probabilities: R (0.89), D (0.95), A (0.82), and E (0.48). Their evolutionary trajectories further highlighted dynamic shifts (\u003cb\u003eSupplementary Table II\u003c/b\u003e): the probability of residue R increases in probability from 0.89 to 1 by node 121, indicating fixation; Residue D, initially highly probable (0.95), decreases to 0.75 at node 108 and is gradually replaced by E from node 113, reaching fixation by node 128; Residue A decreases in probability to 0.44 at node 104, and is then replaced by S from node 109, becoming fixed by node 121; Residue E increases in probability up to node 107, but is ultimately replaced by V with probability 1 at node 108.\u003c/p\u003e\u003cp\u003eACII was purified as a mixture of monomers and oligomers, and the presence of ATP triggered the typical conformational changes typical of chaperonins, transitioning between open and closed states. The 2D and 3D analysis of the particles revealed both single- and double-ring structures in both open and closed configurations \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eb \u003cb\u003eand Supplementary Fig.\u0026nbsp;6\u003c/b\u003e). However, only the closed double-ring structure, the most abundant oligomeric state (35% of all particles), yielded a map with sufficient resolution for atomic modeling (\u003cb\u003eSupplementary Fig.\u0026nbsp;6c\u003c/b\u003e) (PDB 9RWP). When comparing this structure with modern chaperonins such as \u003cem\u003eE. coli\u003c/em\u003e GroEL (Group I) or the group II eukaryotic chaperonin CCT (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e), we found that ACII possesses a built-in helical lid protrusion, similar to CCT. This feature allows ACII to close its cavity without needing a separate co-chaperonin like GroES, which GroEL requires. This structural element suggests that ACII developed an early mechanism for cavity closure. This mechanism is independent of a GroES-like co-chaperonin and predates the more complex mechanisms seen in modern Group II chaperonins, with CCT being the most complex example (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAn interesting observation was that the closed conformation of ACII is less tightly locked than that of CCT (compare central and right structures in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, respectively), indicating distinct closure mechanisms between the two chaperonins. To understand the atomic-level changes that drive CCT-like closure, we first analyzed the structural changes observed within the apical, intermediate, and equatorial domains of ACII and CCT subunits. By calculating the root-square-mean deviation (RSMD), which measures differences in protein backbones, we found that the main changes occur in the arrangement of the apical region, including the intermediate domain (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Further examination of the intra-subunit interactions highlighted several notable aspects. In the built-in lid, CCT contacting-subunits exhibited somewhat different interactions. For example, a salt bridge forms between H312 of CCT5 (the CCT subunit most similar to ACII in the apical region) and E330 of CCT2. These interactions are further stabilized by hydrogen bonds between H312 and Q316 of CCT5 with T334 and E330 of CCT2, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). In ACII, a similar salt bridge exists between H299 and E334. However, due to a lack of interactions in the tip of the apical region, E334 forms a stronger interaction with K303. The positive charge of K303 allows for an additional interaction, similar to that observed with Q316 of CCT5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). In the central part of the helical protrusion, CCT forms strong interactions between K282 of CCT5 and D336 of CCT2, generating a salt bridge in the middle of the helix. At the end of the protrusion, these interactions are reinforced by the hydroxyl group of Y274, which interacts with K74 and E271 of CCT2. In ACII, these interactions are absent. Only a hydrogen bond is formed by P258 and Q267 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, \u003cb\u003eleft\u003c/b\u003e). Additionally, potential repulsive forces along the helical protrusion in ACII further support this (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, \u003cb\u003eright\u003c/b\u003e). Altogether, these observations suggest that while ACII possesses a built-in lid that reduces reliance on a GroES-type cochaperonin for cavity closure, the resulting closure is less complete than that of CCT subunits, where total sealing prevents solute entry or exit.\u003c/p\u003e\u003cp\u003eIn the case of ACIII, oligomeric structures were visible in the absence of ATP, and they all formed double-ring structures (\u003cb\u003eSupplementary Fig.\u0026nbsp;7\u003c/b\u003e). The structure obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e) (PDB 9RWQ) resembles that of the modern thermosomes\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e), although the flexibility observed in the apical domains (\u003cb\u003eSupplementary Fig.\u0026nbsp;7c\u003c/b\u003e) prevented us from modeling these regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFinally, our structural characterization of AFCB (Ancestral FCB Chaperonin) revealed a strikingly modern architecture (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003e \u003cb\u003eand Supplementary Fig.\u0026nbsp;8\u003c/b\u003e). There was no need for the addition of ATP to generate a stable, homogeneous population of double-ring oligomers (\u003cb\u003eSupplementary Fig.\u0026nbsp;8a and b\u003c/b\u003e). This enabled us to obtain a 3.4 \u0026Aring; resolution map (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003ea) and build the corresponding atomic model (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003ec) (PDB: 9RWR). Unsurprisingly, AFCB closely resembles \u003cem\u003eE. coli\u003c/em\u003e GroEL, sharing a 71% sequence identity (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). Although resurrecting the GroES-type cochaperonin was beyond the scope of this study, an analysis of key residues involved in the GroEL-GroES interaction showed that all three essential residues are conserved in AFCB (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). This strongly suggests that AFCB likely interacts with a GroES-type cochaperonin, hinting at the co-evolution of the chaperonin and its cochaperonin counterpart within the FCB lineage.\u003c/p\u003e\u003cp\u003e\u003cem\u003eFunctional evaluation of ancestral chaperonins\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWe next compared the activity of ACs with that of modern \u003cem\u003eE. coli\u003c/em\u003e (Group I, Uniprot: P0A6F5) and \u003cem\u003eCarboxydothermus hydrogenoformans\u003c/em\u003e (Group III, UniProt: Q3AF10), expressed and purified under identical conditions. ATPase activity was monitored in 10\u0026deg;C increments from 30\u0026deg;C and 60\u0026deg;C using BIOMOL GREEN\u0026trade; Reagent, which detects phosphate released during ATP hydrolysis (see Methods)\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). The Group III chaperonin from \u003cem\u003eC. hydrogenoformans\u003c/em\u003e, a thermophile, showed the highest rate of ATP hydrolysis, followed by AFCB. The remaining chaperonins \u003cem\u003eE. coli\u003c/em\u003e GroEl, ACI and ACIII exhibited similar hydrolysis patterns. \u003cem\u003eC. hydrogenoformans\u003c/em\u003e ATPase hydrolysis peaked at 60\u0026ordm;C, while the others peaked at 50\u0026ordm;C. No ATP hydrolysis was detected for ACII. ATPase activity for \u003cem\u003eC. hydrogenoformans\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e was consistent with previous reports\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo evaluate chaperonin function, we assessed their ability to protect lactate dehydrogenase (LDH) from heat-induced inactivation. LDH catalyzes the conversion of pyruvate to lactate while reducing NAD\u0026thinsp;+\u0026thinsp;to NADH, which can be monitored spectrophotometrically at 340 nm. When incubated at 48\u0026deg;C, LDH lost 50% its activity within 15 minutes and almost all activity by 35 minutes. However, LDH activity was preserved in the presence of ancestral or modern chaperonins (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003eThe modern \u003cem\u003eC. hydrogenoformans\u003c/em\u003e chaperonin initially boosted LDH activity after 5 minutes, followed by a return to baseline levels at 15 minutes and a slight decrease to 75% of the initial activity by 35 minutes. AFCB and ACIII showed similar patterns, with a small initial increase in LDH activity before stabilizing at ~\u0026thinsp;75% activity after 35 minutes. By contrast, ACI and ACII provided sustained protection: LDH activity remained at ~\u0026thinsp;150% with ACII throughout the experiment, while ACI caused a 2.5-fold increase in activity within the first 5 minutes before returning to baseline levels by the end of the incubation.\u003c/p\u003e\u003cp\u003e\u003cem\u003eEvolutionary trends in electrostatic potential and folding energy\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo further characterize ACs and identify potential features, we analyzed their electrostatic properties using the APBS method\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e (implemented in PyMol), and calculated variations in folding energies with FoldX (see Methods) \u003cb\u003e(Table II\u003c/b\u003e). Electrostatic map calculations revealed that the most ancestral reconstructions (ACI and ACII) predominantly displayed a negative surface electrostatic potential (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eComputational analysis of free folding energies revealed significant correlations between ancestrality and key structural parameters \u0026ndash; hydrogen bonds, entropy, electrostatic interactions, solvation effects, Van der Waals interactions and torsion energy \u0026ndash; all of which contribute to protein stability (\u003cb\u003eTable II\u003c/b\u003e). Group I ancestors showed significant positive (\u0026ge;\u0026thinsp;0.5) correlations with backbone hydrogen bonds (r\u0026thinsp;=\u0026thinsp;0.94), side-chain hydrogen bonds (r\u0026thinsp;=\u0026thinsp;0.77) and ionization energy (r\u0026thinsp;=\u0026thinsp;0.59); and significant negative (\u0026le;-0.5) correlations with main-chain entropy (r = -0.86) and torsion energy (r = -0.60). Group II ancestors showed significant positive correlations with backbone hydrogen bonds (r\u0026thinsp;=\u0026thinsp;0.90), side-chain hydrogen bonds (r\u0026thinsp;=\u0026thinsp;0.54) and charge-charge interaction (r\u0026thinsp;=\u0026thinsp;0.70); and significant negative correlations with side- (r = -0.70) and main-chain (r = -0.50) entropy, and ionization energy (r = -0.51). Group III ancestors showed significant positive correlations with total stability (r\u0026thinsp;=\u0026thinsp;0.54), Van der Waals interaction (r\u0026thinsp;=\u0026thinsp;0.63), nonpolar solvation (r\u0026thinsp;=\u0026thinsp;0.55), and torsion energy (r\u0026thinsp;=\u0026thinsp;0.86); and significant negative correlations with polar solvation (r = -0.55), backbone Van der Waals clashes (r = -0.51) and helix dipole effects (r = -0.68). These divergences suggest that different chaperonin lineages developed specialized strategies, using diverse physicochemical mechanisms, to optimize protein stability.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cem\u003eIntermediate single-ring structures in ancestral chaperonins support a stepwise oligomerization model\u003c/em\u003e\u003c/p\u003e\u003cp\u003eOur phylogenetic analysis, based on 96 modern sequences, produced a topology consistent with previous studies\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan additionalcitationids=\"CR39 CR40\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e–\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, and allowed us to resurrect and characterize four ancestral nodes (ACI, ACII, ACIII, and AFCB) (\u003cb\u003eSupplementary Fig.\u0026nbsp;2\u003c/b\u003e). We observed that the earliest ancestors – ACI (bacterial GroEL) and ACII (archaeal thermosome) – are single-ring structures. In Group I systems, double-ring structures are known to dissociate upon ATP hydrolysis, increasing folding capacity for larger substrates, and single-ring structures have been observed in bacteriophage-encoded chaperonins (e.g., φ-EL and OBP), the human mitochondrial chaperonin, and bacterial GroEL/ES systems\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. To our knowledge, ACII represents the first reported single-ring structure for a Group II chaperonin.\u003c/p\u003e\u003cp\u003eThe evolutionary progression from an exclusively single-ring structure in ACI, to a mix of single and double rings in ACII, and finally to an exclusively double-ring assembly in ACIII (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), suggests a gradual, step-by-step evolution from single- to double-ring chaperonins. This pattern supports a timeline where ACI is the oldest ancestor, followed by ACII and then ACIII – with the latter likely arising through horizontal gene transfer between an ancestral archaeon and a Firmicutes bacterium\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e rather than being a direct descendent from LUCA\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Sequence divergence patterns (\u003cb\u003eTable I\u003c/b\u003e) further corroborate this timeline, showing ACI as the most divergent, followed by ACII, ACIII, and finally AFCB.\u003c/p\u003e\u003cp\u003eStructurally, ACII features a unique build-in helical protrusion that acts as a lid, eliminating the need for a GroES-type cochaperonin for cavity closure (\u003cb\u003eSupplementary Fig.\u0026nbsp;6\u003c/b\u003e). This feature may reflect an intermediate evolutionary stage between the architectures of modern Group I and II chaperonins. Another key difference lies in their subunit structure: ACI and has seven subunits while ACII has eight – a stoichiometry that mirrors their modern counterparts (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These differences could stem from the presence of multiple assembly types in LUCA, or reflect lineage-specific changes in ring size over evolutionary time. Such evolutionary divergence in subunit stoichiometry is also observed in modern complexes: for example, archaeal peroxiredoxins (a thiol-dependent peroxidase that protects cells from oxidative damage) often form pentameric rings, whereas bacterial homologs adopt hexameric forms\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFunctionally, chaperonins operate through two major conformational states: an open state for substrate recognition, and a closed state that traps and facilitates protein folding. The ACs appear to have developed two distinct mechanisms for cavity closure. Bacterial chaperonins co-evolved with a small capping oligomer (the cochaperonin), whereas archaeal and eukaryotic chaperonins developed an extra sequence, a lid-like protrusion that fulfils the same locking role. These functional variations suggest that the conserved folding chamber of chaperonins adapted to distinct functional and environmental pressures. While the evolutionary relationships between Bacteria, Archaea, and Eukarya are still debated (and may never be fully clarified), our findings align with the classical model in which Bacteria are evolutionarily closer to LUCA\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe evolution of protein complexity – from simpler to more structurally and functionally elaborate proteins (such as from monomers to oligomers or through the acquisition of additional domains) – has been explored using ASR in previous works\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In particular, multimerization has been investigated in the ATPase complex\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e and RuBisCO\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e protein families. Thornton and colleagues have shown that such transitions can occur naturally through just one or a few mutations\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Building on this work, our study reveals an evolutionary trajectory within the chaperonin family. We found that ACI likely transitions between monomeric and single-ring states, representing an early stage in oligomerization. By contrast, ACII and ACIII predominantly form stable double-ring assemblies, suggesting that the molecular framework for full oligomeric complexity was already established in these groups. The coexistence of both single- and double-ring assemblies in ACII illustrates an evolutionary intermediate in which the molecular architecture for oligomerization had emerged but was not yet fully optimized – likely lacking one or a few key mutations needed to substantially enhance binding affinity and stabilize the double-ring state\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. While we did not explicitly test mechanistic models for the evolution of molecular complexity, our analysis of the posterior probabilities of the amino acids at positions known to disrupt double-ring assembly (R452E, E461A, S463A, V464A) in \u003cem\u003eE. coli\u003c/em\u003e GroEL\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e showed that the ancestral sequence (ACI) retained three of these substitutions with high confidence (\u003cb\u003eSupplementary Table II\u003c/b\u003e). Tracking these probabilities across nodes revealed dynamic shifts: residues that potentially prevent double-ring formation in ACI gradually gave way to substitutions that favor stable double-ring interfaces. Together, these patterns further support a gradual evolutionary transition from a single-ring to a double-ring architecture in early Group I chaperonins – a shift predicted to have reached completion by node 128 (\u003cb\u003eSupplementary Fig.\u0026nbsp;3\u003c/b\u003e), corresponding to the divergence time of the FCB group.\u003c/p\u003e\u003cp\u003e\u003cem\u003eATP-dependent stability and activity in ancestral chaperonins\u003c/em\u003e\u003c/p\u003e\u003cp\u003eATP played an essential role in the assembly of ACI oligomers and often enhanced the assembly of ACII by increasing the number of oligomers. By contrast, ACIII and AFCB did not require ATP for either assembly or stability. This suggests that ATP dependency was strongest in the most ancestral nodes, particularly ACI. Some modern thermosomes exhibit ATP-dependent oligomer formation, which could be an evolutionary remnant from ancestral times\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eUnder neutral conditions, ATPase activity was detected in all ancestral chaperonins tested, with the exception of ACII (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). The absence of detectable activity in ACII could indicate a requirement for specific cofactors, such as ammonium salts, as observed in certain methanogenic archaea\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e and bacterial thermosome-like systems\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDespite its lack of detectable ATPase activity, ACII proved to be highly effective at protecting LDH from heat inactivation (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). Indeed, it outperformed the other chaperonins in maintaining LDH stability at 48°C, sustaining 150% of its activity throughout the experiment. Although we initially attempted to assess the ability of these ACs to assist in refolding of chemically denatured proteins, technical challenges prevented these assays from being carried out. Specifically, we were unable to detect successful refolding even with \u003cem\u003eE. coli\u003c/em\u003e GroEL as a control, likely due to the absence of its essential co-chaperonin GroES under our experimental setup. Consequently, we shifted our focus to a more limited, but still insightful, protective assay (LDH heat inactivation), which provided valuable insights into the stress-response capacity of the ACs. While molecular crowding could theoretically explain this effect, the variations seen among the different chaperonins suggest it was not the primary cause.\u003c/p\u003e\u003cp\u003eAlthough the closest modern sequences to our reconstructions (in the NCBI nr-database) were from thermophilic organisms (\u003cb\u003eTable I\u003c/b\u003e), the activity of our ancestral proteins was comparable with that of the mesophile GroEL from \u003cem\u003eE. coli\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. This contrasts with other proteins reconstructed through ASR, which often display high thermostability\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. This suggests that ACs might be a unique case where extreme thermal stability was not a defining ancestral trait or a functional requirement. However, our results on ATP-dependent stability and activity do not necessarily rule out thermal adaptation. Some modern thermophilic chaperonins also exhibit ATP-dependent oligomerization, and ATPase activity alone may not fully reflect thermal robustness\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cem\u003ePredicted electrostatic features suggest ancient environmental pressures\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe electrostatic potential on the surface of a protein is crucial for molecular interactions, and changes in this potential can indicate how proteins adapt to environmental pressures. Our analysis revealed that ACI and ACII, likely the earliest ancestral proteins, have highly negative surface charges (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). This suggests that ACs in Groups I and II evolved in conditions where negative surface charges were advantageous. For example, these changes could have helped stabilize proteins in acidic or high-salt conditions\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, or increased thermal stability at high temperatures\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Interestingly, the closest modern homolog to ACI is an acidophilic thermophile (\u003cb\u003eTable I\u003c/b\u003e)\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, echoing the adaptation of ancestral thioredoxins to acidic environments\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Given the proposed evolutionary link between chaperonins and thioredoxins\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, this parallel supports the idea that both families may have originated in harsh primordial environments, where electrostatic surface properties were crucial for protein stability. Specifically, positive surface charges could have counteracted proton-driven destabilization in low-pH conditions, while surface charges might have been essential in maintaining solubility and preventing aggregation in high-salinity habitats\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. As environmental conditions fluctuated over evolutionary time, increasing positive charges may have been selectively favored to balance protein stability and function, highlighting their adaptive versatility. While the electrostatic profiles and modern homologs suggest that ACs may have been adapted to high-temperature, low-pH, or high-salinity environments, these hypotheses remain speculative. We did not experimentally test activity under extreme conditions, and so direct validation of these proposed environmental adaptations will require further research.\u003c/p\u003e\u003cp\u003e\u003cem\u003eEnergetic trends and environmental adaptations of ancestral chaperonins\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTrends in energy variation reveal distinct evolutionary paths among the three chaperonin groups, driven by environmental pressures (\u003cb\u003eTable II\u003c/b\u003e). In Groups I and II, overall stability remained relatively constant. However, we observed a significant increase in hydrogen bonds and a decrease in the entropy term (calculated by FoldX encompassing main-chain and side-chain conformational entropy)\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. This suggests that ACs in these groups could have evolved more ordered and rigid structures, to maintain stability under stress. This pattern aligns with observations in thermophilic proteins, which enhance stability through stronger intramolecular forces rather than significant changes in global stability\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn Group II, the inferred increase in charge-charge interactions and decrease in ionization energy point to adaptations to high-salt environments, where balancing electrostatic interactions is crucial for solubility and function. Similar adaptations are found in halophilic proteins, which optimize surface charges to prevent aggregation in saline conditions\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Conversely, the increasing ionization energy in Group I suggests adaptations to acidic environments, where stabilizing charged residues is essential for maintaining structural integrity – a common characteristic of acidophilic proteins\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFor Group III ancestors, a notable increase in total stability appears to be driven by strengthened Van der Waals forces and reduced backbone clashes, indicating enhanced hydrophobic packing. This is a well documented adaptation in thermophilic proteins, where compact hydrophobic cores provide resilience to high temperatures\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Additionally, a decrease in polar solvation and increase in nonpolar solvation suggest reduced hydrophilicity. This could reflect adaptations to low-water-activity environments, such as hypersaline, acidic, or thermophilic habitats\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e–\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTogether, these trends suggest that environmental pressures were a significant factor in shaping the evolution of chaperonins, driving structural adaptations to extreme conditions. This supports the hypothesis that early chaperonins likely evolved in halo-acidophilic, possibly thermophilic environments, similar to those thought to exist on early Earth\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, gradually adapting as Earth’s environment became more neutral over time. This perspective differs from previous analyses of ancestral nucleoside diphosphate kinases and ribosomal protein uS8s, which proposed a primitive alkaline habitat\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. However, these scenarios are not mutually exclusive, and the selective pressures that shaped one protein family may have differed from those acting on another. Nonetheless, previous\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e and recent\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e advances in prebiotic chemistry support the idea that life could have formed in acidic hydrothermal environments. This notion is reinforced by studies on ancestral thioredoxins\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, which add to the idea that early life flourished in hot, acidic conditions. These remain open questions, inviting further research.\u003c/p\u003e\u003cp\u003eAlthough these structural trends might suggest adaptations to extreme environments, we recognize that our experimental support for this hypothesis is limited, and computational estimates given by programs such as FoldX have known limitations and should be interpreted with caution\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Furthermore, ATPase activity assays suggest that the reconstructed proteins exhibit limited activity at temperatures above 50°C, although these two properties are not necessarily correlated. To gain a more complete understanding of the environmental preferences of these ancestral proteins, future studies should examine a broader range of physicochemical conditions, including low-pH and high-salinity.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConcluding remarks\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study demonstrates that ASR, despite its inherent challenges and the practical limitations of our own implementation, can reveal unexpected structural features in ACs. Our findings support a model where chaperonins evolved gradually from single-ring to double-ring assemblies, with ACII potentially representing an evolutionary intermediate. These structural changes, coupled with shifts in ATP dependence and stability, suggest an overall trend toward greater molecular complexity\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlthough the energetic patterns we describe were inferred computationally and rely on structural models rather than direct measurements – thus requiring cautious interpretation – they nonetheless indicate adaptations to acidic, high-salinity environments. These environmental pressures may have shaped early protein evolution\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. While some of these insights remain to be experimentally validated, they align with findings from their closely related thioredoxin family\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOverall, our work contributes to the growing evidence on how complexity emerges in molecular systems. It also highlights evolutionary patterns that could guide future research into key transitions in early cellular life and the development of modern protein architectures, particularly within the chaperonin family.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003ePhylogenetic analysis and ancestral sequence reconstruction\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe chaperonin GroEL sequence from \u003cem\u003eE. coli\u003c/em\u003e (P0A6F5) was used as query in a blast search on the KEGG (Kyoto Encyclopedia of Genes and Genomes) server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genome.jp/tools/blast\u003c/span\u003e\u003cspan address=\"https://www.genome.jp/tools/blast\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Searches were performed individually for major taxonomic groups to ensure broad representation, and hits were filtered using a similarity threshold (10\u003csup\u003e− 6\u003c/sup\u003e)\u003csup\u003e63\u003c/sup\u003e. The resulting FASTA sequences were downloaded and curated to generate a manageable and taxonomically-balanced dataset for ancestral sequence reconstruction. We selected 96 sequences based on the following criteria: (1) broad taxonomic coverage, (2) sequence completeness and quality – excluding partial or poorly annotated entries – and (3) removal of redundancy using CD-HIT (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://weizhong-lab.ucsd.edu/cdhit_suite\u003c/span\u003e\u003cspan address=\"http://weizhong-lab.ucsd.edu/cdhit_suite\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e64\u003c/sup\u003e. Multiple sequence alignment was performed with MAFFT (L-INS-i strategy; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mafft.cbrc.jp/alignment/server\u003c/span\u003e\u003cspan address=\"https://mafft.cbrc.jp/alignment/server\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e65\u003c/sup\u003e, followed by manual inspection and curation. Insertions and deletions (\u003cem\u003eindels\u003c/em\u003e) were carefully reviewed using a conservative approach: clade-specific \u003cem\u003eindels\u003c/em\u003e were retained, while individual or sporadic \u003cem\u003eindels\u003c/em\u003e were removed. This strategy aimed to reduce alignment noise while preserving phylogenetically informative features. We note that sequence selection and \u003cem\u003eindel\u003c/em\u003e treatment can significantly influence phylogenetic tree topology and ancestral sequence inference. Although we did not compare results across different, independently curated, datasets, our curation strategy was designed to reflect the best practices in the field, as recommended in previous studies\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eProtTest 3.4 was used to estimate a model of amino acid substitutions\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. The model chosen, according to the Akaike information criterion (AIC), was the Le Gascuel 2008 model, with gamma distribution and a proportion of invariable sites (LG + I + G model, alpha: 1.40)\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. The phylogenetic history of the 96 chaperonin sequences was reconstructed using the Bayesian method, implemented in MrBayes 3.2.7\u003csup\u003e69\u003c/sup\u003e. The analysis used two independent Markov-chain Monte Carlo runs, each with two chains, performed over 800,000 generations until convergence was obtained, which was confirmed by the following indicators: (i) the standard deviation of split frequencies was less than 0.01; (ii) stationarity was checked by plotting likelihood scores (lnL) against a number of generations; and (iii) for each parameter in the model, a value of 1.000 for the potential scale reduction factor (PSRF) was obtained. Trees were sampled every 100 generations. Each run produced 8501 trees, from each 6376 were included, totaling 12,752 trees from which a consensus tree with high probabilities at the nodes was obtained. Marginal reconstruction of ancestral sequences was done with PAML 4.9 CodeML, using the LG substitution model with gamma-distributed rates across sites\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. The most probable ancestral sequences of the four nodes were selected and modified manually to match the closest modern sequence, as determined by branch length\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. The sequences corresponded to the last common ancestor nodes of Group I (ACI, for ancestor group I, aged ~ 4.1 Ga), Group II (ACII, ~ 3.9 Ga), Group III (ACIII, divergence time approximately 3.0-2.5 Ga corresponding to divergence times of firmicutes and cyanobacteria), and the last common ancestor of FCB Group (AFCB, ~ 3.0-2.5 Ga). Divergence times were gathered from various sources and synthesized using the TimeTree project\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eCloning, expression and purification of ancestral enzymes\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe amino acid sequence of each protein included a C-terminal His-tag and was translated into the corresponding DNA nucleotide sequence, codon-optimized for \u003cem\u003eE. coli\u003c/em\u003e using the OptimumGene™ Codon Optimization Analysis and Algorithm (GenScript Biotech, Rijswijk, Netherlands). The optimized genes were synthesized by the GenScript Recombinant Protein Expression Service (GenScript Biotech) and ligated into plasmid pET-30a(+) using the CloneEZ method. Plasmids were cloned, amplified in \u003cem\u003eE. coli\u003c/em\u003e DH5α (DE3), and purified from kanamycin-resistant cells using the QIAprep® Miniprep Kit (Qiagen GmbH, Hilden, Germany). The integrity of the plasmid preparations was verified by agarose gel electrophoresis. \u003cem\u003eE. coli\u003c/em\u003e BL21 (DE3) cells were transformed with the purified plasmids and selected by kanamycin resistance. Recombinant protein expression was induced with 1 mM IPTG for 4 h at 37°C. After centrifugation, the cell pellet was resuspended in nickel nitrilotriacetic acid (Ni-NTA) binding buffer (NiBB) (20 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid [HEPES] pH 7.4, 20 mM imidazole, 500 mM KCl, 1 mM DTT and 15% glycerol [v/v]) supplemented with a protease inhibitor cocktail (Roche Holding AG, Basel, Switzerland). The resuspended solution was sonicated three times for 1 min each time (cycles of 10 sec \u003cem\u003eon\u003c/em\u003e, 50 sec \u003cem\u003eoff\u003c/em\u003e), with an amplitude of 50% in a Branson Digital Sonifier 250, and centrifuged at 15.000 × g in a Beckman Coulter ultracentrifuge with a Type 50.2 Ti rotor (40 min at 4°C). The supernatant was filtered (0.45 µm) and loaded onto a Ni-NTA agarose column (HisTrap FF 5 ml, GE Healthcare, Chicago, IL) using a fast protein liquid chromatography (FPLC) apparatus (GE Healthcare). The loaded column was then washed with 5 column volumes of NiBB and eluted with Ni-NTA elution buffer (NiEB) (same as NiBB but with 500 mM imidazole) using a gradient of 50% over 15 min. Fractions (2 ml) were collected and analyzed by SDS-PAGE, and those containing the corresponding protein were pooled and concentrated by centrifugation (4.000 × g, in a Hitachi centrifuge with a R15A rotor, at 4°C) using 50 kDa or 100 kDa cut-off Amicon Ultra 15 filters (Merck Millipore, Darmstadt Germany). The concentrated fractions containing the protein of interest were loaded onto size exclusion chromatography (SEC) Superose® 6 Increase 10/300 GL (GE Healthcare) columns, previously equilibrated in SEC buffer (SECB) (20 mM HEPES pH 7.4, 150 mM KCl, 10% glycerol [v/v]). Proteins were eluted in SECB and fractions (0.5 ml) were analyzed by SDS-PAGE and by negative staining electron microscopy. When necessary, complex formation was induced with 25 mM MgCl\u003csub\u003e2\u003c/sub\u003e and 5 mM ATP\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Fractions with proteins forming the typical ring complex were supplemented with 5% glycerol, snap frozen in liquid nitrogen and stored at -20°C.\u003c/p\u003e\u003cp\u003e\u003cem\u003eATPase activity assay\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe ATP hydrolysis rates of ancestral chaperonins (ACI, ACII, ACIII, and AFCB) and \u003cem\u003eC. hydrogenoformans\u003c/em\u003e (UniProt: Q3AF10) were calculated as the amount of phosphate (Pi) released (nanomol/min/nanomol chaperonin) based on the theoretical molecular weight of each oligomeric complex. The theoretical molecular weight was determined from the protein amino acid sequence using ProtParam (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://web.expasy.org/protparam/\u003c/span\u003e\u003cspan address=\"https://web.expasy.org/protparam/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). A single-ring oligomer was assumed for ACI, whereas a double-ring oligomer was assumed for the other chaperonins. Chaperonin proteins at concentrations of 0.35 µg•µl\u003csup\u003e− 1\u003c/sup\u003e or 0.5 µg•µl\u003csup\u003e− 1\u003c/sup\u003e were incubated in 50 µl of buffer containing 50 mM HEPES pH 7.4, 150 mM KCl, 5 mM MgCl\u003csub\u003e2\u003c/sub\u003e and 0.5 mM ATP. Reactions without chaperonin served as negative controls, and subtracted from the results. Incubations were carried out on a thermoblock with gentle agitation (300 rpm) across a range of temperatures (30°C, 40°C, 50°C and 60°C). The reaction was stopped with BIOMOL GREEN™ Reagent. Following a 20-minute incubation at room temperature (RT), absorbance at 650 nm was measured using a SpectraMax® iD3 spectrophotometer. The amount of phosphate released was estimated using a standard curve generated from phosphate dilutions ranging from 2 to 0 nmol.\u003c/p\u003e\u003cp\u003e\u003cem\u003eChaperone activity assay with lactate dehydrogenase\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe chaperone activity of the resurrected chaperonins was assessed as described\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, with minor modifications. The assay measures the ability of each chaperonin to preserve LDH activity under thermal stress. Enzyme inactivation was induced at 48°C in 50 µl of HEPES buffer (50 mM HEPES, pH 7.4, 150 mM KCl, 5 mM MgCl\u003csub\u003e2\u003c/sub\u003e) containing 0.1 µM LDH, 0.4 µg•µl\u003csup\u003e− 1\u003c/sup\u003e chaperonin, and 1 mM ATP. Reactions without chaperonin served as negative controls. Incubations were performed on a thermoblock with gentle agitation (300 rpm). At each time point, 5 µl of the incubation mixture was transferred to a cuvette containing 495 µl of assay buffer (20 mM HEPES, pH 7.4, 50 mM KCl, 0.3 mM NADH, and 1.6 mM sodium pyruvate). The cuvette was immediately sealed with parafilm and mixed by inversion. The decrease in absorbance at 340 nm, reflecting NADH consumption, was monitored for 3 minutes at RT, with readings taken every 15 seconds. All assays were performed in duplicate. The slope of each reaction was calculated using Microsoft® Excel, and the mean and standard deviation were determined for each sample. Results were normalized to the enzyme activity prior to thermal stress.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSample preparation for cryogenic electron microscopy\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSamples were vitrified in a Vitrobot Mark IV (FEI, Eindhoven, Netherlands) at 4°C and 100% humidity. A drop of 3 µl of sample was absorbed onto Quantifoil R 2/2 300 mesh and glow-discharged (25 mA, 15 seconds) grids. The force and blotting time were − 2 and 2 s, respectively. Vitrified grids were stored in liquid nitrogen before screening. The vitrified samples were checked, and data from the best sample was acquired in a 200 kV FEI Talos Arctica equipped with a Falcon III direct electron detector at the Spanish National Center for Biotechnology CryoEM facility (CryoEM CNB-CSIC). The images of last common ancestors of Group I and Group III (ACI, ACIII) proteins were acquired at a nominal magnification of ×120000 (corresponding to a pixel size of 0.85 Å/pixel) and the AFCB Group images at ×73000 (corresponding to a pixel size of 1.42 Å/pixel) with a defocus range of -1.2 to -3.0 µm in all samples. The ACII protein was first checked on a 200 kV FEI Talos Arctica at the CNB followed by data acquisition on a FEI Titan Krios electron microscope operated at 300 kV, equipped with a Gatan Quantum K3 Summit direct electron detector at Diamond Light Source (Oxford, UK). Data collection was carried out with a ×130000 nominal magnification (yielding a pixel size of 0.921 Å/pixel) and a defocus range of -1.0 to -2.4 µm.\u003c/p\u003e\u003cp\u003e\u003cem\u003eImage processing and three-dimensional reconstruction\u003c/em\u003e\u003c/p\u003e\u003cp\u003eImage processing of all samples was performed following a similar workflow. All programs used for image processing to obtain the different 3D maps were implemented in Scipion\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. First, the movies were aligned using MotionCor\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e and the outputs were subjected to CTF determination using Gctf\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. Particles were automatically picked with Xmipp3\u003csup\u003e76\u003c/sup\u003e and were subjected to several 2D classifications using Relion 2.0\u003csup\u003e77\u003c/sup\u003e and Cryosparc\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e to exclude bad particles and ice contamination. Some of the more superior 2D classes were used as a template to generate an initial model using both CryoSPARC and RANSAC\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. The initial models were low-pass filtered to 50 Å and used for 3D classifications. The classes with the best structural features were used for the reconstruction of the different chaperonins using Relion 5.0 and CryoSPARC, applying C7 and D8 symmetry for chaperonins ACI and ACII, respectively, and no symmetry (C1) for chaperonins ACIII and AFCB. The resulting maps were visualized with ChimeraX\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. The resolution of the final maps was estimated by the Fourier shell correlation method, with a cut-off of 0.143 and local resolution was calculated by Xmipp3-MonoRes\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eModel building\u003c/em\u003e\u003c/p\u003e\u003cp\u003eModels for each AC were generated with the AlphaFold3 server\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e using the sequence of each chaperonin as a reference. The resulting models were docked into each cryo-EM density map by rigid body fitting with the Fit in Map tool of ChimeraX. Subsequently, the models were refined through multiple rounds of PHENIX 1.20.1-4487\u003csup\u003e83\u003c/sup\u003e real-space refinement and manually adjusted using Coot 0.9.8.96\u003csup\u003e84\u003c/sup\u003e to improve structural restraints, including Ramachandran plot outliers, geometry, and rotamer restraints (Supplementary Table III). The restraints used in PHENIX real-space refinement included both standard restraints (bond, angle, planarity, chirality, dihedral, and nonbonded repulsion) and additional restraints (Ramachandran plot, C-beta deviations, rotamer, and secondary structure). The refinement process also combined morphing, simulated annealing, and rigid-body strategies.\u003c/p\u003e\u003cp\u003eA local grid search-based fit was incorporated into the refinement strategy to correct side-chain outliers, such as rotamers or regions with poor map fitting. Validation of the final models was done using the phenix.validation cryoem module in PHENIX.\u003c/p\u003e\u003cp\u003e\u003cem\u003eFoldX-based stability prediction of AlphaFold3 models\u003c/em\u003e\u003c/p\u003e\u003cp\u003eProtein stability predictions were performed using FoldX 5.1\u003csup\u003e52\u003c/sup\u003e with AlphaFold3-generated structural models\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e as input. The structural models used for these calculations correspond to the ancestral sequences at the nodes highlighted in \u003cb\u003eSupplementary Fig.\u0026nbsp;3\u003c/b\u003e. The analysis was conducted \u003cem\u003evia\u003c/em\u003e the command-line tool using the Stability function (foldx -c Stability --pdb), which calculates: (1) the total energy (kcal/mol), reflecting overall structural stability; (2) the Gibbs free energy change (ΔG, kcal/mol), representing the energy difference between folded and unfolded states; and (3) individual energy contributions, including backbone hydrogen bonds, sidechain hydrogen bonds, Van der Waals clashes, electrostatics, and solvation energy (polar/apolar components). Default FoldX parameters (pH 7.0, 298 K, 0.05 M ionic strength) were applied without further refinement of the input models.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCryo-EM data generated in this study have been deposited in the Electron Microscopy Data Bank under accession codes EMD-54342 for ACI, EMD-54339 for ACII closed-state double ring, EMD-54343 for ACII open-state double ring, EMD-54344 for ACII closed-state single ring, EMD-54345 for ACII open-state single ring, EMD-54340 for ACIII, and EMD-54341 for AFCB, respectively. The associated models have been also deposited in the Protein Data Bank under accession codes 9RWP for ACII closed state double ring, 9RWQ for ACIII and 9RWR for AFCB. All other data generated in this study are provided in the Supplementary Information/Source Data file with this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Jos\u0026eacute; Manuel S\u0026aacute;nchez Ruiz (Granada University, Spain) and Jos\u0026eacute; Berenguer (Autonomous University of Madrid, Spain), for critical insights and discussion. This research was supported by the Spanish Ministry of Science and Innovation and Agencia Estatal de Investigaci\u0026oacute;n MCIN/AEI/10.13039/501100011033 and \u0026ldquo;ESF Investing in your future\u0026rdquo; through the grants PID2021-126746NB-I00 and RTI2018-094368-B-I00 to V.P., and PID2022-137175NB-I00 through the \u0026ldquo;Severo Ochoa\u0026rdquo; Program for Centers of Excellence in R\u0026amp;D (CEX2023-001386-S) to J.M.V. and J.C. The support the grant CaixaResearch Health 2023 (HR23-00837) to J.M.V. is also acknowledged.\u0026nbsp;R.S. is funded by a Ph.D. fellowship from INTA, by the fellowship \u0026ldquo;Ford-Apadri\u0026ntilde;a la Ciencia\u0026rdquo;, and by MCIU/AEI/10.13039/501100011033 and FSE+ through the grant PTA2022-022084-I.\u0026nbsp;The authors acknowledge the technical support of the cryoEM CNB-CSIC facility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCentro de Astrobiolog\u0026iacute;a (CAB), INTA-CSIC, Torrej\u0026oacute;n de Ardoz, Madrid, Spain\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRita Severino, Luis S\u0026aacute;nchez-Pulido, Mercedes Moreno-Paz and V\u0026iacute;ctor Parro\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNational Center for Biotechnology (CNB), CSIC, Madrid, Spain\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJorge Cu\u0026eacute;llar, Jorge Guti\u0026eacute;rrez-Seijo, Mois\u0026eacute;s Maestro-L\u0026oacute;pez, C\u0026eacute;sar Santiago and Jos\u0026eacute; Mar\u0026iacute;a Valpuesta\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUniversity of Alcal\u0026aacute; (UAH), Alcal\u0026aacute; de Henares, Madrid, Spain\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRita Severino\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnidad de Nanobiotecnolog\u0026iacute;a, CNB-CSIC-IMDEA Nanociencia Associated Unit, Madrid, Spain\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJos\u0026eacute; Mar\u0026iacute;a Valpuesta\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceived the study, R.S. and V.P. Phylogenetic analysis, ancestral reconstruction, R.S. Cryo-EM, data acquisition, data processing, structural reconstruction, J.C., J.G-S., M.M-L., C.S. Biochemical experiments, R.S., M.M-L., J.G-S., M.M-P. Computer simulations, R.S., L.S-P. Original draft, R.S. Wrote the manuscript, R.S., J.C., J.M.V., V.P. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Rita Severino \u0026lt;[email protected]\u0026gt; or Jorge\u0026nbsp;Cu\u0026eacute;llar \u0026lt;[email protected]\u0026gt;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHorwich AL, Fenton WA (2020) Chaperonin-assisted protein folding: a chronologue. Q Rev Biophys 53:1\u0026ndash;127\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHorovitz A, Reingewertz TH, Cu\u0026eacute;llar J (2024) Mar\u0026iacute;a Valpuesta, J. Chaperonin Mechanisms: Multiple and (Mis)Understood? Annu Rev Biophys 53:53\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStan G, Lorimer GH, Thirumalai D (2022) Friends in need: How chaperonins recognize and remodel proteins that require folding assistance. Front Mol Biosci 9\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRowland SE, Robb FT, Structure (2017) Function and Evolution of the Hsp60 Chaperonins. in \u003cem\u003eProkaryotic Chaperonins, Heat Shock Proteins, vol 11\u003c/em\u003e (eds. Kumar, C. \u0026amp; Mande, S.) 3\u0026ndash;20Springer Nature Singapore. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-981-10-4651-3_1\u003c/span\u003e\u003cspan address=\"10.1007/978-981-10-4651-3_1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLlorca O, Gal\u0026aacute;n A, Carrascosa JL, Muga A, Valpuesta JM (1998) GroEL under heat-shock: Switching from a folding to a storing function. J Biol Chem 273:32587\u0026ndash;32594\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSantra M, Dill KA, de Graff AMR (2018) How Do Chaperones Protect a Cell\u0026rsquo;s Proteins from Oxidative Damage? Cell Syst 6:743\u0026ndash;751e3\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStorey JM, Storey KB (2023) Chaperone proteins: universal roles in surviving environmental stress. Cell Stress Chaperones 28:455\u0026ndash;466\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDekker C, Willison KR, Taylor WR (2011) On the evolutionary origin of the chaperonins. Proteins Struct Funct Bioinforma 79:1172\u0026ndash;1192\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMu\u0026ntilde;oz-Villagr\u0026aacute;n C et al (2024) The Thioredoxin Fold Protein (TFP2) from Extreme Acidophilic Leptospirillum sp. CF-1 Is a Chaperedoxin-like Protein That Prevents the Aggregation of Proteins under Oxidative Stress. Int J Mol Sci 25\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStroobants S et al (2019) Structure of the Prx6-subfamily 1-Cys peroxiredoxin from sulfolobus islandicus. Acta Crystallogr Sect F Struct Biol Commun 75:428\u0026ndash;434\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoemans CV, Vertommen D, Agrebi R, Collet JF (2018) CnoX Is a Chaperedoxin: A Holdase that Protects Its Substrates from Irreversible Oxidation. Mol Cell 70:614\u0026ndash;627e7\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBresell A, Persson B (2007) Characterization of oligopeptide patterns in large protein sets. BMC Genomics 8:1\u0026ndash;15\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAn YJ et al (2017) Structural and mechanistic characterization of an archaeal-like chaperonin from a thermophilic bacterium. Nat Commun 8:827\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTechtmann SM, Robb FT (2010) Archaeal-like chaperonins in bacteria. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e 107, 20269\u0026ndash;20274\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePereira JH et al (2012) Mechanism of nucleotide sensing in group II chaperonins. EMBO J 31:731\u0026ndash;740\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRebeaud ME, Mallik S, Goloubinoff P, Tawfik DS (2021) On the evolution of chaperones and cochaperones and the expansion of proteomes across the Tree of Life. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e 118, e2020885118\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePauling L, Zuckerkandl E (1963) Chemical Paleogenetics. Molecular \u0026lsquo;Restoration Studies\u0026rsquo; of Extinct Forms of Life. \u003cem\u003eActa Chem. Scand.\u003c/em\u003e 17 supl., 9\u0026ndash;16\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHochberg GKA, Thornton JW (2017) Reconstructing Ancient Proteins to Understand the Causes of Structure and Function. Annu Rev Biophys 46:247\u0026ndash;269\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKa\u0026ccedil;ar B (2024) Reconstructing Early Microbial Life. Annu Rev Microbiol 26:56\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGamiz-Arco G et al (2021) Combining Ancestral Reconstruction with Folding-Landscape Simulations to Engineer Heterologous Protein Expression. J Mol Biol 433:167321\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWheeler LC, Lim SA, Marqusee S, Harms MJ (2016) The thermostability and specificity of ancient proteins. Curr Opin Struct Biol 38:37\u0026ndash;43\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIngles-Prieto A et al (2013) Conservation of protein structure over four billion years. Structure 21:1690\u0026ndash;1697\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarris DF et al (2024) Ancient nitrogenases are ATP dependent. MBio 15:e0127124\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShih PM et al (2016) Biochemical characterization of predicted Precambrian RuBisCO. Nat Commun 7:10382:1\u0026ndash;11\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRisso VA et al (2015) Mutational studies on resurrected ancestral proteins reveal conservation of site-specific amino acid preferences throughout evolutionary history. Mol Biol Evol 32:440\u0026ndash;455\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGaucher EA, Thomson JM, Burgan MF, Benner SA (2003) Inferring the palaeoenvironment of ancient bacteria on the basis of resurrected proteins. Nature 425:285\u0026ndash;288\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmritkar K, Cuevas-Zuvir\u0026iacute;a B, Ka\u0026ccedil;ar B (2025) Evolutionary Dynamics of RuBisCO: Emergence of the Small Subunit and its Impact Through Time. Mol Biol Evol 42\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFinnigan GC, Hanson-Smith V, Stevens TH, Thornton JW (2012) Evolution of increased complexity in a molecular machine. Nature 481:360\u0026ndash;364\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchulz L et al (2022) Evolution of increased complexity and specificity at the dawn of form I Rubiscos. Sci (80-). 378\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeverino R et al (2023) Immunoanalytical Approach for Detecting and Identifying Ancestral Peptide Biomarkers in Early Earth Analogue Environments. Anal Chem 95:5323\u0026ndash;5330\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVillanueva L et al (2021) Bridging the membrane lipid divide: bacteria of the FCB group superphylum have the potential to synthesize archaeal ether lipids. ISME J 15:168\u0026ndash;182\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKumar S et al (2022) TimeTree 5: An Expanded Resource for Species Divergence Times. Mol Biol Evol 39:msac174\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChatellier J, Hill F, Foster NW, Goloubinoff P, Fersht AR (2000) From minichaperone to groel 3: Properties of an active single-ring mutant of groel. J Mol Biol 304:897\u0026ndash;910\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChaston JJ et al (2016) Structural and Functional Insights into the Evolution and Stress Adaptation of Type II Chaperonins. Structure 24:364\u0026ndash;374\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeladopoulos TP, Sotiroudis TG, Evangelopoulos AE (1991) A malachite green colorimetric assay for protein phosphatase activity. Anal Biochem 192:112\u0026ndash;116\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMendoza JA, Warren T, Dulin P (1996) The ATPase activity of chaperonin GroEL is highly stimulated at elevated temperatures. Biochem Biophys Res Commun 229:271\u0026ndash;274\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJurrus E et al (2018) Improvements to the APBS biomolecular solvation software suite. Protein Sci 27:112\u0026ndash;128\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWard LM, Cardona T, Holland-Moritz H (2019) Evolutionary Implications of Anoxygenic Phototrophy in the Bacterial Phylum Candidatus Eremiobacterota (WPS-2). Front Microbiol 10:534180\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCavalier-Smith T, Chao EE (2020) Y. Multidomain ribosomal protein trees and the planctobacterial origin of neomura (eukaryotes, archaebacteria). Protoplasma 257:621\u0026ndash;753\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCavalier-Smith T (2006) Rooting the tree of life by transition analyses. Biol Direct 1:1\u0026ndash;83\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGupta RS (2004) The phylogeny and signature sequences characteristics of Fibrobacteres, Chlorobi, and Bacteroidetes. Crit Rev Microbiol 30(2):123\u0026ndash;143\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBhatt JM et al (2018) Single-Ring Intermediates Are Essential for Some Chaperonins. Front Mol Biosci 5:42\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHimiyama T, Oshima M, Uegaki K, Nakamura T (2019) Distinct molecular assembly of homologous peroxiredoxins from Pyrococcus horikoshii and Thermococcus kodakaraensis. J Biochem 166:1:89\u0026ndash;95\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGribaldo S, Brochier-Armanet C (2006) The origin and evolution of Archaea: A state of the art. Philos Trans R Soc B Biol Sci 361:1007\u0026ndash;1022\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePillai AS, Hochberg GKA, Thornton JW (2022) Simple mechanisms for the evolution of protein complexity. Protein Sci 31\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAndra S, Frey G, Jaenicke R, Stetter KO (1998) The thermosome from methanopyrus kandleri possesses an NH4+-dependent ATPase activity. Eur J Biochem 255:93\u0026ndash;99\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReed CJ, Lewis H, Trejo E, Winston V, Evilia C (2013) Protein adaptations in archaeal extremophiles. Archaea 2013:37327\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVieille C, Zeikus GJ, Hyperthermophilic Enzymes (2001) Sources, Uses, and Molecular Mechanisms for Thermostability. Microbiol Mol Biol Rev 65:1\u0026ndash;43\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsuruoka N et al (2003) Alicyclobacillus sendaiensis sp. nov., a novel acidophilic, slightly thermophilic species isolated from soil in Sendai, Japan. Int J Syst Evol Microbiol 53:1081\u0026ndash;1084\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePerez-Jimenez R et al (2011) Single-molecule paleoenzymology probes the chemistry of resurrected enzymes. Nat Struct Mol Biol 18:592\u0026ndash;596\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchymkowitz J et al (2005) The FoldX web server: An online force field. Nucleic Acids Res 33:W382\u0026ndash;W388\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDelgado J et al (2025) FoldX force field revisited, an improved version. Bioinformatics 41:btaf064\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMadern D, Ebel C, Zaccai G (2000) Halophilic adaptation of enzymes. Extremophiles 4:91\u0026ndash;98\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarcia-Moreno B (2009) Adaptations of proteins to cellular and subcellular pH. J Biol 8\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKraml J, Kamenik AS, Waibl F, Schauperl M, Liedl KR (2019) Solvation Free Energy as a Measure of Hydrophobicity: Application to Serine Protease Binding Interfaces. J Chem Theory Comput 15:5872\u0026ndash;5882\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBenison KC, O\u0026rsquo;Neill WK, Blain D, Hallsworth JE (2021) Water Activities of Acid Brine Lakes Approach the Limit for Life. Astrobiology 21:729\u0026ndash;740\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTadeo X et al (2009) Structural basis for the aminoacid composition of proteins from halophilic archea. PLoS Biol 7\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSugisaki R, Horiuchi Y, Adachi M, Yamasaki K, Sugitani K (1995) Acid character of Archean ocean waters revealed by 3.3 Ga-old ferruginous chert compositions. \u003cem\u003eProc. Japan Acad\u003c/em\u003e 71(B), 170\u0026ndash;174\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFujikawa T, Sasamoto T, Zhao F, Yamagishi A, Akanuma S (2024) Comparative analysis of reconstructed ancestral proteins with their extant counterparts suggests primitive life had an alkaline habitat. Sci Rep 14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKitadai N, Maruyama S (2018) Origins of building blocks of life: A review. Geosci Front 9:1117\u0026ndash;1153\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eŠponer JE et al (2024) Phosphoric acid salts of amino acids as a source of oligopeptides on the early Earth. Commun Chem 7\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBu\u0026szlig; O, Rudat J, Ochsenreither K (2018) FoldX as Protein Engineering Tool: Better Than Random Based Approaches? Comput Struct Biotechnol J 16:25\u0026ndash;33\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKanehisa M, Goto SKEGG (2000) Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 28:27\u0026ndash;30\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang Y, Niu B, Gao Y, Fu L, Li W (2010) CD-HIT Suite: A web server for clustering and comparing biological sequences. Bioinformatics 26:680\u0026ndash;682\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKatoh K, Rozewicki J, Yamada K (2018) D. MAFFT online service: Multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform 20:1160\u0026ndash;1166\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoss CM, Foley G, Boden M, Gillam EMJ (2022) Enzyme Engineering Methods and Protocols. Methods in Molecular Biology, vol 2397. Humana\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDarriba D, Taboada GL, Doallo R, Posada D (2011) ProtTest 3: Fast selection of best-fit models of protein evolution. Bioinformatics 27:1164\u0026ndash;1165\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLe SQ, Gascuel O (2008) An improved general amino acid replacement matrix. Mol Biol Evol 25:1307\u0026ndash;1320\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHall BG (2006) Simple and accurate estimation of ancestral protein sequences. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e 103, 5431\u0026ndash;5436\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang Z, Paml (1997) A program package for phylogenetic analysis by maximum likelihood. Bioinformatics 13:555\u0026ndash;556\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoucher JI, Jacobowitz JR, Beckett BC, Classen S, Theobald DL (2014) An atomic-resolution view of neofunctionalization in the evolution of apicomplexan lactate dehydrogenases. \u003cem\u003eElife\u003c/em\u003e (2014)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHristozova N, Tompa P, Kovacs D (2016) A novel method for assessing the chaperone activity of proteins. PLoS ONE 11:1\u0026ndash;14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede la Rosa-Trev\u0026iacute;n JM et al (2016) Scipion: A software framework toward integration, reproducibility and validation in 3D electron microscopy. J Struct Biol 195:93\u0026ndash;99\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZheng SQ et al (2017) MotionCor2: Anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat Methods 14:331\u0026ndash;332\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang K, Gctf (2016) Real-time CTF determination and correction. J Struct Biol 193:1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVargas J et al (2013) Particle quality assessment and sorting for automatic and semiautomatic particle-picking techniques. J Struct Biol 183:342\u0026ndash;353\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFernandez-Leiro R, Scheres SH (2017) W. A pipeline approach to single-particle processing in RELION. Acta Crystallogr Sect D Struct Biol 73:496\u0026ndash;502\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePunjani A, Rubinstein JL, Fleet DJ, Brubaker MA (2017) CryoSPARC: Algorithms for rapid unsupervised cryo-EM structure determination. Nat Methods 14:290\u0026ndash;296\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVargas J, \u0026Aacute;lvarez-Cabrera AL, Marabini R, Carazo JM, Sorzano CO (2014) Efficient initial volume determination from electron microscopy images of single particles. Bioinformatics 30:2891\u0026ndash;2898\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePettersen EF et al (2021) UCSF ChimeraX: Structure visualization for researchers, educators, and developers. Protein Sci 30:70\u0026ndash;82\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVilas JL et al (2018) MonoRes: Automatic and Accurate Estimation of Local Resolution for Electron Microscopy Maps. Structure 26:337\u0026ndash;344e4\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbramson J et al (2024) Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630:493\u0026ndash;500\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdams PD et al (2010) PHENIX: A comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr Sect D Biol Crystallogr 66:213\u0026ndash;221\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEmsley P, Lohkamp B, Scott WG, Cowtan K (2010) Features and development of Coot. Acta Crystallogr Sect D Biol Crystallogr 66:486\u0026ndash;501\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ch3\u003e\u003cstrong\u003eTable I\u003c/strong\u003e. Best NCBI BLAST Matches for Resurrected Ancestral Chaperonin Sequences\u003c/h3\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 294px;\"\u003e\n \u003cp\u003eBest hits (nr-NCBI Database)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eEstimated age (Ga)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eIdentity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eTaxon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eACI \u0026ndash; Last Common Ancestor of Group I, GroEL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003e\u003cem\u003eAlicyclobacillus sendaiensis\u003c/em\u003e (WP_062305661.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eACII \u0026ndash; Last Common Ancestor of Group II, thermosome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e64%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003e\u003cem\u003eThermococcus alcaliphilus\u003c/em\u003e (WP_252742870.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eACIII \u0026ndash; Last Common Ancestor of Group III, thermosome-like\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026gt;3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003e\u003cem\u003eThermosinus carboxydivorans\u003c/em\u003e (WP_007289467.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eAFCB \u0026ndash; Last Common Ancestor of FCB Group, GroEL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e~3.0-2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003e\u003cem\u003eRhodothermaceae bacterium\u003c/em\u003e (GIV58090.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003e\u003cstrong\u003eTable II\u003c/strong\u003e. Correlation between folding energies and ancestrality, for each group\u003c/h3\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"413\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003eGroup I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003eGroup II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003eGroup III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eFoldX energy terms\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eTotal stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eBackbone hydrogen bonds\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eSide-chain hydrogen bonds\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eVan der Waals\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eElectrostatic (charge-charge)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▼-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003ePolar solvation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eNonpolar solvation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eVan der Waals clashes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▼-0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eSide-chain entropy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▼-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▼-0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eMain-chain entropy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▼-0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eTorsion energy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▼-0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eBackbone Van der Waals clashes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▼-0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eHelix dipole effects\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▲ 0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e▼-0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 229px;\"\u003e\n \u003cp\u003eIonization energy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e▲ \u0026ndash; significant positive correlation (\u0026gt; 0.50)\u003c/p\u003e\n\u003cp\u003e▼ \u0026ndash; negative significant correlation (\u0026lt; -0.50)\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7270162/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7270162/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChaperonins are essential protein-folding machines that can be categorized into three groups based on their structure and phylogeny: Group I (bacterial GroEL), Group II (archaeal thermosome and eukaryotic CCT), and Group III (bacterial thermosome-like). We used ancestral sequence reconstruction (ASR) and protein resurrection (PR) to infer and experimentally test ancestral chaperonins (ACs) from the last common ancestors of these groups (ACI, ACII, and ACIII). The reconstructions exhibited ATPase activity (except for ACII) and client protein heat protection. Electron microscopy and Cryo-EM showed that ACI formed single 7-mer rings, while ACII formed a mix of single/double 8-mer rings, indicating a gradual evolution from simple single-ring to more complex double-ring structures. We also found a unique cochaperonin-independent closing mechanism in ACII. Together, our results illustrate the early stages of molecular complexity evolution and demonstrate how ancestral proteins can inform models of early cellular life.\u003c/p\u003e","manuscriptTitle":"Structural Transitions in Ancient Chaperonins Illustrate Pathways to Protein Complexity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-07 08:34:25","doi":"10.21203/rs.3.rs-7270162/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7e3db2eb-4fec-41dc-9ab4-d32ca1adcb42","owner":[],"postedDate":"August 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":52635559,"name":"Biological sciences/Evolution"},{"id":52635560,"name":"Biological sciences/Structural biology"}],"tags":[],"updatedAt":"2026-01-08T15:05:43+00:00","versionOfRecord":{"articleIdentity":"rs-7270162","link":"https://doi.org/10.1093/molbev/msaf314","journal":{"identity":"molecular-biology-and-evolution","isVorOnly":true,"title":"Molecular Biology and Evolution"},"publishedOn":"2025-11-28 00:00:00","publishedOnDateReadable":"November 28th, 2025"},"versionCreatedAt":"2025-08-07 08:34:25","video":"","vorDoi":"10.1093/molbev/msaf314","vorDoiUrl":"https://doi.org/10.1093/molbev/msaf314","workflowStages":[]},"version":"v1","identity":"rs-7270162","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7270162","identity":"rs-7270162","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}