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. 2021 Nov 23;37(8):110052. doi: 10.1016/j.celrep.2021.110052

Complete atomic structure of a native archaeal cell surface

Andriko von Kügelgen 1, Vikram Alva 2, Tanmay AM Bharat 1,3,4,∗
PMCID: PMC8640222  PMID: 34818541

Summary

Many prokaryotic cells are covered by an ordered, proteinaceous, sheet-like structure called a surface layer (S-layer). S-layer proteins (SLPs) are usually the highest copy number macromolecules in prokaryotes, playing critical roles in cellular physiology such as blocking predators, scaffolding membranes, and facilitating environmental interactions. Using electron cryomicroscopy of two-dimensional sheets, we report the atomic structure of the S-layer from the archaeal model organism Haloferax volcanii. This S-layer consists of a hexagonal array of tightly interacting immunoglobulin-like domains, which are also found in SLPs across several classes of archaea. Cellular tomography reveal that the S-layer is nearly continuous on the cell surface, completed by pentameric defects in the hexagonal lattice. We further report the atomic structure of the SLP pentamer, which shows markedly different relative arrangements of SLP domains needed to complete the S-layer. Our structural data provide a framework for understanding cell surfaces of archaea at the atomic level.

Keywords: cell surface, archaea, cryo-EM, cryo-ET, surface layer, tomography, sub-tomogram averaging, protein evolution, S-layer, immunoglobulin domain

Graphical abstract

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Highlights

  • •

    Cryo-EM reveals the structure of the hexameric S-layer of Haloferax volcanii archaea

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    Immunoglobulin-like domains are widely conserved in archaeal S-layers

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    Cryo-ET shows how an S-layer made of hexamers and pentamers coats curved membranes

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    Atomic-level description of a native archaeal cell surface is shown

von Kügelgen et al. show, using in situ cryo-EM, how Haloferax volcanii archaea are nearly perfectly coated by a hexameric surface layer with pentameric defects, made of a protein with repeated immunoglobulin-like domains. Structure- and sequence-based bioinformatics reveal widespread prokaryotic conservation of these domains, with implications on evolution and fundamental archaeal biology.

Introduction

All prokaryotes interact with their environment through molecules on the cell surface. These cell-surface molecular interactions allow them to locate nutrients, recognize threats, and adapt to their surroundings (Bharat et al., 2021). For prokaryotic organisms living in vastly varied and often harsh habitats, this need for specialized cell-surface molecules is paramount (Filloux and Whitfield, 2016). The entire outer surface of many bacterial and archaeal cells is covered by a two-dimensional array of proteinaceous molecules, a supramolecular structure known as the surface (S-)layer (Sára and Sleytr, 2000). S-layers are built by repeated interactions of S-layer proteins (SLPs), which are often the most abundant cellular molecules, representing up to 15% of the entire protein content of a cell (Bharat et al., 2021; Fagan and Fairweather, 2014; Pum et al., 2013). Owing to their plentitude in prokaryotes, estimates place SLPs as one of the most abundant classes of proteins on Earth (Pum et al., 2013). Despite this, at the fundamental molecular level, relatively little is known structurally about these enigmatic sheet-forming proteins (Bharat et al., 2021).

While some progress has recently been made on understanding bacterial S-layers in a series of structural biology studies (Baranova et al., 2012; Bharat et al., 2017; Fioravanti et al., 2019; von Kügelgen et al., 2020), S-layers from archaea are less understood at the atomic level. Thus far, high resolution atomic structural data have been reported only for the C-terminal repeat segment of the SLP from Methanosarcina acetivorans (Arbing et al., 2012). This segment exhibits two structurally similar β-sandwich folds that is also found in envelope proteins of some eukaryotic RNA viruses. Although the availability of atomic-level structural data on archaeal S-layers is limited, several elegant structural studies have revealed their symmetric organization, providing clues to the constitution and arrangement of these paracrystalline arrays (Arbing et al., 2012; Deatherage et al., 1983; Kessel et al., 1988; Taylor et al., 1982; Trachtenberg et al., 2000). Additionally, some recent tomographic studies have shown the overall arrangement of S-layer lattices at molecular resolution in some archaeal species (Gambelli et al., 2019; Li et al., 2018).

In archaea, S-layer genes are usually the highest expressed, and the corresponding SLPs are, in turn, the highest copy number proteins (Albers and Meyer, 2011; Li et al., 2018). Being the outermost surface in many archaeal cells (Klingl, 2014), S-layers mediate important interactions with their environment, often acting as a molecular sieve regulating the transport of materials to the cell (Li et al., 2018). Additionally, they fulfill several critical cellular functions, including protection from predators and phages (Sára and Sleytr, 2000; Zink et al., 2019), maintenance of a pseudo (or quasi)-periplasmic space outside the cell membrane (Albers and Meyer, 2011), preservation of cell shape (Bharat et al., 2021; Zink et al., 2019), stabilization of the cell membrane (Abdul-Halim et al., 2020), and biomineralization (Kish et al., 2016; Milojevic et al., 2019). In some archaea, S-layers have also been implicated in processes linked to the cell cycle (Albers and Meyer, 2011) as well as to cell division and elongation machinery (Zink et al., 2019). Consequently, understanding the structure, organization, and assembly of S-layers is vital to understanding the basic biology of archaea.

H. volcanii is a genetically tractable model haloarchaeon found in hypersaline environments of the Dead Sea (Mullakhanbhai and Larsen, 1975). It forms pleiomorphic cells surrounded by a proteinaceous S-layer (Figure 1A) with hexagonal symmetry (Kessel et al., 1988), which extends up to ∼125 Å away from the cell surface (Sumper et al., 1990). The H. volcanii S-layer is essential for cell survival and plays vital roles in cell shape maintenance, mating, and many aspects of the cell cycle (Abdul-Halim et al., 2020; Shalev et al., 2017; Tamir and Eichler, 2017). This S-layer consists of repeating units of a single 827-residue SLP called cell-surface glycoprotein (csg) (Figure 1B), which is highly enriched in negatively charged amino acid residues, highlighting the adaptation of H. volcanii to hypersaline environments. While homologs of csg have been characterized and shown to form S-layers with hexagonal lattices in several other haloarchaea (Lechner and Sumper, 1987; Lu et al., 2015; Wakai et al., 1997), csg has, in particular, been extensively studied with electron microscopy (EM) (Kessel et al., 1988) and used as a prominent model system for investigating protein modifications in archaea, owing to extensive post-translational modifications (Kaminski et al., 2013; Kandiba and Eichler, 2014; Kandiba et al., 2016; Konrad and Eichler, 2002; Parente et al., 2014). An archaeosortase-dependent lipid modification occurs at the C terminus of csg after cleavage of a tripartite segment, comprising a conserved Pro-Gly-Phe (PGF) motif, a transmembrane (TM) helix, and a cluster of basic residues (Abdul Halim et al., 2013). Several cryo-electron-microscopy (cryo-EM) studies of H. volcanii cell envelopes have shown that the S-layer is tightly anchored to the cell membrane (Sivabalasarma et al., 2021; Tamir and Eichler, 2017) through these lipid modifications (Konrad and Eichler, 2002) (Figures 1A and 1B). Furthermore, the N-glycosylation of the H. volcanii S-layer has also been intensively analyzed to investigate cell mating (Shalev et al., 2017), a process haloarchaea employ for horizontal gene transfer across cells (Rosenshine et al., 1989). Such mating cells are connected by cell-cell bridges enveloped by a continuous S-layer lattice (Sivabalasarma et al., 2021).

Figure 1.

Figure 1

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Atomic structure of the H. volcanii SLP csg

(A) Cryo-ET slice through the surface of an H. volcanii cell. Density (black) corresponding to the S-layer is marked, showing a tight association with the membrane.

(B) The csg protein contains six domains (D1–D6), colored blue to red in the schematic. Sites of post-translational modifications including the signal-peptide processing, the known and expected protein glycosylation, the O-glycosylated threonine spacer region, and the lipid anchor are shown.

(C) Cryo-EM structure of csg shows that D1–D6 adopt Ig-like folds. The locations of the N-linked glycans are shown in black, and bound cations are shown as green spheres.

(D) Two-dimensional class averages of the sheet-like specimen used for cryo-EM structure determination. Characteristic top and side views are visible.

To understand the fascinating aspects of archaeal S-layers, including specifically those of H. volcanii introduced above, we present the atomic structure of the S-layer from H. volcanii. By visualizing the S-layer in situ, directly in its native environment, we report the structure of the hexagonal S-layer that coats variably curved cellular membranes. We further report the structure of SLP pentamers, showing how the lattice is closed around cells in three dimensions by pentameric defects. Structures of S-layer hexamers and pentamers at different lattice curvatures and states allow us to exhibit an atomic-resolution description of the entire outermost surface of H. volcanii.

Results

Cryo-EM structure of the csg hexamer

To understand cell-surface organization in haloarchaea, we aimed to resolve the atomic structure of the model S-layer from H. volcanii. To this end, we purified native csg protein from H. volcanii cells and incubated it with Ca2+ ions (Figures S1A–S1C). In the resulting mixture, we observed S-layer-like sheets with variable curvature (Figure S1D), showing characteristic top, tilted, and some side views (Figure S1D). We used single-particle cryo-EM data analysis to resolve a global 3.5-Å resolution structure of the hexameric repeating unit of the S-layer within the sheets (Figures S1E–S1J; Table S1) and used it to build an atomic model of csg (Figures 1C and 1D; Video S1; Method details).

Video S1. Single-particle analysis (SPA) reconstruction of csg sheets, related to Figure 3

The 3.5 Å cryo-EM reconstruction is shown with the atomic model (color scheme same as Figure 1C) built into the density (gray isosurface). The hexameric, trimeric and dimeric interfaces in the lattice are highlighted, along with the top and side views of the lattice showing negative curvature.

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The atomic model revealed that each csg monomer assumes an overall sickle shape and is organized into six β-rich immunoglobulin (Ig)-like domains (D1–D6 from hereon) (Figure 1C), of which D1 is highly divergent in sequence among other haloarchaea (Sumper et al., 1990) (Figure S2). Sensitive homology searches and tertiary structure prediction revealed that such arrays of Ig-like folds are widespread across archaeal SLPs (Figure 2), suggesting shared principles of S-layer organization among many archaea. In particular, all analyzed haloarchaeal SLPs had domain compositions similar to csg, with some additional N- or C-terminal Ig-like domains (Figure S3). Such Ig-like domain arrays were also detected, typically in conjunction with other domains, in several non-haloarchaeal SLPs (Figure 2), indicating that these archaea may share similar cell-surface features. For instance, the two putative SLP subunits of Nitrososphaera viennensis, SlaA and SlaB, contain multiple Ig domains (Figure 2). However, some non-haloarchaeal SLPs, such as those of Methanocaldococcus jannaschii and Nanoarchaeum equitans, were predicted to contain no Ig-like domains and instead contain multiple copies of a distinct β-sandwich domain, which is also found in the structurally characterized SLP of M. acetivorans (Arbing et al., 2012).

Figure 2.

Figure 2

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Sequence- and structure-prediction-based analysis reveals underlying domain organization of archaeal SLPs

The multi-domain Ig-like arrangement observed in csg is found across different archaeal phyla. In SLPs outside haloarchaea, Ig-like arrays are typically found in conjunction with coiled-coil segments or a single-stranded right-handed β-helix and a transmembrane (TM) anchor. Some SLPs contain a different β-sandwich domain and a C-terminal csg-like membrane anchor preceded by a conserved PGF motif (PGF-TM) or a putative small Rossmann-like anchor. The SLP of M. acetivorans contains two homologous repeat regions. The structure of the C-terminal repeat region has been characterized (PDB: 3U2H), and it exhibits two structurally similar β-sandwich folds. More details are provided in Figure S3. We note that we were unable to confidently assign some highly divergent parts of the of the sequences in SLPs of M. jannaschii, S. marinus, M. sedula (SlaA), and N. equitans.

In our atomic structure, we observed additional cryo-EM densities at several asparagine residues, which we assigned to known glycosylation sites (Kaminski et al., 2013; Kandiba and Eichler, 2014; Kandiba et al., 2016; Parente et al., 2014) (Figures 1C and S4A–S4E). An N-linked glycan close to the N terminus (E35) of the mature protein on residue N47 probably shields the N terminus from proteolytic cleavage by steric hindrance, in line with previous biochemical experiments (Tamir and Eichler, 2017). At several locations in the protein, unexplained densities were observed within the fold of the protein, coordinated to negatively charged amino acid residue side chains. Given the known dependence of csg on Ca2+ for lattice assembly (Cohen et al., 1991; Rodrigues-Oliveira et al., 2019) and the high concentration of Mg2+ in the medium, we expected that these densities correspond to Ca2+ or Mg2+ cations (Figure S4F).

The csg monomers were packed into the sheet as hexamers (Figure 3A; Video S1). The 6-fold symmetry axis of the hexamer contains repeated interactions of D1 around the central pore, which is ∼13 Å wide (Figure 3B). A glycan on N117 is located close to the hexameric interface, creating a dense network of glycans around this site, further obscuring access of molecules to the narrow pore. The pore is lined with negatively charged residues bound to metal ions, likely Ca2+ or Mg2+, which, in agreement with previous studies, appear to stabilize the hexameric interface critical for lattice formation (Cohen et al., 1991). Because of the sickle shape of the csg monomer, there are repeated intra-hexamer domain interactions between each monomer involving all six domains (Figures 3A and S4G–S4I), resulting in a tight arrangement of the hexamer with multiple protein:protein interfaces.

Figure 3.

Figure 3

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Atomic structure of the hexagonal S-layer lattice

(A) Each csg monomer is arranged into hexamers in a two-dimensional lattice. D1–D6 for one csg monomer are shown in a surface representation.

(B) Magnified view of the hexameric interface (dashed black box in A) reveals glycans and cation-bound residues near the pore in D1.

(C) Magnified view of the trimeric interface (dashed blue box in A) reveals an α-hairpin with bound cations mediating inter-hexameric contacts in D5.

(D) Magnified view of the dimeric interface (dashed purple box in A) shows stacked D4 and D6 mediating a substantial inter-hexameric contact site.

(E) Side view of the csg hexamer, along the plane of the sheet, shows the dome-shaped D1 and D2 structure.

(F) Side view of the lattice. The protein lattice is negatively curved in vitro. Scale bars: 10 Å.

The nonporous hexagonal S-layer lattice supports flexible curvatures

The csg hexamers are packed into a p6 two-dimensional lattice, with inter-hexamer interactions mediated by domains D4, D5, and D6 (Figures 3C and 3D). A conserved α-hairpin motif in D5 forms a prominent trimeric interface (Figure 3C), while stacked D4 and D6 from adjoining hexamers form an extensive dimeric interface (Figure 3D), resulting in a lattice with almost no gaps. Bioinformatic analyses further supported the importance of the α-hairpin motif in D5 that forms the trimeric interface (Figure S3). Many haloarchaeal SLPs with a variable number of Ig-like domains almost always contain only one domain, typically the penultimate domain in the array, with this α-hairpin (Figure S3). The key trimeric D5 inter-hexameric interface is stabilized by several functional divalent cations bound by the α-hairpin of D5, explaining the observed Ca2+ dependence of lattice assembly (Cohen et al., 1991). These residues are conserved in haloarchaea (Figure S2), further supporting their importance in lattice assembly. In more divergent haloarchaeal SLPs that share less than 15% pairwise sequence identity with csg, such as the ones of Haloferax mediterranei and Haloarcula hispanica, the α-hairpin is located in a different position in the domain corresponding to D5 (Figures S3 and S5).

When viewed along the plane of the sheet, D1 and D2 form a dome-shaped structure, with D5 and D6 at the base (Figure 3E). Our reconstituted S-layer sheets displayed a wide variety of lattice curvatures (Figure 3F) and, in extreme cases, curled up into tube-like structures (Figure S6), demonstrating that even though the lattice is tightly packed and nonporous, it can deviate significantly from a planar arrangement, a requirement for coating cellular membranes with variable curvature. To test this hypothesis further, we performed subtomogram averaging (STA) of the tube-like structures and produced a 15.8-Å-resolution structure (Figure S6; Table S2). Fitting of the csg atomic model into the cryo-ET map showed marked deviations in the positions of D5 and D6, suggesting that rearrangement of lattice interfaces in D5 and D6 helps accommodate these variable lattice curvatures (Figure S6).

The native S-layer is nearly continuous with pentameric defects

We next investigated how the in vitro reconstituted csg sheets were related to the native S-layer on membranes. To this end, we purified vesicles from H. volcanii cultures that have been previously observed (Shalev et al., 2017) and visualized them with cryo-ET. STA of the S-layer lattice from these vesicles resulted in a sub-nanometer-resolution (8.0 Å) structure (Figures 4A, 4B, and S7; Table S2), where all six domains of csg, detected in our single-particle cryo-EM structure (Figures 1 and 3), could be unambiguously resolved. The relative arrangements of the domains in our STA map were nearly identical to those seen in the in vitro sheets (Figure 4B). The cryo-ET map on native membranes showed that the dome formed by D1 and D2 faces away from the membrane, meaning that the N-linked glycans described above (Figure 1) point outward away from the cell, where they can play their proposed role in cellular recognition required for key processes such as mating (Shalev et al., 2017).

Figure 4.

Figure 4

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S-layer organization on native membranes

(A) Cryo-ET and STA from vesicles of H. volcanii show the characteristic dome-shaped S-layer enclosing the known pseudo-periplasmic space over the membrane.

(B) Despite opposite lattice curvature, the atomic structure of csg could be unambiguously fitted into the 8-Å resolution cryo-ET density (contour level lower left of panel).

(C) Plotting the resolved structure back onto the tomograms of vesicles revealed a nearly continuous lattice with pentameric defects (red).

(D) STA of the pentameric defects showed that these sites contain the same csg protein with D1–D6, fitted in as rigid bodies separately into the 11.5-Å resolution map.

A notable difference in the S-layer structure on membranes to the in vitro specimen was opposite lattice curvature, suggesting that the membrane might play an important role in affecting lattice curvature (Figure 4A). Another striking feature observed in the S-layer lattice on membranes was the nearly perfect continuity of the S-layer around the vesicles (Figure 4C). Rather than having gaps in the lattice, pentameric defects were observed (Figure 4C). We next extracted subtomograms at the positions of these defects and produced an 11.5-Å-resolution STA map (Figures 4D and S7; Video S2). This map showed clear densities for all six csg domains, confirming that the pentameric defects are made of the same csg protein. This ability of csg to close gaps in the lattice leads to a near-perfect coating of cellular membranes that are known to adopt a variety of curvatures in rod-shaped, spherical, and polymorphic cells (Duggin et al., 2015; Sivabalasarma et al., 2021).

Video S2. Subtomogram averaging (STA) of hexamers and pentamers on native membranes, related to Figure 4

A cryo-electron tomogram of purified H. volcanii vesicles is shown, with the membrane and the S-layer marked. Next, STA maps of the hexamer (gray) and pentamer (red) are plotted on the tomogram coordinates, with zoomed views of the atomic model of csg fitted and displayed within the density. The color scheme for the atomic models is the same as Figure 1C.

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To confirm that our results on purified vesicles faithfully represented the situation on cells, we repeated the cryo-ET and STA experiment on whole H. volcanii cells and produced lattice maps that showed the same hexagonal lattice with pentameric defects (Figure 5A). The unit cell size, along with the modular arrangement of the cellular S-layer, was the same as the S-layer studied on vesicles (Figure 4A), confirmed by the lattice maps obtained on cells (Figure 5A). In our data from cells, the number of pentamers appeared to be increased in areas of the cell with a sudden change in membrane curvature (Figures 5B and 5C). H. volcanii is known to form cells with a variety of shapes (Duggin et al., 2015), and these experiments demonstrate that pentamers of csg are present in the native environment in cells and likely support the maintenance of S-layer coating of membranes with widely different curvatures, while maintaining lattice continuity.

Figure 5.

Figure 5

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S-layer lattice on whole cells

(A) Cryo-ET and STA of whole cells with pleiomorphic shapes show the same hexagonal lattice with pentameric defects.

(B and C) Pentamers are increased in areas of higher membrane curvature (B), compared with flatter areas of the cell membrane (C).

Cryo-EM structure of the csg pentamer

Given the key importance of pentamers in the S-layer lattice, we next set out to resolve an atomic structure of csg pentamers to understand how the SLP changes conformation to incorporate into defects in the lattice. Ho3+ ions are known to replace Ca2+ ions in proteins, and this property has been effectively used in the past for phasing of SLP crystals for X-ray structure determination (Bharat et al., 2017). Following this strategy, we were able to reconstitute pentamers of csg by incubating the protein with Ho3+ ions. Single particles were observed in cryo-EM (Figure 6A), which were used to solve a global 3.9-Å-resolution structure of the pentamer (Figures 6B and S8; Table S1). D1–D3 were well resolved in the pentamer map, and an atomic model could be built de novo only into the N-terminal part of csg, as D4 was only partially resolved, and D5 and D6 were poorly resolved (Figure S8).

Figure 6.

Figure 6

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Atomic structure of csg pentamers

(A) Cryo-EM image of csg pentamers reconstituted with Ho3+ ions; single particles are marked (black arrows). Inset: class averages show side and tilted views of the pentamer.

(B) The 3.9-Å resolution structure shows csg in a pentameric structure (only resolved D1–D4 shown).

(C) The pentameric axis shows a smaller pore with D1 interactions around the axis.

(D) Only D1–D4 are resolved in the cryo-EM map, with D5 and D6 poorly resolved, indicating flexibility without the lattice binding partners (contour level lower left of panel).

(E and F) Comparison of the single-particle analysis (SPA) hexamer and pentamer structure with the pentamer model derived from STA demonstrates large changes in relative positions of the domains. D1 and D2 of all structures have been aligned.

The pentameric interface mediated by D1 involves the same residues as the hexamer (Figure 6C), but since the csg monomers are more tightly packed around the symmetry axis, the pore size is significantly smaller, at ∼6 Å. The poor visibility of D5 and D6 suggests flexibility relative to D1–D4, possibly induced by Ho3+ replacement of Ca2+ in D5 and D6 at the lattice interfaces (Figure 6D). We infer that in the biochemical conditions employed, key interfaces within the lattice are prevented from forming, either due to a lack of Ca2+ or due to flexibility induced by Ho3+ binding, leading to isolated single particles (Figures 6E and 6F).

Complete in situ S-layer structure of H. volcanii

Cryo-EM structures of the csg pentamer and hexamer, along with our cellular tomography lattice maps, allow us to report the structure of the entire outermost surface of an archaeon (Figure 7; Video S3). The hexagonal S-layer of H. volcanii forms a tight and relatively impermeable sheath (Figure 7A) with a narrow pore, ∼13 Å in diameter, at the hexameric axis. This S-layer harbors several key glycans pointing to the extracellular milieu (Figure 7A) and several functional metal ions stabilizing the lattice. Geometric continuity of the S-layer lattice on native membranes is maintained by pentameric defects (Figure 7B), which were also confirmed on whole H. volcanii cells using cryo-ET. The S-layer lattice can coat membranes with a wide range of curvatures, supporting invagination and other pleomorphic cell shapes. All these structurally observed properties of csg allow this enthralling protein to self-assemble and form a micron-scale assembly to coat archaeal cells with near-perfect continuity.

Figure 7.

Figure 7

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Atomic resolution description of an archaeal cell surface

(A) Atomic structure of the csg hexagonal S-layer lattice revealed in this study shows how a flexible but tight proteinaceous layer coats cells of the model archaeon H. volcanii. The coloring scheme for D1–D6 is the same as in Figure 1C.

(B) The S-layer lattice is almost perfectly continuous on cellular membranes with no gaps. The lattice is completed by pentameric defects (colored darker), allowing this fascinating array to fully encase and protect these archaea from harsh environments.

Video S3. Morph between structures resolved in this study, related to Figure 6

Morphs of the atomic models are shown successively between the SPA hexamer, STA hexamer, STA pentamer and the SPA pentamer. At the beginning and end of each morph, the corresponding cryo-EM or cryo-ET density is also shown as gray isosurface. The color scheme for the atomic models is the same as Figure 1C.

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Discussion

Our results will have important implications on prokaryotic cell biology and the evolution of prokaryotic and eukaryotic life. First, in the intensively studied H. volcanii model system, our data confirm how csg is arranged in a hexagonal S-layer tightly associated with the cell membrane, in line with previous studies using negative staining EM and cryo-EM (Kessel et al., 1988; Trachtenberg et al., 2000). On a structural level, the S-layer appears to be stabilized by several positively charged ions, most likely Ca2+ or Mg2+, at the hexameric and trimeric interfaces, allowing co-operative assembly of the lattice and in agreement with past work (Cohen et al., 1991). Calcium dependency of S-layer assembly has been observed in previous atomic structures of Gram-negative (Bharat et al., 2017; von Kügelgen et al., 2020) and Gram-positive bacterial S-layers (Baranova et al., 2012). Further research will be needed to explore how widely this general principle of S-layer assembly is shared. However, in contrast to reported structures of bacterial S-layers (Baranova et al., 2012; Bharat et al., 2017; Fioravanti et al., 2019), there are only narrow pores seen in the csg lattice, which are further obscured by observed glycan moieties; this means that the S-layer severely restricts access to the archaeal cell membrane and the pseudo-periplasmic space, which is a known site for important cellular biochemical reactions (Albers and Meyer, 2011). Furthermore, glycans observed in our structural data have been suggested to play a vital role in the recognition of “self” during cell mating (Shalev et al., 2017), and the surface-exposed arrangement of glycan moieties agrees with that role.

Analogous to multi-domain viral capsids—such as that of HIV-1 (Mattei et al., 2016)—to close the lattice around the cell, pentamers of csg complete the S-layer (Figure 4C), and gaps as seen in bacterial S-layers (Bharat et al., 2017) were not observed. This suggests that closing gaps around the cell membrane is needed for stability, protection from harmful entities, or maintaining a pseudo-periplasmic space between the S-layer and the cell membrane (Albers and Meyer, 2011). One interesting future direction of research could investigate whether the position of pentameric defects is somehow regulated by the SLP secretion machinery or whether this is a stochastic process relying on a pool of unassembled csg in the pseudo-periplasm. Another fascinating direction of future inquiry would be to understand how other cell-surface features, including flagella and pili, extend out from the cell with respect to pentameric defects in the S-layer. Our data further show how this tightly assembled S-layer can significantly deviate from a planar arrangement needed to coat cell envelopes with different curvatures during the cell cycle. Our cryo-ET experiments on vesicles and whole cells confirm that both positive (seen on vesicles and cellular membranes; Figures 4 and 5) and negative curvatures (seen in the in vitro tubes and polymorphic cells; Figures S6 and 5) are physiologically relevant because the cell membrane must invaginate during important processes such as mating, septation, and cell division (Abdul-Halim et al., 2020; Sivabalasarma et al., 2021).

On the technical side, solving structures from two-dimensional crystals has been notoriously difficult (Ganser-Pornillos et al., 2007; Scherer et al., 2014). In this study using STA to produce an initial reference structure, combined with single-particle cryo-EM, we solve an atomic structure from a sheet-like crystal. This will be of interest to many researchers in the cryo-EM field working on two-dimensional electron crystallography (Gonen et al., 2004; Scherer et al., 2014).

Using sequence- and structure-prediction-based bioinformatic analysis, we show conservation of the observed arrangement of Ig-like domains across several archaeal phyla, which means that this complete in situ structure of an archaeal S-layer will open the door to understanding how cell surfaces are organized in these microbes. Based on our bioinformatics data, we anticipate that many archaeal species, particularly haloarchaea, share these general principles of S-layer structure and organization. Nonetheless, we do anticipate there to be marked differences in S-layer anchoring and assembly mechanisms, dependent on the habitat or the organism, as suggested previously (Albers and Meyer, 2011; Bharat et al., 2021). Curiously, several haloarchaeal organisms contain multiple putative SLPs (Figure S3), suggesting that they may be able to use different SLPs to evade predators and phages or to regulate mating preferences.

We anticipate that our results will guide our understanding of certain aspects of eukaryogenesis. Primordial S-layer Ig-like domains at the cell surface may have helped in the recognition of neighboring foreign cells for the formation of mutualistic interactions (Baum and Baum, 2014), which may have led to the emergence of more sophisticated, multi-component recognition systems, such as the modern eukaryotic immune system (Baum and Baum, 2014; Imachi et al., 2020; Spang et al., 2017). Since the Asgard archaeaon “Candidatus Prometheoarchaeum syntrophicum” strain MK-D1—the closest known prokaryotic relative of eukaryotes to date—has been implicated to possess S-layers (Imachi et al., 2020), a fascinating question to contemplate is why and when S-layers were lost in the evolution of contemporary eukaryotes.

Beyond the fundamental biology revealed by our work, S-layers have outstanding potential for synthetic biology applications, and using our past work on S-layers (Bharat et al., 2017; von Kügelgen et al., 2020), the first applications are being reported (Charrier et al., 2019). Although this rising field is still in its infancy, there is a huge potential for the synthesis of the next generation of biomaterials, and recent prominent studies have highlighted this potential (Ben-Sasson et al., 2021). Our results, thus, further our knowledge of a captivating class of naturally abundant molecules with a marked ability to self-assemble around prokaryotic cells at high copy numbers.

Limitations of the study

At the current resolution, the unique chemical identity of the bound metal cations cannot be ascertained. Further structural and biophysical studies will be required to deduce the nature of the bound metal ions. We hope that this complete atomic structure of an archaeal cell surface will help stimulate further research into this enthralling field.

STAR★Methods

Key resources table

REAGENT or RESOURCE SOURCE IDENTIFIER
Chemicals, peptides, and recombinant proteins
Fiducial gold (FG) 10 nm, 400 μL CMC Utrecht N/A
Deposited data
Hv-csg hexameric single particle structure This study PDB: 7PTR
Hv-csg hexameric cryo-EM map This study EMDB: EMD-13634
Hv-csg pentameric single particle structure This study PDB: 7PTU
Hv-csg pentameric cryo-EM map This study EMDB: EMD-13638
Hv-csg hexameric subtomogram averaging structure This study PDB: 7PTT
Hv-csg hexameric cryo-ET map This study EMDB: EMD-13637
Hv-csg pentameric subtomogram averaging structure This study PDB: 7PTP
Hv-csg pentameric cryo-ET map This study EMDB: EMD-13632
Inverted S-layer tube cryo-ET map This study EMDB: EMD-13639
Experimental models: Organisms/strains
Haloferax volcanii H-26 (Allers et al., 2004) H-26
Software and algorithms
3DFSC (Tan et al., 2017) https://3dfsc.salk.edu/
CCP-EM (Burnley et al., 2017) https://www.ccpem.ac.uk/
Coot (Emsley et al., 2010) https://www2.mrc-lmb.cam.ac.uk/personal/pemsley/coot/
CTFFIND (Rohou and Grigorieff, 2015) https://grigoriefflab.janelia.org/ctf
EPU Thermo Fisher Scientific https://www.thermofisher.com/us/en/home/electron-microscopy/products/software-em-3d-vis/epu-software.html
Fiji (Schindelin et al., 2012) https://fiji.sc/
IMOD (Kremer et al., 1996) https://bio3d.colorado.edu/imod/
HHpred (Steinegger et al., 2019) https://github.com/soedinglab/hh-suite
HMMER (Eddy, 1998) http://hmmer.org/
MATLAB R2019b Mathworks https://uk.mathworks.com/
MotionCor2 (implemented in RELION 3.1) (Zheng et al., 2017) N/A
MPI Bioinformatics Toolkit (Zimmermann et al., 2018) https://toolkit.tuebingen.mpg.de/
novaCTF (Turoňová et al., 2017) https://github.com/turonova/novaCTF
PHENIX (Liebschner et al., 2019) https://phenix-online.org/
PlaceObject Chimera Plugin (Qu et al., 2018) https://www2.mrc-lmb.cam.ac.uk/groups/briggs/resources/place-object/
PyMOL (Schrödinger, 2021) https://pymol.org/2/
REFMAC5 (Murshudov et al., 2011) https://www2.mrc-lmb.cam.ac.uk/groups/murshudov/content/refmac/refmac.html
RELION 3.1 (Zivanov et al., 2020; Bharat and Scheres, 2016;
Bharat et al., 2017)		 https://www2.mrc-lmb.cam.ac.uk/relion
SerialEM (Mastronarde, 2005) https://bio3d.colorado.edu/SerialEM/
TOPAZ (Bepler et al., 2019) https://github.com/tbepler/topaz
TrRosetta (Yang et al., 2020) https://yanglab.nankai.edu.cn/trRosetta/
UCSF Chimera (Pettersen et al., 2004) https://www.cgl.ucsf.edu/chimera/
UCSF ChimeraX (Pettersen et al., 2021) https://www.cgl.ucsf.edu/chimerax/
Other
R2/2 200 mesh Cu/Rh holey carbon grids Quantifoil https://www.quantifoil.com/
Open in a new tab

Resource availability

Lead contact

Further information and requests for reagents may be directed to, and will be fulfilled by the Lead Contact, Tanmay A. M. Bharat (tanmay.bharat@path.ox.ac.uk).

Materials availability

Further information and requests for reagents may be directed to, and will be fulfilled by the Lead Contact, Tanmay A. M. Bharat (tanmay.bharat@path.ox.ac.uk).

Experimental model and subject details

All H. volcanii strains listed in this study are listed in the Key resources table. H. volcanii strains were grown in yeast-peptone-casamino acid (Hv-YPC) medium (Allers et al., 2004) at 45°C. Archaeal strains used in this study are further listed in Table S3.

Method details

Purification of csg protein

Wild-type, mature, cell-surface csg protein was purified from the native organism using the lectin concanavalin A. Briefly, 6 L of Hv-YPC medium (Allers et al., 2004) were inoculated 1:50 with a late-log phase culture of H. volcanii (strain H26, Table S3), and cells were grown aerobically at 45°C to an optical density (OD600) of 1.5. Cells were harvested by centrifugation (5,000 rcf., 4°C, 30 min). Cells were resuspended in 20 mL lysis buffer (20 mM HEPES/NaOH pH 7.5, 500 mM NaCl, 1 mM MnCl2, 1 mM CaCl2, 1x cOmplete protease inhibitor (Roche), 50 μg/mL DNaseI, 1 U/mL benzonase (SigmaAldrich)) per 1 L cell pellet and lysed by passing the suspension five times through a homogenizer at 20,000 psi. Cell debris was removed by centrifugation (35,000 rcf., 4°C, 45 min), and archaeal membranes were isolated by ultracentrifugation (200,000 rcf., 4°C, 3 h). Membranes were extracted by resuspending the pellet in 50 mL concanavalin A binding buffer (20 mM HEPES/NaOH pH 7.5, 500 mM NaCl, 1 mM MnCl2, 1 mM CaCl2, 0.04% (v/v) Triton X-100 (SigmaAldrich)) for 2 h. The protein solution was loaded onto three 5 mL HiTrap-Concanavalin-A-4B-HP columns (GE Healthcare) using an ÄKTA pure 25 system (GE Healthcare). Unbound protein was washed away with 75 mL concanavalin A binding buffer, and bound protein was eluted with an increasing gradient of 45 mL elution buffer (20 mM HEPES/NaOH pH 7.5, 500 mM NaCl, 50 mM methyl-α-D-mannopyranoside (SigmaAldrich), 0.02% (v/v) Triton X-100). Fractions containing csg were pooled, concentrated using a 30 kDa MWCO Ultra Centrifugal tube (Amicon) and loaded to a Superdex S200-Increase 10/300 GL column (GE Healthcare) equilibrated with 20 mM HEPES/NaOH pH 7.5, 150 mM MgCl2, 0.65% (w/v) CHAPS detergent. Protein was eluted in the same buffer, and fractions containing csg were collected, concentrated (Amicon 30 kDa MWCO), flash-frozen in liquid nitrogen and stored at −80°C until further use. Chromatograms and SDS-PAGE gel images were visualized with MATLAB (MathWorks) and Fiji (Schindelin et al., 2012), respectively. This mature, purified csg protein was used for all experiments below, including in vitro reconstitution of hexagonal sheets and pentamers.

In vitro reconstitution and purification of specimens for cryo-EM

Reconstitution of S-layer tubes and sheets: S-layer tubes were assembled by adding 15 mM CaCl2 to purified wild-type csg at a final protein concentration of 3.2 mg/mL and incubating the solution on ice for 25 mins. Assembled S-layer sheets were then immediately prepared for cryo-EM.

Purification of vesicles for cryo-ET and subtomogram averaging: Vesicles were purified from a 200 mL H. volcanii cell culture which was previously inoculated 1:50 with a late-log starter culture and grown to an optical density (OD600) of 1.2 at 45°C. Cells were removed by centrifugation (5,000 rcf, 20 min, 25°C), and the supernatant was filtered through a 0.45 μm pore-size filter. Archaeal vesicles were isolated by ultracentrifugation (200,000 rcf., 4°C, 3 h) and carefully resuspended in 10 μL of 18% (w/v) artificial sea-water (SW) containing identical salt concentrations as Hv-YPC media, but lacking nutrient sources.

Reconstitution of csg pentamers: Pentamers of csg were assembled by adding 1.5-1.75 mM HoCl3 to purified wild-type csg at a final protein concentration of 2.5 mg/mL and incubating the solution on ice for 2 hours.

Cryo-EM sample preparation

For cryo-EM grid preparation, 2.5 μL of in vitro reconstituted sample or purified vesicles solution or H. volcanii culture grown on a 1.5% (w/v) agar plate were applied to a freshly glow discharged Quantifoil R2/2 Cu/Rh 200 mesh grid, adsorbed for 10 s, blotted for 4-5 s and plunge-frozen into liquid ethane in a Vitrobot Mark IV (ThermoFisher), while the blotting chamber was maintained at 100% humidity at 10°C. For cryo-ET, 10 nm protein-A gold (CMC Utrecht) was additionally added to the samples immediately prior to grid preparation.

Cryo-EM and cryo-ET data collection

Cryo-EM single particle data: Single-particle cryo-EM data were collected on a Titan Krios G3 microscope (ThermoFisher) operating at 300 kV fitted with a Quantum energy filter (slit width 20 eV) and a K3 direct electron detector (Gatan) with a sampling pixel size of 0.55 Å running in counting super-resolution mode. For the csg sheets S-layer sample used for the csg hexameric lattice structure, a total of 18,468 movies were collected in two sessions with a dose rate of 3.5 e-/pixel/s on the camera level. The sample was subjected to 3.4 s of exposure, during which a total dose of 49 or 51.44 e-/Å2 respectively was applied, and 40 frames were recorded per movie (see Table S1). For pentameric csg specimens, a total of 11,871 movies were collected in two sessions with a dose rate of 3.5 e-/pixel/s on the camera level. The specimen was subjected to 3.6 s of exposure, during which a total dose of 53.45 or 53.9 e-/Å2 respectively was applied, and 40 frames were recorded per movie (see Table S1).

Cryo-ET data: For tomographic data collection, the SerialEM software (Mastronarde, 2005) was used as described previously (Sulkowski et al., 2019) (see Table S2). Tomographic data collection of cellular specimens was performed on the same Titan Krios microscope using the Quantum energy filter (slit width 20 eV) and the K3 direct electron detector running in counting mode. Tilt series (33 in total) with a defocus range of −5 to −8 μm were collected between ± 60° in a dose symmetric scheme (Hagen et al., 2017) with a 2° tilt increment. A total dose of 73 e-/Å2 was applied over the entire series, and image data were sampled at a pixel size of 3.468 Å. For in-vitro reconstituted inverted S-layer tubes 33 bi-directional and 14 dose-symmetrical) tilt series were collected with a 3° tilt increment at a dose rate of 5.88 or 6.1 e-/pixel/s, respectively. A total dose of 90 or 123 e-/Å2 was applied over the entire series, and image data were sampled at a calibrated pixel size of 2.238 Å using a K2 direct electron detector running in counting mode (slit width 25 eV) (see Table S2). For in situ structure determination of the S-layer from coated vesicles, a pipeline for high-throughput data collection was adopted (Wan et al., 2017). Briefly, a Titan Krios microscope was used to collect tilt series data with a dose symmetric tilting scheme (Hagen et al., 2017). A total of 172 tilt series were collected at a pixel size of 1.328 Å, with a total dose of 120 e-/Å2 was applied over the entire series collected between ± 60° with 3° tilt increments using a K2 detector with a slit width of 20 eV.

Cryo-EM single particle analysis

Hexameric structure from two-dimensional sheets: Movies were clustered into optics groups based on the XML meta-data of the data-collection software EPU (ThermoFisher) using a k-means algorithm implemented in EPU_group_AFIS (https://github.com/DustinMorado/EPU_group_AFIS). Imported movies were motion-corrected, dose weighted, and Fourier cropped (2x) with MotionCor2 (Zheng et al., 2017) implemented in RELION3.1 (Zivanov et al., 2018). Contrast transfer functions (CTFs) of the resulting motion-corrected micrographs were estimated using CTFFIND4 (Rohou and Grigorieff, 2015). Initially, side views of S-layer sheets were first manually picked along the edge of the lattice using the helical picking tab in RELION while setting the helical rise to 160 Å. Top and tilted views were manually picked at the central hexameric axis. Manually picked particles were extracted in 4x downsampled 100 × 100 boxes and classified using reference-free 2D classification inside RELION3.1. Class averages centered at a hexameric axis were used to automatically pick particles inside RELION3.1. Automatically picked particles were extracted in 4x downsampled 100x100 pixel boxes and classified using reference-free 2D classification. Particle coordinates belonging to class averages centered at the hexameric axis were used to train TOPAZ (Bepler et al., 2019) in 5x downsampled micrographs with the neural network architecture ResNet8. For the final reconstruction, particles were picked using TOPAZ and the previously trained neural network above. Additionally, top and bottom views were picked using the reference-based autopicker inside RELION3.1, which were not readily identified by TOPAZ. Particles were extracted in 4x downsampled 100 × 100 boxes and classified using reference-free 2D classification inside RELION3.1. Particles belonging to class averages centered at the hexameric axis were combined, and particles within 100 Å were removed to prevent duplication after alignment. All resulting particles, side views from TOPAZ picking and top/bottom views from RELION picking, were then re-extracted in 4x downsampled 100 × 100 boxes and were subjected to 3D classification using a 60 Å lowpass filtered reference map from subtomogram averaging of the inverted S-layer tubes (Figure S6). Particles from classes with the same curvature were combined, re-extracted in 400 × 400 boxes and subjected to a focused 3D auto refinement on the central 6 subunits using the scaled and lowpass filtered output from the 3D classification as a starting model. Per-particle defocus, anisotropy magnification and higher-order aberrations (Zivanov et al., 2020) were refined inside RELION3.1, followed by another round of focused 3D auto refinement and Bayesian particle polishing (Zivanov et al., 2020). At this point, both S-layer sheet datasets were merged for a final round of 3D-auto refinement after CTF Refinement. The final map was obtained from 1,087,798 particles and post-processed using a soft mask focused on the central hexamer yielding a global resolution of 3.5 Å according to the gold standard Fourier shell correlation criterion of 0.143 (Scheres, 2012). The two-dimensional sheet-like arrangement led to anisotropy in resolution, with lower resolution perpendicular to the plane as estimated by directional FSCs (Tan et al., 2017), observed previously by several studies on two-dimensional sheets (Ganser-Pornillos et al., 2007; Scherer et al., 2014). Cryo-EM single-particle data statistics are summarized in Table S1.

Structure of the csg pentamer: Images of pentameric csg complexes were similarly processed with the following differences: particles were initially picking using the Laplacian-of Gaussian algorithm implemented in RELION3.0 (Zivanov et al., 2018). Particles were extracted in 8x down-sampled in 50x50 pixel boxes and classified using reference-free 2D classification inside RELION3.0. Class averages showing high-resolution features were used for reference-based autopicking, followed by refinement as detailed above for the csg hexameric sheets. Particles belonging to 2D classes showing high-resolution features were re-extracted in 320 × 320 pixel boxes and an initial 3D reference model was prepared inside RELION3.0 with the stochastic gradient descent (SGD) algorithm. The final map (RELION3.1) was obtained from 382,105 particles and post-processed using a soft mask focused on the entire pentameric map yielding a global resolution of 3.87 Å with resolution anisotropy from 3.49-8.11 Å from the central C5 axis near domains D1-D3 (well resolved) to the more flexible domains D4 (partially resolved) and D5-D6 (not resolved).

Cryo-ET data analysis

Tilt series alignment using gold fiducials and tomogram generation was performed in IMOD (Kremer et al., 1996). Sub-tomogram averaging was performed using custom scripts written in MATLAB (MathWorks), described previously (Bharat et al., 2011; Förster et al., 2005; Wan et al., 2017). For preliminary assignment of angles and initial structure determination, we adopted previously published methods (Bharat et al., 2017) using a 3D-CTF correction method for tomographic data (Turoňová et al., 2017). This workflow allowed us to produce lattice maps from tubes, cells and vesicles of H. volcanii (Figures 4, 5, S6, and S7), which were used to map the positions of hexamers and pentamers in the lattice. Initial subtomogram averaging maps and output angular angle assignments were then used for sub-tomogram averaging in RELION3.1 (Bharat and Scheres, 2016; Bharat et al., 2015), leading to the final maps of the csg hexamer from tubes (15.8 Å resolution, Figure S6) and vesicles (8.0 Å resolution, Figure 4) and pentamer from vesicles (11.5 Å resolution, Figure 4). Figure panels containing cryo-EM or cryo-ET images were prepared using IMOD and Fiji (Schindelin et al., 2012). Lattice maps of S-layers were plotted inside UCSF Chimera (Pettersen et al., 2004) with the PlaceObject Plugin (Qu et al., 2018) and copies of atomic coordinates were plotted inside UCSF ChimeraX (Pettersen et al., 2021) with the sym function and the BIOMATRIX PDB file header. Supplementary videos (Videos S1, S2, and S3) were prepared with UCSF Chimera.

Model building and refinement

Csg hexameric structure from sheets: The boundaries of the six Ig-like domains, D1-D6, were predicted using HHpred (Steinegger et al., 2019) in default settings within the MPI Bioinformatics Toolkit (Zimmermann et al., 2018). Subsequently, structural models for these domains were built using the Robetta structure prediction server, employing the deep learning-based modeling method TrRosetta (Yang et al., 2020). The obtained structural models of domains D3-D6 resulted in an overall fit into the hexameric cryo-EM map of csg from the reconstituted sheets. D1-D2 deviated significantly from any obtained homology models, and for those domains, the carbon backbone of the csg protein was manually traced through a single subunit of the hexameric cryo-EM density using Coot (Emsley et al., 2010). Due to the edge effect of the box used in the refinement of the 3.5 Å map, parts of D6 displayed edge artifacts. These artifacts were removed using single-particle cryo-EM refinement in a larger box, which led to an overall slightly lower resolution (3.8 Å) but allowed fitting of the D6 homology model unambiguously. Following initial manual building (for D1-D2) or fitting in of structural models (for D3-D6), side chains were assigned in regions with density corresponding to characteristic aromatic residues allowing us to deduce the register of the amino acid sequence in the map. Another important check of the model building was the position of known glycan positions, which were readily assigned based on large unexplained densities on characteristic asparagine residues. The atomic model was then placed into the hexameric map in six copies and subjected to several rounds of refinement using refmac5 (Murshudov et al., 2011) inside the CCP-EM software suite (Burnley et al., 2017) and PHENIX (Liebschner et al., 2019), followed by manually rebuilding in Coot (Emsley et al., 2010). Model validation was performed in PHENIX and CCP-EM, and data visualization was performed in Chimera, ChimeraX, and PyMOL (Schrödinger, 2021). To analyze lattice interfaces, multiple copies of the hexameric structure were placed in the cryo-EM map prepared with a larger box size and refined once in PHENIX.

Csg pentamer: The initial manual build of D1-D2 was performed independently using the csg pentameric cryo-EM map, which served as an additional validation of the manual building performed in the csg hexamer above. The manual building exercise yielded a nearly identical result to the hexamer; thus, the final refined hexameric structures of D1-D2, along with D3-D4 were taken and fitted into the pentameric map (∼3.87 Å resolution in D1-D3, lower in D4 which is partially resolved). Five copies of these D1-D4 were used for refinement and model building as for the hexamer, except D3 and D4 was restrained in position, due to steadily deteriorating resolution in this part of the map. D5-D6 were not resolved in the pentameric structure and were thus not included in the refinements. Model validation and visualization were performed in the same way as for the hexameric structure.

Bioinformatic analysis

All sequence similarity searches were performed in the MPI Bioinformatics Toolkit (Zimmermann et al., 2018) using the sensitive sequence comparison methods in HMMER (Eddy, 1998) and HHpred (Steinegger et al., 2019). HMMER searches were performed against the nr_arc database, a version of the NCBI nonredundant protein sequence database (nr) filtered for archaeal sequences, to identify homologs of csg in haloarchaea and other closely related classes of archaea. The searches were seeded with the protein sequence of csg (UniProt ID P25062) as well as the experimentally characterized SLPs of Halobacterium salinarum (B0R8E4), Haloarcula japonica (Q9C4B4), and Haloarcula hispanica (csg1- G0HV85, csg2 - G0HV86). Divergent homologs of csg were detected in Haloferax mediterranei (two homologs), and outside haloarchaea, in the order Methanomicrobiales (e.g., Methanospirillum hungatei). The domain organizations of several obtained matches were analyzed using HHpred searches over the PDB70 and ECOD70 databases in default settings and using the TrRosetta method implemented within the Robetta structure prediction server (Yang et al., 2020). Additionally, the domain organization of some other experimentally characterized SLPs were also analyzed: Aeropyrum pernix (Q9YEG7), Metallosphaera sedula (SlaA - A4YHQ8, SlaB - A4YHQ9), Methanocaldococcus jannaschii (Q58232), Methanosarcina acetivorans (Q8TSG7), Methanothermus fervidus (P27373), Nanoarchaeum equitans (Burghardt et al., 2009) (Q74MU7), Nitrososphaera viennensis (Kerou et al., 2016) (SlaA - A0A060HS03, SlaB - A0A060HR06), and Staphylothermus marinus (Q54436). The SLPs of Methanosarcina acetivorans, Methanocaldococcus jannaschii, and Nanoarchaeum equitans contain no Ig-like domains and instead contain multiple copies of a different β sandwich fold (Arbing et al., 2012); while the former contains a membrane anchor preceded by a conserved PGF motif, the latter two are predicted to contain a small C-terminal Rossmann-like domain.

Quantification and statistical analysis

See Method details and Tables S1 and S2 for further information on the statistical analyses for bioinformatics and resolution estimates for cryo-EM maps.

Acknowledgments

T.A.M.B. is a recipient of a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (202231/Z/16/Z). T.A.M.B. would like to thank the Vallee Research Foundation, the European Molecular Biology Organization, and the Leverhulme Trust for support. The authors would like to thank Thorsten Allers for the kind gift of the H26 strain of H. volcanii, Wim Hagen for collecting of part of the cryo-ET data in this manuscript, and Jan Löwe and Iain Duggin for helpful discussions. V.A. would like to thank Andrei Lupas for continued support. This work was partly supported by institutional funds of the Max Planck Society.

Author contributions

A.v.K. and T.A.M.B. designed research; A.v.K., V.A., and T.A.M.B. performed research; A.v.K., V.A., and T.A.M.B. analyzed data; A.v.K., V.A., and T.A.M.B. wrote the manuscript.

Declaration of interests

The authors declare no competing interests.

Published: November 23, 2021

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.celrep.2021.110052.

Supplemental information

Document S1. Figures S1–S8 and Tables S1–S3
mmc1.pdf (10.8MB, pdf)
Document S2. Article plus supplemental information
mmc5.pdf (22.5MB, pdf)

Data and code availability

  • •

    Cryo-EM maps have been deposited in the Electron Microscopy Data Bank (EMDB) under the accession code EMD-13634 for the hexameric SPA, EMD-13638 for the pentameric SPA, EMD-13637 for the hexameric STA and EMD-13632 for the pentameric STA. Corresponding refined atomic models have been deposited in the Protein Data Bank (PDB) under the accession numbers to 7PTR for the hexameric SPA, 7PTU for the pentameric SPA, 7PTT for the hexameric STA and 7PTP for the pentameric STA respectively. The cryo-ET map of the inverted S-layer tubes has been deposited with the EMDB accession code EMD-13639. For further details see Tables S1 and S2 and the Key resources table.

  • •

    This paper does not report original code.

  • •

    Any additional information required to reanalyse the data reported in this paper is available from the lead contact upon request.

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Associated Data

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

Supplementary Materials

Video S1. Single-particle analysis (SPA) reconstruction of csg sheets, related to Figure 3

The 3.5 Å cryo-EM reconstruction is shown with the atomic model (color scheme same as Figure 1C) built into the density (gray isosurface). The hexameric, trimeric and dimeric interfaces in the lattice are highlighted, along with the top and side views of the lattice showing negative curvature.

Download video file (20.7MB, mp4)
Video S2. Subtomogram averaging (STA) of hexamers and pentamers on native membranes, related to Figure 4

A cryo-electron tomogram of purified H. volcanii vesicles is shown, with the membrane and the S-layer marked. Next, STA maps of the hexamer (gray) and pentamer (red) are plotted on the tomogram coordinates, with zoomed views of the atomic model of csg fitted and displayed within the density. The color scheme for the atomic models is the same as Figure 1C.

Download video file (26.4MB, mp4)
Video S3. Morph between structures resolved in this study, related to Figure 6

Morphs of the atomic models are shown successively between the SPA hexamer, STA hexamer, STA pentamer and the SPA pentamer. At the beginning and end of each morph, the corresponding cryo-EM or cryo-ET density is also shown as gray isosurface. The color scheme for the atomic models is the same as Figure 1C.

Download video file (24.5MB, mp4)
Document S1. Figures S1–S8 and Tables S1–S3
mmc1.pdf (10.8MB, pdf)
Document S2. Article plus supplemental information
mmc5.pdf (22.5MB, pdf)

Data Availability Statement

  • •

    Cryo-EM maps have been deposited in the Electron Microscopy Data Bank (EMDB) under the accession code EMD-13634 for the hexameric SPA, EMD-13638 for the pentameric SPA, EMD-13637 for the hexameric STA and EMD-13632 for the pentameric STA. Corresponding refined atomic models have been deposited in the Protein Data Bank (PDB) under the accession numbers to 7PTR for the hexameric SPA, 7PTU for the pentameric SPA, 7PTT for the hexameric STA and 7PTP for the pentameric STA respectively. The cryo-ET map of the inverted S-layer tubes has been deposited with the EMDB accession code EMD-13639. For further details see Tables S1 and S2 and the Key resources table.

  • •

    This paper does not report original code.

  • •

    Any additional information required to reanalyse the data reported in this paper is available from the lead contact upon request.

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