Tracing back variations in archaeal ESCRT-based cell division to protein domain architectures

Béla P Frohn; Tobias Härtel; Jürgen Cox; Petra Schwille

doi:10.1371/journal.pone.0266395

. 2022 Mar 31;17(3):e0266395. doi: 10.1371/journal.pone.0266395

Tracing back variations in archaeal ESCRT-based cell division to protein domain architectures

Béla P Frohn ^1,², Tobias Härtel ¹, Jürgen Cox ^2,^3,^*, Petra Schwille ^1,^*

Editor: Ernesto Perez-Rueda⁴

PMCID: PMC8970359 PMID: 35358274

Abstract

The Endosomal Sorting Complex Required for Transport (ESCRT) system is a multi-protein machinery that is involved in cell division of both Eukaryotes and Archaea. This spread across domains of life suggests that a precursor ESCRT machinery existed already at an evolutionary early stage of life, making it a promising candidate for the (re)construction of a minimal cell division machinery. There are, however, only few experimental data about ESCRT machineries in Archaea, due to high technical challenges in cultivation and microscopy. Here, we analyse the proteins of ESCRT machineries in archaea bioinformatically on a protein domain level, to enable mechanistical comparison without such challenging experiments. First, we infer that there are at least three different cell division mechanisms utilizing ESCRT proteins in archaea, probably similar in their constriction mechanisms but different in membrane tethering. Second, we show that ESCRT proteins in the archaeal super-phylum Asgard are highly similar to eukaryotic ESCRT proteins, strengthening the recently developed idea that all Eukaryotes descended from archaea. Third, we reconstruct a plausible evolutionary development of ESCRT machineries and suggest that a simple ESCRT-based constriction machinery existed in the last archaeal common ancestor. These findings not only give very interesting insights into the likely evolution of cell division in Archaea and Eukaryotes, but also offer new research avenues by suggesting hypothesis-driven experiments for both, cell biology and bottom-up synthetic biology.

Introduction

Cell division is one of the most fundamental biological processes and typically regarded as one of the basic properties of life. It must be executed in a highly controlled manner, as errors can quickly have fatal consequences. The emergence of cell division machineries that allowed such a high degree of control was hence a major milestone in early evolution, enabling cells to regulate their reproduction. However, how such an early cell division machinery might have looked like is not yet known, and it has not yet been possible to build an in vitro system that can mimic early cell division by fully dividing a membrane vesicle. Thus, the important question of how cell division emerged as a mechanism remains unsolved.

One membrane-transforming machinery which is particularly interesting to this open question is the Endosomal Sorting Complex Required for Transport (ESCRT) [1–4]. It is involved in cell division of both Eukaryotes and Archaea, so it is likely that ESCRT proteins were already playing a role in cell division in their last common ancestor. Especially, it has been suggested that the mechanistic principles of ESCRT machineries in Eukaryotes and Archaea are comparable [1,2,5,6], indicating that ESCRT-like proteins in the common ancestor already formed a machinery. Comparative studies of the variations of today’s known ESCRT machineries hence promise to give insights into an evolutionary early mechanism of cell division.

While the eukaryotic ESCRT machinery has become a highly popular research target over the last years, as it is potentially involved in a wide range of human diseases [7–9], progress in researching the archaeal pendant is slow. One reason for this is that most archaea thrive only under extreme conditions, what makes microscopic or molecular biology-based studies technically challenging. This lack of information is particularly unfortunate when one is interested in a potential ancient ESCRT machinery, because a comparative approach investigating similarities between machineries derived from the same ancestor offers more significant insights when including an higher diversity of descendants in the analysis. Thus, a deeper understanding of the mechanisms of archaeal ESCRT machineries and their diversity is needed.

The ESCRT machinery in archaea was first found in Sulfolobus acidocaldarius [3,4], and it was originally named Cdv system (Cdv for Cell DiVision). In S. acidocaldarius, the machinery consists of three proteins, named CdvA, CdvB (having multiple paralogs) and CdvC [1–4]. Importantly, CdvB proteins are homologs of the eukaryotic ESCRT-III proteins (also having multiple paralogs), and CdvC is a homolog of the eukaryotic Vps4 protein, which is also a part of the ESCRT machinery [1–4]. CdvA, however, has no homologs in Eukaryotes. Thus, there are both similarities and differences in the composition of the machineries, supporting the hypothesis that they derived from a common ancestral machinery but evolved differently.

After the discovery of CdvABC in S. acidocaldarius, homologous proteins were identified in many other archaea. There are four archaeal super-phyla, named DPANN, Euryarchaeota, Asgard and TACK [10], and three of them contain species that possess Cdv proteins [11]. In Euryarchaeota, some few species show CdvB and/or CdvC proteins encoded in their genome, but most species do not possess Cdv proteins. In Asgard archaea, only little is known, because it was just recently possible to cultivate a member of this super-phylum [5,12], but metagenome data and protein prediction indicates that genes encoding for CdvB and CdvC proteins are common within this group, and first experimental evidence is accumulating [13,14]. In TACK archaea, to which Sulfolobus acidocaldarius belongs, species of all groups except Thermoproteales possess all three proteins CdvABC. These variations between super-phyla once more indicate that there was once an ancient Cdv/ESCRT machinery that has evolved differently. Importantly, it was recently suggested that all Eukaryotes originate from the Asgard super-phylum [15], so the eukaryotic ESCRT machinery might be a highly refined version of the Asgard Cdv system. This idea emphasizes the relevance of studying archaeal Cdv machineries to increase our understanding of ancestral versions of eukaryotic ESCRT machineries.

Surprisingly, experiments conducted with TACK archaea showed unequal results in the two main groups of this super-phylum, Crenarchaeota and Thaumarchaeota, although in both groups all three proteins CdvABC are found [1,2]. While in both groups fluorescence microscopy studies showed that initially CdvA proteins enrich at the future division site, probably binding to the membrane, the subsequent steps seem to differ. In Crenarchaeota, CdvB homologs successively join CdvA, together with CdvC [1,5,6,16–19]. While the exact mechanism is unknown, it is mostly suggested that CdvB homologs form a ring-like higher order structure, tethered to the membrane by CdvA [1,16,18]. Then, it is assumed that this ring constricts with the help of CdvC, leading to membrane fission and cell-division [1,5,6,17]. In contrast, in the Thaumarchaeon Nitrosopumilus maritimus, only CdvC concentrates at the division site together with CdvA, while the distribution of CdvB is diffuse [1,20,21]. Up to now, there exists no explanation for this deviation and no model of how membrane constriction may be achieved in Thaumarchaeota.

Thus, while a comparative analysis of Cdv/ESCRT machineries promises interesting insights into an evolutionary early mechanism of cell division, there are two major challenges. First, experimental studies with archaeal Cdv machineries are technically highly challenging, due to the extreme conditions archaeal organisms thrive under. Second, comparing presence or absence of homologs between organisms seems insufficient to draw conclusions about differences in the emerging functions: Both Cren- and Thaumarchaeota possess proteins classified as CdvABC, but nonetheless there seem to be differences in their machineries. Hence, simply investigating which proteins of the Cdv/ESCRT machinery might have existed in the ancient predecessor, as done in previous studies [1,2], cannot lead to a deep mechanistical understanding.

Thus, we here analyse the proteins of archaeal Cdv machineries bioinformatically on a domain level, going beyond the pure existence or absence analysis. This is inspired by the idea that the mechanism of a protein machinery is a result of the interactions between the proteins, and that these interactions occur at specific regions of the proteins’ amino acid sequences. We show that CdvABC homologs in Cren- and Thaumarchaeota differ in their domain compositions and that the different interactions of the proteins caused by these different compositions might explain the previously observed experimental variations. Backed by this finding we then expand the domain analysis to Asgard archaea and find that Cdv machineries in this archaeal super-phylum are highly similar to the eukaryotic ESCRT machinery. Finally, by combining the domain analysis with phylogenetic analysis, we propose an evolutionary scenario of Cdv/ESCRT development, which provides insights into how an ancient machinery based on evolutionary early Cdv/ESCRT proteins might have looked like. Importantly, we suggest that this ancient machinery might have been able to form a contracting ring, making it a strong candidate for a very simple cell division machinery.

Results

Cdv systems are composed of eleven domains, seven of them occurring in all organisms, four only in specific phylogenetic groups

Based on homology to previously studied Cdv machineries, we searched publicly available genomes and proteomes of archaeal organisms for homologs of CdvABC proteins. From the resulting list of organisms containing at least one CdvABC homolog we selected 37 organisms based on the high quality of their genomic information. We then identified domains of interest in Cdv proteins of the selected organisms by secondary structure prediction, by search against Pfam, InterPro and the Conserved Domain Database (CDD), and by utilizing regular expressions reported in the literature. Hereafter we will call all regions in the amino acid sequences of proteins that are expected to execute a distinct function domains, although strictly speaking some are only motifs). As Fig 1 shows, we found eleven different domains in Cdv machineries (for the exact locations see S1 Table). Four domains (Snf7, AAA+ATPase, MIT and Vps4_C) were found in organisms of all three super-phyla, indicating that they were already part of evolutionary early Cdv machineries. One domain (MIM2) was found in Asgard and TACK archaea, but not in Euryarchaeota, two domains (CdvA_alpha and CdvA_beta) were found in TACK archaea, but not in Euryarchaeota or Asgard archaea, and two domains (BWI and BWH) were found only in the TACK subgroup called Crenarchaeota. This suggests that by gain or loss of some domains, rather than gain or loss of full proteins, Cdv systems developed differently from their common ancestor, providing a hint that this might be an explanation for differences in their respective mechanisms. Finally, in Asgard archaea, we found two more unique domains. Interestingly, these matched domains occurring in the eukaryotic ESCRT machinery. First, consistent with the results of Lu et al. [22], we found potential MIM1 [23] domains at the C-terminus of most Asgard CdvB homologs. Second, consistent with the results of Caspi and Dekker [1], we predicted alpha-helices at the N-terminus of one group of Asgard CdvB homologs that match the ESCRT-III N-terminal ANCHR [24] motif. Thus, this simple analysis already yielded two interesting results: First, four domains are shared between all organisms included in this study, which suggests that the Cdv present in their common ancestor likely presented these domains. Second, some domains occur only in specific phylogenetic groups, thus they are promising candidates to explain differences between the machineries of these groups. To analyse these differences and the machineries they might give rise to, we next investigated the domain architectures of proteins within each super-phylum in detail, starting with Euryarchaeota.

Cdv protein domains in Euryarchaeota do not constitute a common functional system

Only few Euryarchaeota showed CdvABC encoding genes, and in half of these no conserved domain sequences could be found (blue background in Fig 1). This indicates that Cdv protein genes in Euryarchaeota mutated beyond domain-recognition. Furthermore, no domains allowing interaction between proteins could be identified, making a cell-division system similar to Cdv-including mechanisms in other archaea unlikely. Instead, most of them possess multiple FtsZ homologs (S2 Table), which at least in some species were experimentally shown to be crucial for cell division [26,27], and it is widely accepted that Euryarchaeota divide by a FtsZ-based mechanisms more comparable to bacteria than other archaea [1]. Thus, our findings match to this idea that Euryarchaeota do not use a Cdv-including system for cell division. However, these proteins might still play physiological roles in machineries different from Cdv/ESCRT in TACK, Asgard and Eukaryotes.

Cdv proteins of Cren- and Thaumarchaeota are composed of different domains

In contrast to Euryarchaeota, in TACK archaea we identified CdvABC homologs in all phylogenetic orders except Thermoproteales, where it was suggested that cell division is based on the actin homolog crenactin [28], although this idea has recently been questioned [1]. Furthermore, in nearly all Cdv proteins of TACK archaea we identified specific conserved domains in the Cdv proteins, allowing comparison of domain architectures between organisms (Fig 1, green background). This comparison showed architectures that were relatively consistent within phylogenetic orders, meaning that within organisms of the same phylogenetic order homologous proteins mainly consist of the same domains. This suggests that mechanisms may be comparable between organisms of the same phylogenetic order. On the level of phyla, however, domain architecture showed distinct differences: While in all Thaumarchaeota the proteins classified as CdvA homologs were constructed of the three domains CdvA_alpha, CdvA_beta and MIM2 (or putative MIM2), in all organisms of Crenarchaeota the proteins were composed of CdvA_alpha, CdvA_beta and BWI. Furthermore, while the great majority of Crenarchaeota possessed exactly one protein with a BWH domain, classified as CdvB homolog, this domain did not occur in Thaumarchaeota at all. Importantly, BWI and BWH are known to be able to interact [16,18,19], so the joint absence or presence of the two domains indicated a mechanistical difference in the machineries of Cren- and Thaumarchaeota. To further scrutinize this finding, we next analysed which protein-protein-interactions (PPIs) may be possible based on the domain architecture in TACK archaea.

Protein domain compositions explain experimental findings indicating differences between Cren- and Thaumarchaeota

To infer PPIs, we searched in the literature which interactions the domains we had identified might allow (Figs 2 and S1). We found that four domain-pairs are experimentally shown to lead to interaction: Two of these interactions are between different domains, that is MIM2-MIT [1,18,29] and BWI-BWH [16,18,19], and two of them are between the same domains, that is Snf7-Snf7 [1,19] and Vps4_C-Vps4_C [1,22]. Furthermore, it was suggested that CdvA_beta can polymerise [18,19], but experiments on this are not conclusive [1]. Importantly, these experiments were conducted with only a selection of the organisms included in this study. Our approach here was to test whether generalisation of these interactions can lead to interesting results. Thus, we asked which interaction networks would arise if interactions were governed by domains and the interaction rules just described.

Fig 2 — Proteins are displayed as sets of building blocks, each building block representing one protein domain. Five potential domain-based interactions derived from literature are displayed in the top, grey numbers indicating the literature references where these domain-domain interactions were described. Based on the potential domain-domain interactions, protein-protein interaction networks are shown, where arrows indicate a potential interaction between two domains of the connected proteins. Literature about polymerisation of the CdvA_beta domain varies, so it is displayed in grey instead of black. The networks visualise the interactions of proteins that most likely existed in the last common ancestors of each of the three phylogenetic groups Crenarchaeota, Thaumarchaeota and Asgard archaea (see also **Fig 6**). Thus, this visualises conceptual differences between the three phylogenetic groups, and does not reflect the specific protein interactions of all organisms found today. Abbreviations and colours as in Fig 1.

In Thaumarchaeota, our approach suggested four qualitatively different potential PPIs. First, CdvA might interact with CdvC based on the MIM2 domain in CdvA and the MIT domain in CdvC. Second, the same interaction might take place between most of the CdvB homologs and CdvC. Third, most CdvB homologs might be able to polymerise at the Snf7 domain. Fourth, CdvC proteins might polymerise as well, utilizing the Vps4_C domain. In contrast, in Crenarchaeota our approach also suggested four possible PPIs, but these were based on other domains and occurred between different proteins. First, the BWI domain of CdvA might bind to the one CdvB homolog possessing a BWH domain. Second, all CdvB homologs might bind to each other and polymerise utilizing the Snf7 domain. Third, the CdvB homologs which possess a MIM2 domain might be able to interact with the MIT domain of CdvC. Fourth, CdvC might polymerise at the Vps4_C domain. Thus, there is one major difference from the suggested PPIs of Thaumarchaeota to the ones of Crenarchaeota (Fig 2): while in Thaumarchaeota the domain composition suggests that CdvA binds to CdvC, in Crenarchaeota it implies that CdvA binds to CdvB. Interestingly, this finding matches well to the differences between the two phyla found in fluorescence microscopy studies [1,5,6,16,19–21]. In the Thaumarchaeon N. maritimus, fluorescence bands of CdvA at the division site are followed by bands of CdvC, whilst in Crenarchaeota CdvA bands are followed by CdvB bands.

Thus, these previously unexplained experimental differences support our analysis of potential PPIs. Furthermore, in Crenarchaeota it was experimentally shown that CdvB homologs enrich sequentially at the division site, first the CdvB homolog possessing a BWH domain, second the CdvB homologs not possessing this domain [5]. Again, this is what the domain-architecture-based PPI inference suggests, as the enrichment is thought to be mediated by CdvA, and in our suggested PPI network only the CdvB homolog with a BWH domain can interact with CdvA. Reassured by this support from the literature, we next tried to derive mechanistical models based on the domain compositions for membrane constriction and cell division in TACK archaea, beginning with Crenarchaeota.

Mechanistical models of Cdv based cell division suggest two different systems in TACK archaea

Crenarchaeota organisms showed different numbers of CdvB homologs (Fig 1). As we wanted to derive a common mechanism for Crenarchaeota, which might be slightly adapted by individual organisms, we first had to make homologs comparable to find similarities within the phylum. Thus, we clustered the homologs by phylogeny (Fig 3) and then analysed the domain architectures within the clusters. Reassuringly, the differences in domain architecture were congruent with their phylogeny, as seen by their placement in different branches within the CdvB tree (Fig 3). Additional gene cluster analysis showed similar architectures of Cdv genes within phylogenetic branches (S2 Fig). Therefore, we defined three different classes of CdvB homologs, which we named CdvB, CdvB1/2 and CdvB3 with respect to previous work [1]. CdvB class proteins are constructed of the three domains Snf7, MIM2 and BWH, CdvB1/2 class proteins of Snf7 and MIM2, and CdvB3 class proteins of Snf7 only (Fig 1). Because this result implies that the common ancestor of all Crenarchaeota did possess these three CdvB homologs, we based our mechanistical model on these proteins (together with CdvA and CdvC). Then, to infer a mechanistical model, we first assigned one specific function to each domain (Fig 4 legend, white background), derived from literature, and defined one protein as the initiating one. Second, we analysed possible PPIs step-by-step and thereby deduced possible occurring higher order processes (Figs 4 and S1). Importantly, this is not a mathematical modelling, but a qualitative explanation.

Fig 3 — Background colours as in Fig 1 plus Eukaryotes (ESCRT-III proteins of *Homo sapiens* and *Saccharomyces cerevisiae*) in yellow, proteins schematically depicted as sets of domains as in Fig 2. In Crenarchaeota, CdvB homologs split into three phylogenetic clusters (CdvB, CdvB1/2 and CdvB3) where within each cluster most homologs have the same domain composition. In Thaumarchaeota, no clear phylogenetic clustering is visible. In Asgard archaea, CdvB homologs split into two branches, with clear differences in domain architecture between clusters. They group together with the two eukaryotic ESCRT-III groups Vps2/24/46 (CdvBa1) and Vps20/32/60 (CdvBa2), indicating a shared evolutionary history of ESCRT-III proteins in Asgard archaea and Eukaryotes. Single proteins that do not match the clusters are indicated by arrows. These might be the results of horizontal gene transfer or contamination of metagenome data. A: Two Euryarchaeota CdvB proteins (*Thermoplasa acidophilum*, UniProt ID Q9HIZ5 and *Thermoplasma volcanium*, Q97BR8). B: *Thaumarchaeon Nitrosopumilus maritimus*, A9A4K8. C: *Fervidococcus fontis*, domain architecture of a CdvB protein (Snf7 and MIM2), I0A2N3. D: *Candidatus Heimdallarchaeon*, A0A523XLA6.

In Crenarchaeota (Fig 4A), we defined CdvA as initiating protein, because it is the only protein with a potentially membrane-targeting domain, and experiments show that neither CdvB nor CdvC can bind the membrane [1,16,18,19]. Also, it has been validated that CdvA is the first protein to enrich at the division site [1,16,18,19]. As we had identified only one PPI for CdvA in Crenarchaeota, BWI-BWH, we first suggest that the CdvB class homolog binds to CdvA. This protein then has two more potential PPI options, mediated by the Snf7 and MIM2 domains. Which of these options is utilized first cannot be inferred from our analyses, so we had to consult the literature. It was shown experimentally that CdvB, CdvB1/2 and probably also CdvB3 enrich at the division site before CdvC joins [1,6]. Thus, we suggest that the affinity for the Snf7-Snf7 interaction is higher than for the MIM2-MIT interactions, and hence, that a ring-like structure composed of CdvB, CdvB1/2 and probably also CdvB3 is formed. Thus, while we cannot directly infer from our analyses why CdvB polymerisation takes place before CdvC enrichment, we can explain why CdvB enriches before CdvB1/2 and CdvB3. We strongly encourage experimentalist to compare Snf7-Snf7 and MIM2-MIT affinities to test this idea.

After the ring has been assembled at the division site, composed of CdvB homologs and tethered to the membrane by CdvA, there are two domains left to interfere with: the MIM2 domain of the CdvB class homolog and the MIM2 domain of the CdvB1/2 class homolog. As experimental data suggests that CdvB class homologs enrich before CdvB1/2 class homologs [5], we asked which structural cause this could have. The interaction is reported to take place at the short motif MIM2 [1,29]. Importantly, in the MIM2 motif of ESCRT-III there are four prolines which seem to be essential [29]. Interestingly, in the CdvB1/2 class homologs we found consistently fewer (2 instead of 4) prolines than in the CdvB class homologs (S3 Fig). Thus, it is tempting to speculate that this lower number of prolines might cause a lower affinity of the MIM2 domain in CdvB1/2 class homologs to the MIT domain in CdvC than the MIM2 domain in CdvB class homologs. This higher affinity of CdvB class homologs would be a simple mechanistical explanation of the experimental results. Giving respect to the literature, in our hypothesised mechanism we suggest that in the next step CdvC binds preferably to the CdvB class homologs in the ring at the division site.

Based on the AAA+ ATPase and Vps4_C domains of CdvC, this binding presumably results in the disassembly of the bound CdvB class homolog from the higher-order structure [1]. As more and more CdvB class homologs get disassembled, CdvC more often binds to CdvB1/2 class proteins, due to the increasing concentration, and starts disassembling them, too. Thus, the ring of homologs first becomes a ring of mostly CdvB1/2 and CdvB3 class homologs, and then gets disassembled. Once again, this is in accordance with experimental data [5]. However, we cannot explain how CdvB3 class homologs can dissociate from the division site, as we did not identify domains mediating interaction with CdvC in these homologs. Finally, how this mechanism results in membrane constriction and cell division can only be speculated, and we will suggest possible explanations in the Discussion.

In Thaumarchaeota, a classification of CdvB homologs as in Crenarchaeota was not possible. Phylogenetic and gene cluster analyses showed no clear clusters (Figs 2 and S2), and the domain composition of most homologs was the same: Snf7 and MIM2 (Fig 1). Thus, the role of different CdvB homologs in Thaumarchaeota remains unclear. Nonetheless, we were able to propose a possible mechanism based on the domain compositions (Figs 4B, 4C and S1).

Same as in Crenarchaeota, the suggested process starts with CdvA binding to the membrane and enriching at the division site. Next, CdvC binds to CdvA, utilizing the MIM2-MIT interaction. Then, there are two options: either CdvA itself had already formed a ring-like polymer at the division site, which is then disassembled in the same way as CdvB in Crenarchaeota (Fig 4B). Alternatively, CdvC functions as a linker to CdvB, which could then result in a mechanism similar to Crenarchaeota (Fig 4C). However, in the second scenario it is unclear how the higher-order structure could eventually be disassembled again, as CdvC can hardly function as a linker between CdvA and CdvB, and as a disassembler of CdvB at the same time. Therefore, we strongly prefer the first scenario, which is also supported by the diffuse distribution of CdvB in fluorescence microscopy experiments [20]. Driven by the good agreement of our inferred models with experimental data, we next used the same approach to investigate Asgard archaea.

Asgard archaea possess a system closely related to ESCRT

All investigated genomes of Asgard archaea contained at least one CdvB and one CdvC homolog, indicating their conservation within the super-phylum (Fig 1). Furthermore, in the genome of the only Asgard archaeon that could yet be cultivated and whose genome data is therefore trustworthy (Candidatus Prometheoarchaeum syntrophiculm) [12], all CdvB homologs contained either MIM1 or MIM2 domains, both of which could allow interactions with the MIT domain found in the CdvC homolog. Potential interactions between CdvBs and CdvC based on these domains in Asgard archaea were recently investigated in detail by Lu et al. [22], whose results suggest that indeed CdvC in Asgard archaea can disassemble CdvB filaments, supporting the idea of a Cdv-including mechanism comparable to other archaea in this super-phylum. Another recent experimental study further supports the idea of Cdv protein-protein interactions in Asgard archaea similar to Crenarchaeota and Eukaryotes [13].

However, to form a cell division system, this potential constriction machinery must be tethered to the membrane. But there is no CdvA homolog in Asgard archaea to achieve this, so we had to search for different ways of membrane tethering. As in our model every function of a protein is based on domains, for membrane binding there were two options: either some of the CdvB homologs in Asgard archaea possess domains that can bind to the membrane themselves (similar to ESCRT-III), or they possess a domain that can interact with another protein executing this task (similar to Crenarchaeota). Caspi and Dekker [1], who at that time had only metagenome data of a single Asgard archaeon (Lokiarchaeon sp. GC14_75) available, hypothesised that the N-terminal alpha helix similar to the ESCRT-III ANCHR motif [24] found in one Lokiarchaeon CdvB homolog might allow direct interaction with the membrane. Our analysis of multiple Asgard archaea genomes and especially that of its only cultivated member Cand. P. synthrophicum indeed revealed that this region is highly conserved within Asgard archaea, but only in the CdvBa1 subgroup of Asgard CdvB homologs (Fig 5A). Interestingly, in our phylogenetic tree this subgroup clusters with the eukaryotic Vps2/24/46 group of ESCRT-III proteins (Fig 2), which are the ESCRT-III versions that can bind to the membrane via the ANCHR motif [24]. Thus, it is plausible to assume that the membrane binding of the Vps2/24/46 ESCRT-III group is similar to the CdvBa1 group of Asgard archaea. Supporting this idea, secondary structure prediction suggested that the region forms an alpha helix, while in the CdvBa2 subgroup a conserved proline prohibits this (Fig 5). This finding strongly supports the idea of Caspi and Dekker [1] and might point to a solution to the question of membrane tethering in Asgard archaea. Furthermore, the phylogenetic relationship and structural similarity places the Cdv mechanism of Asgard archaea much closer to ESCRT in Eukaryotes than to any other archaeal Cdv-including mechanism.

Fig 5 — Predicted secondary structure is indicated by background colour, amino acids matching regular expressions of specific domains as defined in the literature are indicated by font colour. Prolines in red. Protein sequences of the different clades in the phylogeny (**Fig 3**), CdvBa1 and CdvBa2, differ mostly at the N-terminus, where in all but one sequences of CdvBa1 an alpha helix is predicted, whilst in in all CdvBa2 proteins no alpha helix is predicted. Abbreviations: LK: Lokiarchaeum sp. GC14_75, PS: Candidatus P. syntrophicum MK-D1, OD: Candidatus Odinarchaeota archaeon LCB_4, HD: Candidatus Heimdallarchaeota archaeon, TO: Candidatus Thorarchaeota archaeon (strain OWC), TA: Candidatus Thorarchaeota archaeon strain AB_25.

Based on these potential interactions, we inferred a possible mechanism of cell division in Asgard archaea (Figs 4D and S1): First, CdvBa1 proteins bind to the membrane, mediated by the ANCHR domain. Second, both CdvB paralog versions polymerise via the Snf7 domain, giving rise to a filamentous ring-like structure. Third, CdvC disassembles CdvB homologs in the same way as in TACK archaea, constricting the ring. In this final step, our model cannot distinguish whether CdvC first disassembles CdvBa1 or CdvBa2 proteins, because interaction of the proteins can take place either via MIM1-MIT interaction or MIM2-MIT interaction. Furthermore, while in Cand. P. synthrophicum the CdvBa1 paralogs seem to possess both MIM1 and MIM2 and the CdvBa2 paralog seems only to possess MIM1, in all other Asgard archaea it is the other way round. There, CdvBa1 proteins only possess MIM1 domains, while CdvBa2 proteins possess correct MIM2 motifs but only fragmented MIM1 domains (Fig 5). Thus, differences between the two groups of CdvB in Asgard archaea will have to be investigated experimentally until more high-quality data is available. Also, it might be possible that one of the interactions can lead to binding of CdvC to CdvB without subsequent disassembly.

Finally, as our results suggest mechanistically different Cdv-including mechanisms within the archaeal kingdom, we asked which evolutionary processes might have given rise to these variations and how a simple Cdv machinery in a common ancestor might have looked like. In particular, we wanted to find out if the domain architecture of such an evolutionary early machinery may have been sufficient to give rise to a cell division mechanism.

An ancestral Cdv-including machinery was probably able to perform constriction, but membrane tethering remains unclear

Based on the structure of the protein phylogenies, the domain architectures and gene cluster analysis (Figs 2, S2 and S4), we inferred an evolutionary scenario of domain reorganisation by maximum parsimony (Fig 6). Interestingly, this scenario indicates that all CdvB duplication events took place after speciation of the common ancestor into Euryarchaeota, Asgard and TACK, such that in the ‘original’ machinery there most likely was only one CdvB protein. This protein was probably composed of two domains, Snf7 and MIM2, such that it might have been able to form filaments based on the Snf7 domain. Furthermore, the scenario suggests that the common ancestor also possessed a complete CdvC protein, such that the early CdvB protein might have been able to interact with it via the MIM2 domain. Thus, it is possible that these two proteins together were already able to form a constricting ring by CdvB polymerisation and CdvC-mediated disassembly.

Fig 6 — Scenario based on phylogenetic trees (**Figs 2** and S4) and maximum parsimony. Domains displayed as blocks as in Figs 2–5.

To form a cell division machinery, though, CdvB and CdvC must have been able to attach to the cell membrane. The CdvA protein, which probably fulfils this task in TACK archaea, arose after the speciation of TACK, and the ANCHR domain, which might tether CdvB to the membrane in Asgard archaea, arose only after the speciation of Asgard (Fig 6). Thus, it is unclear how the ancient machinery might have fulfilled this task. Interestingly, the region defined as potential ANCHR in Asgard CdvB homologs is also present in TACK CdvB homologs, but it does not form an alpha helix due to a helix-breaking proline. Hence, it is possible that in the evolutionary early CdvB protein this region was functioning as a membrane tether, and that the gain of CdvA made this capability redundant or even obstructive, such that it got lost. If this is true, the ancestral machinery might have been a true cell division machinery.

Discussion

The mechanism we suggested for Crenarchaeota supports a recent study of Tarrason Risa et al. [6] which investigated the role of CdvB homologs in S. acidocaldarius. This organism possesses one protein of the CdvB class, two of the CdvB1/2 class and one of the CdvB3 class. The experiments showed that the CdvB homologs pass four distinct steps: First, the CdvB class proteins assemble at the division site to form a non-constricting ring. Second, CdvB1/2 class proteins are recruited to that ring. Third, CdvB class proteins get disassembled from the division site, leading to a ring consisting of only CdvB1/2 class proteins. Fourth, the CdvB1/2 class ring constricts. Disregarding CdvB3, this is exactly what our model indicates. While Tarrason Risa et al. described these findings but did not detail the mechanism, our study now provides a plausible scenario of how disassembly of CdvB proteins from the ring can take place and why CdvB class homologs are disassembled before CdvB1/2 class homologs. As the fluorescence microscopy experiment did not yet involve labelled CdvA and CdvC proteins, it would be interesting to see whether our model still holds true in studies investigating the full machinery.

In their paper, Tarrason Risa et al. [6] hypothesised that constriction could be the result of different preferential curvatures of CdvB and CdvB1/2 class proteins. Thus, when CdvB class proteins are removed by CdvC, the ring would shrink to the smaller preferred diameter of CdvB1/2 class proteins. Furthermore, a simulation in this study indicated that to achieve full cell division disassembly of CdvB and CdvB1/2 class homologs is needed in addition to the change in preferred curvature [6]. This explains why both CdvB and CdvB1/2 class homologs possess a MIM2 domain. Furthermore, as we found only one possible interaction for CdvB3 class homologs, namely binding to other CdvB homologs, this need of disassembly suggests that CdvB3 plays a different role. If it cannot interact with CdvC, it cannot be disassembled like CdvB and CdvB1/2. One straightforward idea for the function of CdvB3 might be that it can temporarily stabilise the ring of CdvB and CdvB1/2 homologs while or after CdvC disassembles a component. Simple knockout experiments should provide first insights into the role of CdvB3.

As CdvA was not labelled in their experiment, Tarrason Risa et al. [6] did not comment on how the ring of CdvB1/2 proteins could constrict the membrane without being able to bind to CdvA and thus not being tethered to the membrane. This might be explained by our model. Initially, CdvC mostly disassembles CdvB class proteins due to the potential higher affinity of their MIM2 domain. However, when concentrations change due to disassembly, and more and more CdvC binds to CdvB1/2 class proteins, there should be still some CdvB class proteins left. Thus, even during the final constriction stage, there should always be some remaining membrane anchors, as CdvB class proteins are never entirely removed. It will be very interesting to test the idea of different MIM2-MIT affinities.

There is, however, one result from another study which cannot be explained by our model. Based on data taken with a newly developed microscope, Pulschen et al. [5] suggested that the two different class CdvB1/2 proteins of S. acidocaldarius, called CdvB1 and CdvB2, may play different roles. While they colocalised in their experiments as expected, cells lacking CdvB1 did occasionally fail cell division, whilst cells lacking CdvB2 showed a wrongly positioned division site. As we classified them as two paralogs belonging to the same group, we cannot explain this behaviour. However, we did not investigate this in detail, as it is a specific modification in one particular subgroup of Crenarchaeota. Here, we tried to infer common shared principles, which might then be slightly adapted individually by single organisms. Furthermore, none of the proteins were essential, as would be expected from our model. Unfortunately, they did not test cells lacking both CdvB1 and CdvB2, which would be very interesting for validating the theory of membrane constriction due to different preferred curvatures. Such double-knockout experiments would greatly help understanding the mechanism of constriction.

To conclude, in this paper we stated two possible scenarios for Cdv-including cell division in Thaumarchaeota. While we strongly favour one of them, only experimental work can reveal which one comes closer to reality. As in one scenario CdvB homologs are involved, while in the other they are not, the most straightforward way to answer this question might be to knock out all CdvB homologs and see whether cell division is still possible.

While our proposed models of cell division in TACK archaea provide a theoretical basis that should inspire experimentalists to new studies, the results also show that findings in TACK archaea are only poorly transferable to the eukaryotic ESCRT system. However, we demonstrated the high potential of research in Asgard archaea, whose Cdv machinery we found to be closely related to ESCRT. Based on our results we recommend two in vitro experiments that might be possible to conduct despite the hard task of Asgard cultivation. First, as we suggested that CdvBa1 proteins can bind to the membrane via their ANCHR domain, whilst CdvBa2 proteins cannot, this should be tested in vitro to verify the central idea of our model. Second, as we could not quantify differences between CdvBa1 and CdvBa2 paralogs in their affinity to CdvC, experiments providing insight into this would greatly help to evolve the model further. In addition, a recent study by Hatano et al. [13] further suggests that at least some Asgard archaea also possess functional homologs of the additional proteins involved in the eukaryotic ESCRT machinery, ESCRT-I and ESCRT-II, and that they might be involved in ubiquitin-directed recruitment of CdvB (ESCRT-III). While we did not investigate these additional components here, as our main goal was to find similarities between all archaea that could be traced back to a very simple division machinery, this study once more emphasises the strong connection between Asgard and the eukaryotic machineries.

The close relationship between Cdv proteins in Asgard archaea and Eukaryotes further allows an interesting hypothesis about membrane binding in the ancient Cdv machinery in the common ancestor of all Cdv machineries. The potential ANCHR domain in Asgard archaea suggests that some CdvB homologs in these organisms can directly bind membranes, just as some ESCRT-III proteins in Eukaryotes. On the other hand, recent analyses of the membrane composition of Asgard archaea suggest that their lipid composition is comparable to other archaea, strongly differing from Bacteria and Eukaryotes. The important question is now whether the analogy of ANCHR motifs for membrane binding in Eukaryotes and Asgard is still valid, despite the differing lipid composition. If so, a direct membrane tethering of CdvB proteins may have occurred in the common ancestor, whose membrane probably consisted of similar lipids as archaea today. If not, it would be interesting to explore why Asgard archaea possess ANCHR domains and what task apart from membrane-binding they could serve. Some CdvB homologs in TACK archaea possess a region similar to and aligning with the region identified as ANCHR domain in Asgard homologs, but it cannot form an alpha helix due to a helix-breaking proline. As this region is present in diverged organisms, it is likely that it already existed in the common ancestor. The question is now whether it then was able to form an alpha helix to bind the membrane. If so, then the ancient machinery might have been able to function as a true cell division machinery, consisting of only two proteins.

Beyond cell biology and evolution, the reconstruction of this very simple ancient cell division machinery should be of great interest for the synthetic biology community. Bottom-up synthetic biologists try to build life from scratch, and especially to build basic functional building blocks in vitro. One such basic functional building block would be a simple system able to divide a lipid vesicle, mimicking true cell division. A synthetic system reconstituting the ancient Cdv machinery inferred by this study should be a very promising candidate for this yet unaccomplished endeavour. Especially, it will be very interesting to fabricate synthetic ESCRT-III/CdvB proteins consisting of one Snf7 and one MIM2 domain and to combine them with Vps4 or CdvC proteins in vitro, possibly even inserting them into giant unilamellar vesicles. If successful, this would depict an extremely simple system of cell division, that might be easy to study and allow interesting insights into the origin of cell division and life.

Materials and methods

Searching Cdv homologs

Archaeal proteins classified in the eggNOG [30] database as belonging to the Cdv system were used as starting points together with the proteins investigated by Makarova et al. [2] in a previous study. These included the entries ENOG4111F6A (CdvA), COG5491 (all CdvBs) and COG0464 (CdvC), corresponding to entries arCOG04054 (interestingly CdvA and B3), arCOG00452 (cdvB1/2), arCOG00453 (CdvB) and arCOG01307 (CdvC) of the archaea-only database arCOG [31]. Using the resulting set of proteins as input, a Python script was designed to run PSI-Blast [32] against the NCBI protein [33] database (v2020-11-11). Default parameters were used except that the scoring matrix was set to BLOSUM45 [34] due to the distant relationships. Then, Python scripts were written to eliminate all hits from organisms with unclear phylogeny, organisms with fragmented genome data, results of marine sediment probes and duplicates from different strains of the same species. Only in Asgard archaea incomplete genomes were accepted and multiple strains included, because all available data is incomplete except for Cand. P. syntrophicum. Hits to CdvC homologs were then further analysed because the AAA+ ATPase region is widely spread amongst many different proteins and accounts for most of the sequence of CdvC proteins. Thus, many false positive hits that are no true CdvC homologs could be expected. Only sequences that possessed at least a VPS4_C or a MIT region were further selected (exception: F. acidarmanus, because it is part of the arCOG01307 entry and had a very good PSI-Blast E-Score of 2e-48). Finally, proteins in close genomic neighbourhood of all finally selected proteins were checked whether they may depict overseen homologs. Eventually, 37 organisms remained and were selected for further analysis. The set of proteins can be found in S2 Table (which also includes FtsZ proteins).

Fragmenting protein sequences into domains

To fragment protein sequences into domains we used two different approaches. On one hand, we used available software tools to scan the proteins’ sequences for domains that are described in public databases. For scanning against the Pfam [35] and InterPro [36] databases we used the InterProScan [37] software, while for scanning against the CDD [38] database we used a custom Python script connecting to the online API of the database. The resulting data files were then processed to summarise hits that represented the same domains or were sub-parts of a larger domain. This led to the identification of the domains CdvA_alpha, BWH, Snf7, MIT, AAA+ ATPase and Vps4_C. On the other hand, we had to check for domains and short conserved motifs which are not defined in the three mentioned databases. For this, we generated multiple sequence alignments and predicted the secondary structure of the proteins. We then inspected the results manually for regions with high sequence conservation and consistent predicted secondary structure, which led to the identification of a beta-sheet rich region in TACK archaeota CdvA proteins, a single conserved beta-sheet in Crenarchaeota CdvA proteins, and the conserved alpha helices in Asgard CdvB proteins. As the beta-sheet rich region in CdvA proteins was previously described as a functional region [1,16,18,19], we labelled it as a unique domain, named CdvA_beta. Similarly, the conserved single beta-sheet in Crenarchaeota CdvA proteins was previously described as functional region for interaction with the BWH domain in CdvB [18], so we classified this as domain, named BWH interaction site (BWI). Furthermore, inspired by Caspi and Dekker [1] and Lu et al. [22], we then compared the conserved regions in Asgard archaea to the N-terminal ANCHR domain [24] and the C-terminal MIM1 domain [23] occurring in some ESCRT-III proteins (Fig 5). This led to the identification of the ANCHR and MIM1 domains. Finally, based on the work of Kojima et al. [29] and Samson et al. [18], a python script was generated to search for the MIM2 motif by regular expressions. Three different kinds of MIM2 were defined: MIM2_Core = φPxφP, MIM2_total = MIM2_Core + xxPφP and MIM2_Sulf = xφxxφφPx + MIM2_Core, where φ represents hydrophobic amino acids [AILMFVPGW], x represents charged amino acids [RKDE] and P is proline. In the two Thaumarchaeota Nitrososphaera viennensis and Candidatus Nitrosphaera gargensis we classified a proline-rich region as ‘putative MIM2’, although not perfectly fitting to the regular expressions. This is justified because they aligned to the proline rich regions of the Thaumarchaeota possessing a full MIM2 motif, they did not show other proline-rich regions and the structural limitations of MIT-MIM2 interaction are unknown despite being based on proline. Taken together, these analyses led to the eleven basic building blocks that are utilized in the Cdv system. S1 Table provides an overview of the exact location of the domains on the proteins.

Multiple sequence alignment and secondary structure prediction

The Multiple Alignment tool MAFFT [39] was used for sequence alignment. For proteins belonging to different super-phyla (different background colours in Fig 1) the substitution matrix BLOSUM45 [34] was used, for alignment of proteins of the same super-phyla BLOSUM62 [34]. The exact command-line instruction was

mafft—bl 45 (or 62)—localpair—maxiterate 1000—reorder input.fasta > output.fasta.

Secondary structure prediction based on multiple sequence alignment was executed with JPred [40] using default parameters.

Phylogenetic analysis

Based on the multiple sequence alignments, Bayesian phylogenetics was used to generate phylogenetic trees. The software Mr. Bayes [41] was run with a chain length of 1,000,000, a subsample frequency of 1,000, a burn-in length of 100,000, gamma rate variation with 4 categories and a Poisson rate matrix. The resulting effective sample size was 213 resp. 181.

Mechanism inference

Each protein was abstracted as a combination of domains (Figs 1, 4 and S1). Based on literature, each domain was assigned a specific function (Fig 4). Then, networks of possible interactions were built, based on potential interactions derived from the literature (Figs 3 and S1). To infer a potential mechanism based on these interaction networks, one starting protein was selected for each mechanism. In TACK archaea, CdvA homologs were selected, because fluorescence microscopy studies indicate that they enrich first at the division site (1,6,18). Also, they are the only Cdv proteins able to bind the membrane in TACK archaea, and they possess a CdvA_beta domain, which we did not assume to interact with other Cdv proteins. Thus, this domain has the potential to be involved in the positioning of CdvA. Neither CdvB homologs nor CdvC did show such “unused” domains in TACK archaea, so if instead these proteins would enrich first at the division site, we could not explain this by domain architecture. In Asgard archaea, we selected CdvBa1 as starting protein, because it is potentially able to bind membranes. However, it is of course possible that instead CdvBa2 enriches first. This would change the order of appearance, but the overall assumed mechanism of polymerisation, membrane binding and CdvC mediated depolymerisation would still hold.

The subsequent process of mechanism inference is visualised in S1 Fig. After selecting a starting protein, we analysed which interactions were possible for this protein. If only one interaction was possible, we assumed this to occur as a next step. If more than one interaction was possible, we tried to infer which interaction might have a higher affinity, and thus would occur more quickly. If this was not possible, we inferred different scenarios. These steps were then executed recursively. The resulting mechanisms were then summarized and simplified to the mechanisms displayed in Fig 1.

Code availability

The used data and python scripts are available at a public GitHub repository (https://github.com/BelaFrohn/ArchaealESCRTDomains).

Limitations of the study

The study is purely computational with the goal to generate hypotheses that can be tested experimentally. Thus, the described mechanistical models are suggestions and must be validated experimentally. Furthermore, we based our analysis purely on domain analysis, so any functional changes that result from small sequence or structural alterations that are not reflected in domain architecture are not incorporated in our models. Such small alterations most likely cause small functional differences between highly similar homologs, hence between closely related organisms. Consequentially, our analysis cannot draw detailed conclusions about single particular organisms. We were interested in general principles, whose implementation in distinct organisms might differ slightly. To infer explicit models for single organisms, more detailed structural modelling of the involved proteins is necessary.

Supporting information

S1 Fig. Interactions underlying the suggested mechanisms.

In Crenarchaeota, the potential polymerisation capabilities of CdvA and CdvC are not displayed as they do not help explain the suggested mechanism. In Asgard archaea, the CdvC polymerisation capability is likewise not displayed. Background colours indicate phylogenetic groups. Red: Asgard archaea, dark green: Thaumarchaeota, pale green: Crenarchaeota.

(TIF)

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S2 Fig. Cluster analysis of Cdv genes in archaea.

Organisms are grouped by phylogeny. Genes encoding CdvA, CdvB and CdvC are in direct neighbourhood in Crenarchaeota. In Thaumarchaeota, in three out of four organisms one CdvB homolog gene is in close neighbourhood to the CdvC gene. CdvA homologs are not. In Euryarchaeota, if there are genes encoding both CdvB and CdvC homologs, they are either in direct or in relatively close neighbourhood. In Asgard archaea, except in Cand. P. syntrophicum only fragmentary genomes are available. In three out of six Asgard archaea genomes CdvC and CdvB homolog genes are in close neighbourhood. This pattern across all archaeal phyla indicates that indeed CdvC and one CdvB homolog existed in the last common ancestor of TACK, Asgard and Euryarchaeota.

(TIF)

Click here for additional data file.^{(264.4KB, tif)}

S3 Fig. Multiple Alignments of the MIM2 domain in CdvB and CdvB1/2 proteins.

In CdvB1/2 proteins the MIM2 domain contains consistently fewer prolines, indicating a weaker affinity to the MIT domain than the MIM2 of CdvB proteins. Abbreviations: AP: Aeropyrum pernix, AS: Acidilobus saccharovorans, PO: Pyrodictium occultum, HB: Hyperthermus butylicus, AH: Acidianus hospitalis, AM: Acidianus manzaensis, AS: Acidianus sulfidivorans, SI: Sulfolobus islandicus, SS: Saccharolobus solfataricus, SA: Sulfolobus acidocaldarius, ST: Sulfurisphaera tokodaii, MS: Metallosphaera sedula, FF: Fervidicoccus fontis, DA: Desulfurococcus amylolyticus, SM: Staphylothermus marinus, CL: Caldisphaeralagunensis, IH: Ignicoccus hospitalis.

(TIF)

Click here for additional data file.^{(659.2KB, tif)}

S4 Fig. Phylogenetic Tree of CdvC proteins.

The overall structure shows the same phylogenetic relations as the CdvB tree (Fig 2): Asgard archaea are located between Euryarchaeota and Crenarchaeota, while Thaumarchaeota are most distant from Asgard archaea. However, the Euryarchaeota group of Thermoplasma is not located near all other Euryarchaeota but between Asgard archaea and TACK archaea. This might be an artifact because the proteins in Thermoplasma mutated massively and maybe gained an entirely new function (the branch is the longest in the whole phylogeny), or it might be caused by horizontal gene transfer. Background colours indicate phylogenetic groups. Blue: Euryarchaeota, red: Asgard archaea, dark green: Thaumarchaeota, pale green: Crenarchaeota. Numbers indicate posterior probabilities.

(TIF)

Click here for additional data file.^{(1MB, tif)}

S1 Table. Domain locations of the investigated proteins.

(XLSX)

Click here for additional data file.^{(20.5KB, xlsx)}

S2 Table. Protein and gene data of the investigated proteins.

(CSV)

Click here for additional data file.^{(51.2KB, csv)}

Acknowledgments

We thank Dina Grohmann (University of Regensburg) and Henri Franquelim for helpful feedback on the paper. B.F. is supported by the Graduate School of Quantitative Biosciences Munich (QBM).

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

References

1.Caspi Y, Dekker C. Dividing the Archaeal Way: The Ancient Cdv Cell-Division Machinery. Front Microbiol. 2018. Mar 2;9:174. Available from: http://journal.frontiersin.org/article/10.3389/fmicb.2018.00174/full. doi: 10.3389/fmicb.2018.00174 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Makarova KS, Yutin N, Bell SD, Koonin E V. Evolution of diverse cell division and vesicle formation systems in Archaea. Nat Rev Microbiol. 2010; 8(10):731–741. doi: 10.1038/nrmicro2406 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Lindås A-C, Karlsson EA, Lindgren MT, Ettema TJG, Bernander R. A unique cell division machinery in the Archaea. Proc Natl Acad Sci U S A. 2008. Dec 2;105(48):18942–6. doi: 10.1073/pnas.0809467105 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Samson RY, Obita T, Freund SM, Williams RL, Bell SD. A role for the ESCRT system in cell division in archaea. Science 2008;322(5908):1710–1713. doi: 10.1126/science.1165322 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Pulschen AA, Mutavchiev DR, Culley S, Sebastian KN, Roubinet J, Roubinet M, et al. Live Imaging of a Hyperthermophilic Archaeon Reveals Distinct Roles for Two ESCRT-III Homologs in Ensuring a Robust and Symmetric Division. Curr Biol. 2020; 30(14):2852–2859.e4. doi: 10.1016/j.cub.2020.05.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Tarrason Risa G, Hurtig F, Bray S, Hafner AE, Harker-Kirschneck L, Faull P, et al. The proteasome controls ESCRT-III-mediated cell division in an archaeon. Science. 2020; 369(6504):eaaz2532. doi: 10.1126/science.aaz2532 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Sadler JBA, Wenzel DM, Williams LK, Guindo-Martínez M, Alam SL, Mercader JM, et al. A cancer-associated polymorphism in ESCRT-III disrupts the abscission checkpoint and promotes genome instability. Proc Natl Acad Sci U S A. 2018; 115(38):E8900–E8908. doi: 10.1073/pnas.1805504115 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Votteler J, Sundquist WI. Virus budding and the ESCRT pathway. Cell Host and Microbe. 2013; 14(3):232–241. doi: 10.1016/j.chom.2013.08.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Lee JA, Beigneux A, Ahmad ST, Young SG, Gao FB. ESCRT-III Dysfunction Causes Autophagosome Accumulation and Neurodegeneration. Curr Biol. 2007. [published correction appears in Curr Biol. 2007 Sep 18;17(18):1622]; 17(18):1561–1567. doi: 10.1016/j.cub.2007.07.029 [DOI] [PubMed] [Google Scholar]
10.Eme L, Spang A, Lombard J, Stairs CW, Ettema TJG. Archaea and the origin of eukaryotes. Nature Reviews Microbiology. 2017; 15(12):711–723. doi: 10.1038/nrmicro.2017.133 [DOI] [PubMed] [Google Scholar]
11.Adam PS, Borrel G, Brochier-Armanet C, Gribaldo S. The growing tree of Archaea: new perspectives on their diversity, evolution and ecology. ISME J. 2017. Nov 4;11(11):2407–25. Available from: http://www.nature.com/articles/ismej2017122. doi: 10.1038/ismej.2017.122 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Imachi H, Nobu MK, Nakahara N, Morono Y, Ogawara M, Takaki Y, et al. Isolation of an archaeon at the prokaryote–eukaryote interface. Nature. 2020; 577(7791):519–525. doi: 10.1038/s41586-019-1916-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Hatano T, Palani S, Papatziamou D, Souza DP, Salzer R, Tamarit D, et al. Characterisation of the Ubiquitin-ESCRT pathway in Asgard archaea sheds new light on origins of membrane trafficking in eukaryotes. bioRxiv [Preprint]. 2021. Aug 17; 2021.08.17.456605. Available from: https://www.biorxiv.org/content/10.1101/2021.08.17.456605v1. [Google Scholar]
14.Nachmias D, Melnikov N, Zorea A, De-picchoto Y, Zarivach R, Mizrahi I, et al. Asgard ESCRT-III and VPS4 reveal evolutionary conserved chromatin binding properties of the ESCRT machinery. bioRxiv [Preprint]. 2021. Nov 29;2021.11.29.470303. Available from: https://www.biorxiv.org/content/10.1101/2021.11.29.470303v1. [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Zaremba-Niedzwiedzka K, Caceres EF, Saw JH, Bäckström D, Juzokaite L, Vancaester E, et al. Asgard archaea illuminate the origin of eukaryotic cellular complexity. Nature. 2017. Jan 19;541(7637):353–8. Available from: http://www.nature.com/articles/nature21031. doi: 10.1038/nature21031 [DOI] [PubMed] [Google Scholar]
16.Moriscot C, Gribaldo S, Jault JM, Krupovic M, Arnaud J, Jamin M, et al. Crenarchaeal CdvA forms double-helical filaments containing DNA and interacts with ESCRT-III-like CdvB. PLoS One. 2011;6(7):e21921. doi: 10.1371/journal.pone.0021921 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Bernander R, Ettema TJ. FtsZ-less cell division in archaea and bacteria. Curr Opin Microbiol. 2010. Dec;13(6):747–52. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1369527410001669. doi: 10.1016/j.mib.2010.10.005 [DOI] [PubMed] [Google Scholar]
18.Samson RY, Obita T, Hodgson B, Shaw MK, Chong PL-G, Williams RL, et al. Molecular and structural basis of ESCRT-III recruitment to membranes during archaeal cell division. Mol Cell. 2011. Jan;41(2):186–96. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1097276510010038. doi: 10.1016/j.molcel.2010.12.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Dobro MJ, Samson RY, Yu Z, McCullough J, Ding HJ, Chong PL-G, et al. Electron cryotomography of ESCRT assemblies and dividing Sulfolobus cells suggests that spiraling filaments are involved in membrane scission. Mol Biol Cell. 2013. Aug;24(15):2319–27. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23761076. doi: 10.1091/mbc.E12-11-0785 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Pelve EA, Lindås AC, Martens-Habbena W, de la Torre JR, Stahl DA, Bernander R. Cdv-based cell division and cell cycle organization in the thaumarchaeon Nitrosopumilus maritimus. Mol Microbiol. 2011; 82(3):555–566. doi: 10.1111/j.1365-2958.2011.07834.x [DOI] [PubMed] [Google Scholar]
21.Ng K-H, Srinivas V, Srinivasan R, Balasubramanian M. The Nitrosopumilus maritimus CdvB, but not FtsZ, assembles into polymers. Archaea. 2013;2013:104147. doi: 10.1155/2013/104147 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Lu Z, Fu T, Li T, Liu Y, Zhang S, Li J, et al. Coevolution of eukaryote-like vps4 and ESCRT-III subunits in the asgard archaea. MBio. 2020; 11(3):e00417–20. Published 2020 May 19. doi: 10.1128/mBio.00417-20 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Sciskala B, Kölling R. Interaction maps of the Saccharomyces cerevisiae ESCRT-III protein Snf7. Eukaryot Cell. 2013;12(11):1538–1546. doi: 10.1128/EC.00241-13 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Buchkovich NJ, Henne WM, Tang S, Emr SD. Essential N-Terminal insertion motif anchors the ESCRT-III filament during MVB vesicle formation. Dev Cell. 2013; 27(2):201–214. doi: 10.1016/j.devcel.2013.09.009 [DOI] [PubMed] [Google Scholar]
25.Schoch CL, Ciufo S, Domrachev M, Hotton CL, Kannan S, Khovanskaya R, et al. NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database (Oxford). 2020;2020. doi: 10.1093/database/baaa062 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Liao Y, Ithurbide S, Evenhuis C, Löwe J, Duggin IG. Cell division in the archaeon Haloferax volcanii relies on two FtsZ proteins with distinct functions in division ring assembly and constriction. Nat Microbiol. 2021. May 1;6(5):594–605. doi: 10.1038/s41564-021-00894-z [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Pende N, Sogues A, Megrian D, Sartori-Rupp A, England P, Palabikyan H, et al. SepF is the FtsZ anchor in archaea, with features of an ancestral cell division system. Nat Commun. 2021. Dec 1;12(1). doi: 10.1038/s41467-021-23099-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Izoré T, Kureisaite-Ciziene D, McLaughlin SH, Löwe J. Crenactin forms actin-like double helical filaments regulated by arcadin-2. Elife. 2016. Nov 17;5. doi: 10.7554/eLife.21600 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Kojima R, Obita T, Onoue K, Mizuguchi M. Structural Fine-Tuning of MIT-Interacting Motif 2 (MIM2) and Allosteric Regulation of ESCRT-III by Vps4 in Yeast. J Mol Biol. 2016; 428(11):2392–2404. doi: 10.1016/j.jmb.2016.04.007 [DOI] [PubMed] [Google Scholar]
30.Huerta-Cepas J, Szklarczyk D, Heller D, Hernández-Plaza A, Forslund SK, Cook H, et al. EggNOG 5.0: A hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 2019; 47(D1):D309–D314. doi: 10.1093/nar/gky1085 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Makarova KS, Wolf YI, Koonin E V. Archaeal clusters of orthologous genes (arCOGs): An update and application for analysis of shared features between thermococcales, methanococcales, and methanobacteriales. Life. 2015; 5(1):818–840. Published 2015 Mar 10. doi: 10.3390/life5010818 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Research. 1997; 25(17):3389–3402. doi: 10.1093/nar/25.17.3389 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Agarwala R, Barrett T, Beck J, Benson DA, Bollin C, Bolton E, et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2016; 46(D1):D8–D13. doi: 10.1093/nar/gkv1290 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Mount DW. Using BLOSUM in Sequence Alignments. Cold Spring Harb Protoc. 2008. Jun 1;2008(6):pdb.top39–pdb.top39. doi: 10.1101/pdb.top39 [DOI] [PubMed] [Google Scholar]
35.Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, et al. Pfam: The protein families database. Nucleic Acids Research. 2014; 42(Database issue):D222–D230. doi: 10.1093/nar/gkt1223 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Mitchell AL, Attwood TK, Babbitt PC, Blum M, Bork P, Bridge A, et al. InterPro in 2019: Improving coverage, classification and access to protein sequence annotations. Nucleic Acids Res. 2019; 47(D1):D351–D360. doi: 10.1093/nar/gky1100 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Jones P, Binns D, Chang HY, Fraser M, Li W, McAnulla C, et al. InterProScan 5: Genome-scale protein function classification. Bioinformatics. 2014; 30(9):1236–1240. doi: 10.1093/bioinformatics/btu031 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Marchler-Bauer A, Derbyshire MK, Gonzales NR, Lu S, Chitsaz F, Geer LY, et al. CDD: NCBI’s conserved domain database. Nucleic Acids Res. 2015; 43(Database issue):D222–D226. doi: 10.1093/nar/gku1221 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Katoh K, Misawa K, Kuma K, Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 2002. Jul 15;30(14):3059–66. doi: 10.1093/nar/gkf436 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Drozdetskiy A, Cole C, Procter J, Barton GJ. JPred4: A protein secondary structure prediction server. Nucleic Acids Res. 2015; 43(W1):W389–W394. doi: 10.1093/nar/gkv332 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S, et al. MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space. Syst Biol. 2012. May 1;61(3):539–42. doi: 10.1093/sysbio/sys029 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0266395.r001

Decision Letter 0

Ernesto Perez-Rueda

5 Jan 2022

PONE-D-21-29711

Tracing back variations in archaeal cell division to protein domain architectures

PLOS ONE

Dear Dr. Cox,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: N/A

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: No

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors discuss an important topic in the article, such as the cell division machinery in Archaea, with a specific focus on the component of the Endosomal Sorting Complex Required for Transport. They employed a bioinformatics technique to develop their investigation at the level of domains and protein motifs in the homologous sequences of a group of Archaea.

The study has a good development; however, several questions emerge from the text that must be addressed before the study is accepted for publishing.

The greatest problem emerges in sentences like:

142

230-234

318-321

where, despite the fact that it is entirely bioinformatic study, additional analyses are required to allow consolidation of their considerations

Some other considerations are listed below.

In 131: They selected 37 organisms for their analysis. But in Figure 1 and Suppl. Table 1. The set of organisms that they present corresponds to a set of 51 organisms.

In 133: CDD needs to be defined the first time it is used.

In 135: Figure 1B does not contain the eleven domains that they describe in the text.

In general, figure captions are very extensive and tend to repeat information from the main text. As a result, they should be reorganized in general.

In this context, Figure 1 includes too much information forcing the transfer of a component to Figure 3. It is preferable to create one more figure that makes the information more clear; this will help to better understand the phylogenetic information. Finally, the legend of the figure must be written in a sequential manner and must avoid discussing portion B) at the conclusion.

They indicate that CDv genes are identified in just a few species in the case of Euryarchaeota. It would be interesting to study if these remaining genes have been subjected to relaxed selection pressures. To back up the decision expressed in lines 200-202.

In 238, change T to t.

If the interactions described are previously known, the section 230-242 should be appropriately cited, and if they are the results of the study, further proof of these interactions should be provided.

Regarding figure 2, it is unclear if the phylogeny was constructed using the 37 organisms or the 51 in figure 1, and how the organisms in the Eukaryotic clades were chosen. Check the Eukaryotic typeface in figure 2.

Figure 3 shows the domain table with information that is duplicated from Figure 1B.

Although the article does not focus on other types of machinery, it would be preferable for the authors to address more fully what happens with organisms that do not conserve CDv genes.

Finally, all data, including scripts, should be included as supplemental material or deposited in a freely accessible repository.

Reviewer #2: Cox et al. present a detailed in silico characterization and bibliographic revision of the proteins of archaeal ESCRT machineries (i.e. CdvABC) and compares them with their better described Eukaryotic counterparts to infer a series of models for the mechanisms by which these might be involved in cell division withing the Euryarchaeota, Asgard and TACK super-phyla. Also, by finding similarities between all archaea that could be traced back to a very simple division machinery, this study adds yet another piece of evidence for the close relationship between Asgard and the eukaryotic machineries.

Overall the rational of the authors is sound and it was a very pleasant read for someone the is not a specialist in Archaeal cell division mechanisms. This mauscript builds upon the work of Tarrason Risaet et al. (2020) and the models presented here seem like a step in the correct direction regarding the mechanistic characterization of the CdvABC proteins. However, I would like to ask for the authors to create and share with us a robust and reproducible (bioinformatic) algorithm or tool (script) to identify Archaeal CdvABC proteins. While reading their methods it sometimes feels like they are cherry-picking some protein sequences and discarding others. That is only the feeling I get when reading this version of the manuscript and I would greatly appreciate something like a validated HMM that could be offered to the community for these Archaeal proteins.

General comments

Are the assignments of the protein domains described in the article similar to what tools like InterPro scan reveal as output using HMMs? and, if no Pfam model were available. would it be possible to obtain the same results when creating HMMs using your set of known domains instead of regular expressions?

I would ultimately like to know if your approach is as sensitive and/or robust as the extensive use of HMMs to determine a proteomic domain or motif.

Resolution of the Figures I reviewed was very low and I hope that this is due to the Plos review platform and not the authors’ design. Figures 1 and 3 are a vital component of this article and should have exceptional resolution to offer the most needed aid the reader requires to understand the different variations of the CdvABC secondary structures and their proposed mechanisms.

Please note that major parts of the “Figure legends” should be moved to the “Results” or “Discussion” sections of the main text as descriptions of the outcome of your analysis, and not as the caption describing the figure to the reader.

Specific comments

In line no. 14 “... This spread across super-phyla suggests that…” Archaea and Eukaryotes have the taxonomic rank of “Domains” of life, not “Super-phyla”, specify that you assessed “super-phyla within these Domains”.

In line no. 68 “... After the discovery of CdvA, -B and -C in S. acidocaldarius, …” Better refer to these three proteins as “CdvABC” here and below.

In line no. 82 “... concept as one highly refined version of the Asgard Cdv system. This relationship emphasizes that it is necessary to investigate archaeal Cdv machineries in addition to eukaryotic ESCRT machineries to draw conclusions about the ancestral machinery.”

This phrase would read better if written something like:

In line no. 101 “... On the one hand, experimental studies with archaeal Cdv machineries are technically highly challenging, due to the extreme conditions archaeal organisms thrive under. On the other hand,...” These phrases would read better if you started them with “First” and Second” instead of “on one hand and on the other”.

In line no. 150 “... Thus, this simple analysis already yielded two interesting results: First, four domains are shared between all organisms…” Please constrain the extent of your findings to “all genomes included in this analysis” instead of “all organisms”.

In line no. 161 I recommend a more universal color name instead of “Khaki”, such as “yellow” or “pale yellow”.

In Figure 1A legend please move to the Results section descriptions of the outcome of your analysis, such as those from line no. 163 “Differing domain patterns matching the phylogenetic groups are clearly visible…” to line no. 177. There are more phrases further below that can also be moved to results instead of the figure caption.

248 “Thus, these previously unexplained experimental differences fit nicely to our analysis of potential PPIs.” I suggest changing “fit nicely” with “are further supported by” or something similar.

Please rephrase line no. 249 “potential PPIs. Furthermore, it was observed that in Crenarchaeota it is indeed the CdvB homolog with the BWH domain that enriches first, followed by the other CdvB homologs (5).”

In line no. 261 “Reassuringly, the differences in domain architecture fitted perfectly to the phylogenetic clusters (Figure 2).” change to something like “... were congruent with their phylogeny, as seen by their placement in different branches within the CdvB tree”

Please tone down the following phrase (that should be in Results section and not as part of a Figure legend) to clarify that this is an hypothetical explanation derived from your data (e.g. “Our data supports that…”): in line no. 277 “This means that all interactions between different CdvB homologs developed independently and are therefore not comparable.”

Text from line 276 to 286 should be incorporated to the “Results” or “Discussion” sections of the main text as descriptions of the outcome of your analysis

Please change line no. 380 “Our analysis of multiple Asgard archaea genomes and especially the trustworthy Cand. P. synthrophicum genome…” with something like “Our analysis of multiple Asgard archaea genomes and especially that of its only cultivated member Cand. P. synthrophicum…”

Text from line 399 to 406 should be incorporated to the “Results” or “Discussion” sections of the main text as descriptions of the outcome of your analysis

Text from line 461 to 467 should be incorporated to the “Results” or “Discussion” sections of the main text as descriptions of the outcome of your analysis

Please change in line no. 481 “The mechanism we suggested for Crenarchaeota fits nicely to a recent study of Tarrason Risa et al. (6)” with “... further supports the recent study of…”

In line no. 594 “... to run PSI-Blast (27) against the NCBI protein (28) database.” Please specify which NCBI database version you used (e.g. v2021-12-20)

In line no. 610 “Decomposing proteins into domains” Please consider changing this to “Fragmented analysis of protein domains” or something like that (here and along all the methods section below)

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Reviewer #1: No

Reviewer #2: Yes: Alvaro M. Plominsky

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PLoS One. 2022 Mar 31;17(3):e0266395. doi: 10.1371/journal.pone.0266395.r002

Author response to Decision Letter 0

15 Feb 2022

Our replies are contained in the uploaded document Response to Reviewers.pdf.

Attachment

Submitted filename: Response to Reviewers.pdf

Click here for additional data file.^{(140.3KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0266395.r003

Decision Letter 1

Ernesto Perez-Rueda

21 Mar 2022

Tracing back variations in archaeal ESCRT-based cell division to protein domain architectures

PONE-D-21-29711R1

Dear Dr. Cox,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

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Kind regards,

Ernesto Perez-Rueda

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: N/A

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

Reviewer #2: General comments

I liked the current experimental design and bioinformatic analysis supporting the nice findings the authors made. The logic was sound and the authors propose a guide as well as interesting challenges for experimental biologists to test.

I noticed that the quality of the manuscript increased notably after line 190. Please revise the writing for the first 190 lines again as there are better ways to present your ideas and the results of your work. I gave some recommendations but this is not an exhaustive list.

The resolution of the Figures I reviewed was very low, but I downloaded Figures from the github associated with this article and all figures were clear and high quality. Please make sure that quality is translated into the final article version. All main Figures are a vital component of this article and should have exceptionally high resolution to offer the most needed aid the reader requires to understand the presence/absence of Cdv proteins in the various taxa and the different variations of the CdvABC domains and their proposed interactions.

Specific comments

In line no. 57 “... because a comparative approach investigating similarities of machineries derived from the same ancestor is the more interesting the more different descendants are included.” I suggest changing to “... would offer more significant insight when including a higher diversity of descendants in the analysis.”

In line no 67 “... Thus, there are both similarities and differences in the composition of the machineries, fitting to the hypothesis that they derived from a common ancestral machinery but evolved differently.” I suggest changing to “... supporting the hypothesis that they derived from a common ancestral machinery…”

In line no 71 “... Interestingly, for which of the three proteins homologs were found was closely related to the phylogeny of Archaea.” I suggest removing that sentence.

In line no 82 “... phyla once more indicate that there was once an ancient Cdv/ESCRT machinery that has been adapted differently.” I suggest changing to “... evolved differently.”

In line no 85 “... This idea emphasizes that if one wants to draw conclusions about an ancestral ESCRT machinery, it is essential to investigate archaeal Cdv machineries in addition to eukaryotic ESCRT machineries.” I suggest changing to “... This idea emphasizes the relevance of studying archaeal Cdv machineries to increase our understanding of ancestral versions of the eukaryotic ESCRT machineries.”

In line no 114-119 “... This is inspired by the idea that the mechanism of a protein machinery is a result of the interactions between the proteins, and that these interactions are located at specific regions of the proteins’ amino acid sequences. We show that CdvABC homologs in Cren- and Thaumarchaeota differ in their domain compositions and that the different interactions of the proteins caused by these different compositions have the potential to explain the variations found in experiments.” I suggest changing to “... and that these interactions occur at specific regions of their amino acid sequences… and that the distinctive interactions of the proteins caused by these different compositions might explain the previously observed experimental variations.”

In line no 134-139 (sentence is too long) I suggest changing it to something like: “... From the resulting list of organisms containing at least one CdvABC homolog we selected 37 organisms based on the high quality of their genomic information. The secondary structure of the Cdv protein architecture from these selected genomes was analyzed by processing them through Pfam, InterPro, CDD, and utilizing previously reported regular expressions to identify domains of interest. Hereafter we will call all regions in the amino acid sequences of proteins that are expected to execute a distinct function ‘domains’, although strictly speaking some are only motifs.”

In line no 155-156 “... First, four domains are shared between all organisms included in this study, which suggests that the common ancestor of Cdv-including systems might have utilized these domains.” I suggest changing to “..., which suggests that the Cdv present in their common ancestor likely presented these domains.”

In line no 181-183 It’s better not to speculate on what evolutionary event was responsible for mutating the Euryarchaeota cdv genes if you are not going to test these hypotheses. Just state they “... mutated beyond recognition.”

In line no 184-185 “Furthermore, no domains allowing interaction between proteins could be identified, making a system similar to Cdv-including mechanisms in other archaea unlikely.” I suggest changing to something like “... Furthermore, no domains allowing interaction between proteins could be identified. Thus, suggesting that Euryarchaeota likely have a different mechanism for cell division.”

Please make the “Crenarchaeota” label under its corresponding set of interaction models in Fig. 2 more visible (darker) because it was barely notable in the figure set I received to review.

In line no 325 “...Which of these options is utilised first cannot be inferred from our analyses…” change to “utilized”

In line no 367 “...Next, CdvC binds to CdvA, utilising the MIM2-MIT interaction.” change to “utilizing”.

In line no 605 “...(exception: F. acidarmanus, because it is part of the arCOG01307 entry and had a very good PSI-Blast score).” Please specify the score instead of saying it is “very good”.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Edgardo Galán-Vásquez

Reviewer #2: Yes: Alvaro M. Plominsky

PLoS One. doi: 10.1371/journal.pone.0266395.r004

Acceptance letter

Ernesto Perez-Rueda

23 Mar 2022

PONE-D-21-29711R1

Tracing back variations in archaeal ESCRT-based cell division to protein domain architectures

Dear Dr. Cox:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ernesto Perez-Rueda

Academic Editor

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Interactions underlying the suggested mechanisms.

(TIF)

Click here for additional data file.^{(263.9KB, tif)}

S2 Fig. Cluster analysis of Cdv genes in archaea.

(TIF)

Click here for additional data file.^{(264.4KB, tif)}

S3 Fig. Multiple Alignments of the MIM2 domain in CdvB and CdvB1/2 proteins.

(TIF)

Click here for additional data file.^{(659.2KB, tif)}

S4 Fig. Phylogenetic Tree of CdvC proteins.

(TIF)

Click here for additional data file.^{(1MB, tif)}

S1 Table. Domain locations of the investigated proteins.

(XLSX)

Click here for additional data file.^{(20.5KB, xlsx)}

S2 Table. Protein and gene data of the investigated proteins.

(CSV)

Click here for additional data file.^{(51.2KB, csv)}

Attachment

Submitted filename: Response to Reviewers.pdf

Click here for additional data file.^{(140.3KB, pdf)}

Data Availability Statement

All relevant data are within the paper and its Supporting Information files.

[pone.0266395.ref001] 1.Caspi Y, Dekker C. Dividing the Archaeal Way: The Ancient Cdv Cell-Division Machinery. Front Microbiol. 2018. Mar 2;9:174. Available from: http://journal.frontiersin.org/article/10.3389/fmicb.2018.00174/full. doi: 10.3389/fmicb.2018.00174 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref002] 2.Makarova KS, Yutin N, Bell SD, Koonin E V. Evolution of diverse cell division and vesicle formation systems in Archaea. Nat Rev Microbiol. 2010; 8(10):731–741. doi: 10.1038/nrmicro2406 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref003] 3.Lindås A-C, Karlsson EA, Lindgren MT, Ettema TJG, Bernander R. A unique cell division machinery in the Archaea. Proc Natl Acad Sci U S A. 2008. Dec 2;105(48):18942–6. doi: 10.1073/pnas.0809467105 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref004] 4.Samson RY, Obita T, Freund SM, Williams RL, Bell SD. A role for the ESCRT system in cell division in archaea. Science 2008;322(5908):1710–1713. doi: 10.1126/science.1165322 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref005] 5.Pulschen AA, Mutavchiev DR, Culley S, Sebastian KN, Roubinet J, Roubinet M, et al. Live Imaging of a Hyperthermophilic Archaeon Reveals Distinct Roles for Two ESCRT-III Homologs in Ensuring a Robust and Symmetric Division. Curr Biol. 2020; 30(14):2852–2859.e4. doi: 10.1016/j.cub.2020.05.021 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref006] 6.Tarrason Risa G, Hurtig F, Bray S, Hafner AE, Harker-Kirschneck L, Faull P, et al. The proteasome controls ESCRT-III-mediated cell division in an archaeon. Science. 2020; 369(6504):eaaz2532. doi: 10.1126/science.aaz2532 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref007] 7.Sadler JBA, Wenzel DM, Williams LK, Guindo-Martínez M, Alam SL, Mercader JM, et al. A cancer-associated polymorphism in ESCRT-III disrupts the abscission checkpoint and promotes genome instability. Proc Natl Acad Sci U S A. 2018; 115(38):E8900–E8908. doi: 10.1073/pnas.1805504115 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref008] 8.Votteler J, Sundquist WI. Virus budding and the ESCRT pathway. Cell Host and Microbe. 2013; 14(3):232–241. doi: 10.1016/j.chom.2013.08.012 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref009] 9.Lee JA, Beigneux A, Ahmad ST, Young SG, Gao FB. ESCRT-III Dysfunction Causes Autophagosome Accumulation and Neurodegeneration. Curr Biol. 2007. [published correction appears in Curr Biol. 2007 Sep 18;17(18):1622]; 17(18):1561–1567. doi: 10.1016/j.cub.2007.07.029 [DOI] [PubMed] [Google Scholar]

[pone.0266395.ref010] 10.Eme L, Spang A, Lombard J, Stairs CW, Ettema TJG. Archaea and the origin of eukaryotes. Nature Reviews Microbiology. 2017; 15(12):711–723. doi: 10.1038/nrmicro.2017.133 [DOI] [PubMed] [Google Scholar]

[pone.0266395.ref011] 11.Adam PS, Borrel G, Brochier-Armanet C, Gribaldo S. The growing tree of Archaea: new perspectives on their diversity, evolution and ecology. ISME J. 2017. Nov 4;11(11):2407–25. Available from: http://www.nature.com/articles/ismej2017122. doi: 10.1038/ismej.2017.122 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref012] 12.Imachi H, Nobu MK, Nakahara N, Morono Y, Ogawara M, Takaki Y, et al. Isolation of an archaeon at the prokaryote–eukaryote interface. Nature. 2020; 577(7791):519–525. doi: 10.1038/s41586-019-1916-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref013] 13.Hatano T, Palani S, Papatziamou D, Souza DP, Salzer R, Tamarit D, et al. Characterisation of the Ubiquitin-ESCRT pathway in Asgard archaea sheds new light on origins of membrane trafficking in eukaryotes. bioRxiv [Preprint]. 2021. Aug 17; 2021.08.17.456605. Available from: https://www.biorxiv.org/content/10.1101/2021.08.17.456605v1. [Google Scholar]

[pone.0266395.ref014] 14.Nachmias D, Melnikov N, Zorea A, De-picchoto Y, Zarivach R, Mizrahi I, et al. Asgard ESCRT-III and VPS4 reveal evolutionary conserved chromatin binding properties of the ESCRT machinery. bioRxiv [Preprint]. 2021. Nov 29;2021.11.29.470303. Available from: https://www.biorxiv.org/content/10.1101/2021.11.29.470303v1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref015] 15.Zaremba-Niedzwiedzka K, Caceres EF, Saw JH, Bäckström D, Juzokaite L, Vancaester E, et al. Asgard archaea illuminate the origin of eukaryotic cellular complexity. Nature. 2017. Jan 19;541(7637):353–8. Available from: http://www.nature.com/articles/nature21031. doi: 10.1038/nature21031 [DOI] [PubMed] [Google Scholar]

[pone.0266395.ref016] 16.Moriscot C, Gribaldo S, Jault JM, Krupovic M, Arnaud J, Jamin M, et al. Crenarchaeal CdvA forms double-helical filaments containing DNA and interacts with ESCRT-III-like CdvB. PLoS One. 2011;6(7):e21921. doi: 10.1371/journal.pone.0021921 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref017] 17.Bernander R, Ettema TJ. FtsZ-less cell division in archaea and bacteria. Curr Opin Microbiol. 2010. Dec;13(6):747–52. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1369527410001669. doi: 10.1016/j.mib.2010.10.005 [DOI] [PubMed] [Google Scholar]

[pone.0266395.ref018] 18.Samson RY, Obita T, Hodgson B, Shaw MK, Chong PL-G, Williams RL, et al. Molecular and structural basis of ESCRT-III recruitment to membranes during archaeal cell division. Mol Cell. 2011. Jan;41(2):186–96. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1097276510010038. doi: 10.1016/j.molcel.2010.12.018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref019] 19.Dobro MJ, Samson RY, Yu Z, McCullough J, Ding HJ, Chong PL-G, et al. Electron cryotomography of ESCRT assemblies and dividing Sulfolobus cells suggests that spiraling filaments are involved in membrane scission. Mol Biol Cell. 2013. Aug;24(15):2319–27. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23761076. doi: 10.1091/mbc.E12-11-0785 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref020] 20.Pelve EA, Lindås AC, Martens-Habbena W, de la Torre JR, Stahl DA, Bernander R. Cdv-based cell division and cell cycle organization in the thaumarchaeon Nitrosopumilus maritimus. Mol Microbiol. 2011; 82(3):555–566. doi: 10.1111/j.1365-2958.2011.07834.x [DOI] [PubMed] [Google Scholar]

[pone.0266395.ref021] 21.Ng K-H, Srinivas V, Srinivasan R, Balasubramanian M. The Nitrosopumilus maritimus CdvB, but not FtsZ, assembles into polymers. Archaea. 2013;2013:104147. doi: 10.1155/2013/104147 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref022] 22.Lu Z, Fu T, Li T, Liu Y, Zhang S, Li J, et al. Coevolution of eukaryote-like vps4 and ESCRT-III subunits in the asgard archaea. MBio. 2020; 11(3):e00417–20. Published 2020 May 19. doi: 10.1128/mBio.00417-20 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref023] 23.Sciskala B, Kölling R. Interaction maps of the Saccharomyces cerevisiae ESCRT-III protein Snf7. Eukaryot Cell. 2013;12(11):1538–1546. doi: 10.1128/EC.00241-13 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref024] 24.Buchkovich NJ, Henne WM, Tang S, Emr SD. Essential N-Terminal insertion motif anchors the ESCRT-III filament during MVB vesicle formation. Dev Cell. 2013; 27(2):201–214. doi: 10.1016/j.devcel.2013.09.009 [DOI] [PubMed] [Google Scholar]

[pone.0266395.ref025] 25.Schoch CL, Ciufo S, Domrachev M, Hotton CL, Kannan S, Khovanskaya R, et al. NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database (Oxford). 2020;2020. doi: 10.1093/database/baaa062 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref026] 26.Liao Y, Ithurbide S, Evenhuis C, Löwe J, Duggin IG. Cell division in the archaeon Haloferax volcanii relies on two FtsZ proteins with distinct functions in division ring assembly and constriction. Nat Microbiol. 2021. May 1;6(5):594–605. doi: 10.1038/s41564-021-00894-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref027] 27.Pende N, Sogues A, Megrian D, Sartori-Rupp A, England P, Palabikyan H, et al. SepF is the FtsZ anchor in archaea, with features of an ancestral cell division system. Nat Commun. 2021. Dec 1;12(1). doi: 10.1038/s41467-021-23099-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref028] 28.Izoré T, Kureisaite-Ciziene D, McLaughlin SH, Löwe J. Crenactin forms actin-like double helical filaments regulated by arcadin-2. Elife. 2016. Nov 17;5. doi: 10.7554/eLife.21600 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref029] 29.Kojima R, Obita T, Onoue K, Mizuguchi M. Structural Fine-Tuning of MIT-Interacting Motif 2 (MIM2) and Allosteric Regulation of ESCRT-III by Vps4 in Yeast. J Mol Biol. 2016; 428(11):2392–2404. doi: 10.1016/j.jmb.2016.04.007 [DOI] [PubMed] [Google Scholar]

[pone.0266395.ref030] 30.Huerta-Cepas J, Szklarczyk D, Heller D, Hernández-Plaza A, Forslund SK, Cook H, et al. EggNOG 5.0: A hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 2019; 47(D1):D309–D314. doi: 10.1093/nar/gky1085 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref031] 31.Makarova KS, Wolf YI, Koonin E V. Archaeal clusters of orthologous genes (arCOGs): An update and application for analysis of shared features between thermococcales, methanococcales, and methanobacteriales. Life. 2015; 5(1):818–840. Published 2015 Mar 10. doi: 10.3390/life5010818 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref032] 32.Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Research. 1997; 25(17):3389–3402. doi: 10.1093/nar/25.17.3389 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref033] 33.Agarwala R, Barrett T, Beck J, Benson DA, Bollin C, Bolton E, et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2016; 46(D1):D8–D13. doi: 10.1093/nar/gkv1290 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref034] 34.Mount DW. Using BLOSUM in Sequence Alignments. Cold Spring Harb Protoc. 2008. Jun 1;2008(6):pdb.top39–pdb.top39. doi: 10.1101/pdb.top39 [DOI] [PubMed] [Google Scholar]

[pone.0266395.ref035] 35.Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, et al. Pfam: The protein families database. Nucleic Acids Research. 2014; 42(Database issue):D222–D230. doi: 10.1093/nar/gkt1223 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref036] 36.Mitchell AL, Attwood TK, Babbitt PC, Blum M, Bork P, Bridge A, et al. InterPro in 2019: Improving coverage, classification and access to protein sequence annotations. Nucleic Acids Res. 2019; 47(D1):D351–D360. doi: 10.1093/nar/gky1100 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref037] 37.Jones P, Binns D, Chang HY, Fraser M, Li W, McAnulla C, et al. InterProScan 5: Genome-scale protein function classification. Bioinformatics. 2014; 30(9):1236–1240. doi: 10.1093/bioinformatics/btu031 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref038] 38.Marchler-Bauer A, Derbyshire MK, Gonzales NR, Lu S, Chitsaz F, Geer LY, et al. CDD: NCBI’s conserved domain database. Nucleic Acids Res. 2015; 43(Database issue):D222–D226. doi: 10.1093/nar/gku1221 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref039] 39.Katoh K, Misawa K, Kuma K, Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 2002. Jul 15;30(14):3059–66. doi: 10.1093/nar/gkf436 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref040] 40.Drozdetskiy A, Cole C, Procter J, Barton GJ. JPred4: A protein secondary structure prediction server. Nucleic Acids Res. 2015; 43(W1):W389–W394. doi: 10.1093/nar/gkv332 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0266395.ref041] 41.Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S, et al. MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space. Syst Biol. 2012. May 1;61(3):539–42. doi: 10.1093/sysbio/sys029 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Tracing back variations in archaeal ESCRT-based cell division to protein domain architectures

Béla P Frohn

Tobias Härtel

Jürgen Cox

Petra Schwille

Roles

Abstract

Introduction

Results

Cdv systems are composed of eleven domains, seven of them occurring in all organisms, four only in specific phylogenetic groups

Fig 1. Distribution of CdvABC homologs in archaea and their domain composition.

Cdv protein domains in Euryarchaeota do not constitute a common functional system

Cdv proteins of Cren- and Thaumarchaeota are composed of different domains

Protein domain compositions explain experimental findings indicating differences between Cren- and Thaumarchaeota

Fig 2. Potential protein-protein interactions of archaeal CdvABC homologs.

Mechanistical models of Cdv based cell division suggest two different systems in TACK archaea

Fig 3. Phylogenetic tree of CdvB homologs calculated via Bayesian phylogeny.

Fig 4. Possible mechanisms of Cdv-based cell division in Crenarchaeota, Thaumarchaeota and Asgard.

Asgard archaea possess a system closely related to ESCRT

Fig 5. Multiple sequence alignment and potential domains of Asgard CdvB homologs.

An ancestral Cdv-including machinery was probably able to perform constriction, but membrane tethering remains unclear

Fig 6. Potential evolutionary development of Cdv/ESCRT machineries.

Discussion

Materials and methods

Searching Cdv homologs

Fragmenting protein sequences into domains

Multiple sequence alignment and secondary structure prediction

Phylogenetic analysis

Mechanism inference

Code availability

Limitations of the study

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Ernesto Perez-Rueda

Roles

Author response to Decision Letter 0

Decision Letter 1

Ernesto Perez-Rueda

Roles

Acceptance letter

Ernesto Perez-Rueda

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

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