Clostridium oremlandii (CoMsrA). The overall structure of CoMsrA is unusual, consisting of two domains, the N-terminal catalytic domain and the C-terminal distinct helical domain which is absent from other known MsrA structures. Deletion of the helical domain almost completely abolishes the catalytic activity of CoMsrA. In this study, we determined the crystal structure of the helical domain-deleted (ΔH-domain) form of CoMsrA at a resolution of 1.76 Å. The monomer structure is composed of the central rolled mixed β-sheet surrounded by α-helices. However, there are significant conformational changes in the N- and C-termini and loop regions of the ΔH-domain protein relative to the catalytic domain structure of full-length CoMsrA. The active site structure in the ΔH-domain protein completely collapses, thereby causing loss of catalytic activity of the protein. Interestingly, dimer structures are observed in the crystal formed by N-terminus swapping between two molecules. The ΔH-domain protein primarily exists as a dimer in solution, whereas the full-length CoMsrA exists as a monomer. Collectively, this study provides insight into the structural basis of the essential role of the helical domain of CoMsrA in its catalysis.We previously determined the crystal structures of 1-Cys type selenoprotein MsrA from  S-isomer of methionine sulfoxide and MsrB for the R-isomer. Both MsrA and MsrB enzymes prevent excessive accumulation of oxidized proteins and the cytotoxic effects of reactive oxygen species [Methionine sulfoxide reductases (Msrs) are ubiquitous and highly conserved enzymes that catalyze the reduction of methionine sulfoxide to methionine. Msr enzymes for the reduction of peptidyl methionine sulfoxide are classified into two protein families based on the stereospecificity of methionine sulfoxide enantiomers . MsrA is species –4. Altho species –7. The gClostridium oremlandii contains a selenocysteine (Sec)-containing MsrA (CoMsrA) [CoMsrA composed of 209 amino acids contains only one catalytic Sec residue with no Cys residues and is classified as 1-Cys type MsrA. The catalytic activity of selenoprotein CoMsrA is 20-fold higher than that of its Sec-to-Cys version, revealing a catalytic advantage provided by selenium [CoMsrA is not performed by the general reductant for MsrA, thioredoxin [CoMsrA is instead efficiently reduced by glutaredoxin [CoMsrA using the Cys version proteins [CoMsrA including the conserved active site sequence GCFWG shows a fold similar to that of other known MsrAs, which contains a central core composed of a rolled mixed β-sheet with the exterior side surrounded by α-helices. The unique C-terminal helical domain (residues 145–209) consists of five helices and interacts with the catalytic domain via the α8 helix located between the catalytic domain α1 and α5 helices. The C-terminal helical domain is conserved in some selenoprotein MsrAs [CoMsrA catalysis [The anaerobic gram-positive bacterium (CoMsrA) . This seselenium . In addiaredoxin . We receproteins . This enproteins –15. The in MsrAs . Interesatalysis . Our preatalysis . HoweverCoMsrA was determined. The ΔH-domain structure reveals insight into the essential role of the helical domain in formation of the active site of the catalytic domain. Loss of catalytic activity of the ΔH-domain form occurs due to the active site collapse caused by loss of interaction with the helical domain and the catalytic domain. There are significant structural changes in the ΔH-domain form when compared to the full-length CoMsrA, including a swapped dimer structure.In this study, the crystal structure of the C-terminal helical domain-deleted (ΔH-domain) form of CoMsrA was PCR-amplified and cloned into expression vector pET21b as previously described [Escherichia coli BL21 (DE3) star cells transformed with the recombinant plasmid were grown in LB medium containing 50 μg/ml ampicillin at 37°C until the OD600 reached 0.5–0.6. Protein expression was induced by the addition of IPTG at a final concentration of 0.3 mM, after which cells were grown at 18°C for another 16 h. Cells were subsequently harvested by centrifugation and disrupted by sonication in ice-cold buffer A . Following centrifugation, the supernatant containing the amplified protein was loaded onto a HisTrap column that had been equilibrated in buffer A and the protein was eluted by a gradient increase of imidazole concentration from 20 to 500 mM. The purified protein was concentrated and applied to gel filtration chromatography on a Superdex 75 column in buffer . Finally, the protein purity was confirmed by SDS-PAGE analysis, and the purified protein was concentrated to 8 mg/ml.A DNA sequence encoding residues 1–144 (ΔH-domain) of escribed . The recCoMsrA (PDB ID: 4LWJ) was used as a search model [http://pymol.sourceforge.net/). Structural factors and coordinates of ΔH-domain protein have been deposited in the Protein Data Bank under accession code 4W8C. The data processing and structural refinement statistics are summarized in Initial crystallization of the ΔH-domain protein was carried out by the sitting drop vapor diffusion method at 20°C using Crystal Screen, Index, SaltRx, PEGRx, and PEG-ion kits (Hampton Research). Crystals were grown from a 1:1 mixture of protein solution  and reservoir solution  using the hanging drop vapor diffusion method at 20°C. Prior to X-ray diffraction analysis, crystals were transferred into reservoir solution containing 20% (v/v) glycerol as a cryoprotectant and flash-frozen in the liquid nitrogen stream. The diffraction data were collected on beamline 5C at the Pohang Light Source . All data sets were scaled and merged using the HKL2000 package . The inich model . Furtherch model , after wch model . The finThe purified ΔH-domain protein was diluted to a final concentration of 0.2 mg/ml with buffer . Reducing agent dithiothreitol (DTT) was added to the protein sample at a final concentration of 10 mM to test involvement of the disulfide bond in dimer formation. Dimer formation was also confirmed by size exclusion chromatography (SEC).CoMsrA. Protein samples at concentrations of 2.5 and 1.5 mg/ml for full-length and ΔH-domain forms, respectively, were applied to a WTC-015S5 column mounted on a Shimadzu HPLC system equilibrated at a flow rate of 0.5 ml/min with 20 mM Tris-HCl (pH 8.0) and 100 mM NaCl at 298K. The scattered light intensity and protein concentration of the column eluate were measured using a DAWN HELEOS II laser detector and an OPTILAB T-rEX refractive index detector (Wyatt Technology), respectively. Data analysis from both detectors was carried by ASTRA software version 6.1 (Wyatt Technology).SEC coupled to multiangle laser light scattering (SEC-MALLS) was used to determine the solution molecular weight of full-length and ΔH-domain forms of The crystal structure of the ΔH-domain form comprising residues 1–144, corresponding to the catalytic domain, was determined at a resolution of 1.76 Å. In an asymmetric unit, there are two molecules of ΔH-domain protein, but each molecule shows different crystal structures. Refinement of crystal structure was tricky because while the structure of a molecule (chain B) of the two ΔH-domain proteins was easily solved, the other molecule (chain A) was difficult to refine. The correct phase of chain A was determined by molecular replacement using the chain B structure followed by iterative refinements. The final refined model contains chain A comprising 134 residues (7–140) and chain B comprising 137 residues (6–142). Superposition of chain A with chain B provides a root mean square deviation (r.m.s.d.) of 0.54 Å for 90 Cα atom pairs . Each chCoMsrA. The catalytic domain structure of full-length CoMsrA consists of five α-helices and six β-strands, which fold into a rolled mixed β-sheet surrounded by α-helices [CoMsrA gives r.m.s.d. values 0.62 Å for 97 Cα and 0.59 Å for 98 Cα atom pairs for chains A and B, respectively  that participates in the rolled mixed β-sheet. In contrast, the N-terminal end migrates in the opposite direction in the ΔH-domain form, where it interacts with another symmetric molecule in the crystal , which corresponds well to the ΔH-domain form of CoMsrA, shows an activity comparable to the full-length wild-type in the presence of DTT [E. coli MsrA truncated protein is present as a monomer in solution as the full-length wild-type [CoMsrA ΔH-domain form are quite different from those of the E. coli MsrA truncated form.The ΔH-domain form of e of DTT . The E. ild-type . The enz2 for dimer A and 2607 Å2 for dimer B, which correspond to 13% and 16% of the surface areas, respectively. Dimer B is more compact than dimer A by the PISA analysis [CoMsrA and the only Cys in the entire protein sequence [The two dimer structures have similar N-terminus swapping, but different interface areas. The buried areas are 2186 Åanalysis . The twoCoMsrA consisting of residues 1–144 corresponds well to other known MsrAs in sequence and structure [CoMsrA protein. The helical domain has several hydrogen bond interactions via the α8 helix with the two neighboring helices (α1 and α5) of the catalytic domain [CoMsrA catalytic domain [CoMsrA is similar to other MsrAs, including E. coli and bovine enzymes. The active site includes the highly conserved 15GCFWG19 motif and residues Tyr47, Glu55, Gln89, Tyr90, His137, and Tyr140  of individual monomers are interchanged between identical partners . The obsCoMsrA lacking the C-terminal helical domain is described. The active site is completely destroyed in the ΔH-domain protein, demonstrating its loss of catalytic activity. In addition, the ΔH-domain protein forms a dimer structure via swapping of the N-terminus and is predominantly present as a dimer in solution, whereas the full-length CoMsrA is a monomeric protein.The crystal structure of


Expansion is a modular protein that is conserved in protostomes. The first structure of the N-terminal domain of Expansion has been determined at 1.6 Å resolution and the new Nα-MH2 domain was found to belong to the Smad/FHA superfamily of structures. Drosophila embryos after inducing the transcription factor Tramtrack led to the identification of the protein Expansion. Expansion contains an N-terminal domain similar in sequence to the MH2 domain characteristic of Smad proteins, which are the central mediators of the effects of the TGF-β signalling pathway. Apart from Smads and Expansion, no other type of protein belonging to the known kingdoms of life contains MH2 domains. To compare the Expansion and Smad MH2 domains, the crystal structure of the Expansion domain was determined at 1.6 Å resolution, the first structure of a non-Smad MH2 domain to be characterized to date. The structure displays the main features of the canonical MH2 fold with two main differences: the addition of an α-helical region and the remodelling of a protein-interaction site that is conserved in the MH2 domain of Smads. Owing to these differences, to the new domain was referred to as Nα-MH2. Despite the presence of the Nα-MH2 domain, Expansion does not participate in TGF-β signalling; instead, it is required for other activities specific to the protostome phyla. Based on the structural similarities to the MH2 fold, it is proposed that the Nα-MH2 domain should be classified as a new member of the Smad/FHA superfamily.Gene-expression changes observed in  The analysis of gene-expression changes in Drosophila embryos after inducing Ttk loss of function and gain of function enabled the identification of the Expansion gene . A search for similar proteins to Expansion led to the identification of CG13183  with PSI-BLAST  as the query. Multiple sequence alignments with the query and the target proteins were generated with MAFFT v.7.164b using the iterative L-INS-i method .Sequences corresponding to Expansion proteins were retrieved from the Ensembl Metazoa database (BoxShade server v.3.21 (http://sourceforge.net/projects/boxshade/) written by K. Hofmann and M. Baron. A graphical representation of secondary structure was added to the alignment using the ESPript server  by means of ligation-independent cloning. The initial construct used for NMR screening and preliminary crystallization trials consisted of a fragment comprised of residues 29–240. We also prepared a second construct including an N-terminal extension (residues 3–240), which was used for structural studies.D. melanogaster Expansion cDNA  as a template. PCR amplification was carried out using the standard PCR Master Mix with 0.02 unit µl−1Taq DNA polymerase (Thermo Scientific), 1 ng µl−1 template DNA and 0.5 µM of each primer, using an annealing temperature of 321 K for the first ten rounds and 341 K for the last 30 rounds. After subsequent purification of the reaction product using the GeneJET PCR purification kit (Fermentas), ligation-independent cloning was performed in the presence of 6 µg µl−1 RecA DNA recombinase in the recommended buffer (New England Biolabs) at 310 K for 15 min. The full recombination reaction was then used for transformation in E. coli DH5α and positive clones were selected on kanamycin agar plates (50 µg ml−1). Positives clones were verified by DNA sequencing and subsequently transformed into the expression strain E. coli BL21 (DE3) Rosetta (Invitrogen), selecting positive clones on kanamycin (50 µg ml−1) + chloramphenicol (34 µg ml−1) agar plates.Inserts were obtained by PCR using the appropriate primers and the 2.3.M isopropyl β-d-1-thiogalactopyranoside (IPTG). Expression took place for 12–15 h and the cells were harvested by centrifugation . Labelled samples for NMR were prepared in a similar manner using minimal medium (M9) enriched with 15NH4Cl.Cultures were grown at 310 K until an OD of ∼0.6 was reached; the temperature was then lowered to 293 K and protein expression was induced by the addition of 1 mM Tris–HCl pH 7.2, 500 mM NaCl, 1 mM phenylmethylsulfonylfluoride (PMSF), 0.1 mM β-mercaptoethanol (BME), 0.1 mM EDTA supplemented with 0.1 mg ml−1 lysozyme, 0.25 mg ml−1 DNaseI, 25 mM MgCl2, 0.01 mg ml−1 RNaseA for lysis. Lysis was performed in a pressurized cell homogenizer at 277 K and the crude solution was incubated for 20 min on ice. The soluble fraction was then isolated by centrifugation .The cells were washed in TBS buffer and 5 g of cells were resuspended at 277 K in 10 ml buffer consisting of 50 mM Tris–HCl pH 7.2, 500 mM NaCl, 0.1 mM BME, 0.1 mM EDTA and eluted with a gradient to the same buffer freshly supplemented with 500 mM imidazole . Peak fractions were isolated and diluted with buffer  to lower the salt and imidazole concentrations for enzymatic digestion. Subsequently, the N-terminal 6×His tag was removed by overnight digestion at 277 K with Tobacco etch virus (TEV) protease and the digested protein was repurified by IMAC as described above. Size-exclusion chromatography (SEC) was performed on a Superdex 200 10/300 column using buffer consisting of 50 mM Tris–HCl pH 7.2, 200 mM NaCl, 0.1 mM BME and the peak fractions were collected and concentrated to ∼10 mg ml−1 using centrifugal filters (Amicon).Immobilized metal-ion affinity chromatography (IMAC) was performed on an ÄKTA FPLC system at room temperature using a prepacked 1 ml His-tag column . The domain of interest was purified using buffer consisting of 50 m2.4.The fly strains used are described in FlyBase. Df(2R)ED2247 and Df(2R)BSC879 uncover CG13188 and CG13183 and were used in transheterozygous conditions to analyze the absence of both genes (CG13188+CG13183 mutants). The transgenes used were P(TRiP.HMS01445)attP2 (UAS13188RNAi), P(TRiP.HMS01444)attP2 (UAS13183RNAi), P(TRiP.JF02218)attP2 (UASMedRNAi), UASDad and UASTkvCA.For overexpression experiments, we used the Gal4/UAS system  were stained for GFP. The bltGal4 in this combination also drives the other UAS transgenes.ImageJ and Adobe Photoshop and assembled using Adobe Illustrator.Confocal images were acquired with a Leica TCS-SPE system. Images were post-processed with 2.5.z-pulse field gradient unit and a triple  resonance probe head. The protein sample (0.7 mM) was equilibrated in 20 mM deuterated Tris–HCl, 150 mM NaCl buffer with 10% D2O and the pH adjusted to 7.5. The data were processed using the XwinNMR 3.5 software supplied with the Bruker NMR spectrometer.An HSQC (heteronuclear single-quantum coherence) NMR experiment (eight scans and 128 increments in the indirect dimension) was recorded at 298 K on a Bruker Avance III 600 MHz spectrometer equipped with a 2.6.v/v) 1,2-propanediol, 9%(w/v) PEG 20 000, 0.1 M glycine pH 9. The short protein construct crystallized in similar conditions.Initial crystallization conditions were identified from sparse-matrix screens. A series of gradient screens optimized the final condition and three-dimensional diffraction-quality crystals were finally grown in sitting drops at 293 K from 12%. The ensemble and the final model are superimposed and displayed in Supplementary Fig. S1.Sequence alignment and selection of homologues was performed with Rosetta model completion and relaxation in phenix.mr_rosetta, and automated rebuilding yielded the best results starting from Smad2 MH2 (PDB entry 1khx), which resulted in a model with a free R factor of 30%.Initial molecular-replacement solutions were rebuilt using phenix.refine . Iterative refinement and model building was continued until no significant improvement in R factors could be obtained. The refined model was validated using MolProbity  based on the β-strand content of each structure as calculated by DSSP  is mostly restricted to the MH2 domain (∼30%). A comparison with Smads reveals a similarity about 16%, which is limited to the MH2 domain. This similarity suggests that the Exp/Reb and Smads proteins share the presence of the MH2 domain and that the Exp/Reb proteins may constitute a new protein family with a specialized function in a subset of metazoan phyla.The sequence identity of the Exp/Reb http://metazoa.ensembl.org) using PSI-BLAST with the Expansion full-length sequence as the query. Our search retrieved two sets of matches. The first set reflects similarity to the entire query in nematodes, arthropods and other hexapods, suggesting the presence of orthologous proteins in these organisms. The second set reflects similarity of the N-terminal part of the sequence query to only the C-terminal part of Smads, specifically to the MH2 domain, as reported in the annotation of these proteins in the NCBI database. Remarkably, the similarity in the Exp/Reb subfamily covers an additional region of similarity preceding the canonical MH2 domain which is absent in the Smad sequences. The alignment comparing the sequences of the Exp/Reb domains with those of the MH2 domain of Smads is shown in Fig. 1a).To clarify this issue, we searched the Ensembl Metazoa database . A schematic representation of the domain organization of the Exp/Reb proteins and the similarity to Smads is shown in Fig. 1b). An alignment based on the full sequence of the Expansion proteins is shown in Supplementary Fig. S3.Secondary-structure predictions using 3.2.Drosophila. The TGF-β signalling pathway has been shown to play a key role in tracheal formation, specifying the most dorsal and ventral branches  all branches migrate along the dorso–ventral axis . We have observed that the pattern of dorsal and ventral branches was correct not only when Exp/Reb were downregulated using RNAi  but also when both genes were removed using a combination of chromosome deficiencies that uncovers both of them . In fact, we detected a completely different phenotype in loss-of-function conditions for these genes , related to the accumulation of an apical chitinous extracellular matrix , S4(h) and S4(i), the detected phenotypes of Exp/Reb downregulation are very different from those of the control, confirming that Exp/Reb do not appreciably transduce TGF-β signals. Our results are consistent with recently reported experiments . These two recombinant proteins were soluble and eluted as monomers in size-exclusion chromatography . According to NMR experiments the construct consisting of amino acids 29–240 was folded , and the initial crystallographic results were obtained using this construct. Since diffraction-quality crystals were also obtained from the larger construct, we focused the structural work on this construct consisting of amino acids 3–240. This would allow us to elucidate the role of the entire N-terminal region.Based on the sequence conservation and on the secondary-structure predictions, we selected two different domain boundaries for structural studies: a construct including the most conserved predicted helix (amino acids 29–240) and a second construct comprising nearly the full N-terminal region of the protein (amino acids 3–240) Fig. 1b. TheseP21 to a maximum resolution of 1.6 Å. Matthews coefficient analysis indicated a solvent content of ∼27% for one protomer (∼28 kDa) in the asymmetric unit, which was consistent with the tight packing observed in the structure.Diffraction data were collected from a monoclinic wedge-shaped crystal with approximate dimensions of 10 × 30 × 150 µm. The data were processed in space group 3.3.2.Phaser . The selected solution (using Phaser) reported values of LLG = 56.1, TFZ = 4.3 and Rval = 58.5 at 3 Å resolution, and allowed us to partially trace the map. However, we were unable to perform rigid-body refinement as we could not improve the R factors beyond Rwork = 0.5207 and Rfree = 0.5215. Similar values were obtained for other resolution ranges.Owing to the anticipated structural resemblance of the new domain to the canonical Smad MH2 domain, we first attempted to solve the structure by conventional molecular replacement (MR) using MR-Rosetta algorithm, which has recently been demonstrated to facilitate molecular replacement in cases where only search models of low sequence identity are available. Using the methods compiled in the MR-Rosetta pipeline . The structure comprises a β-sandwich core of twisted antiparallel β-sheets capped at one end by a three-helix bundle and at the other by a region containing an α-helix and several loops. In Smad MH2 domains this region is commonly referred to as the ‘loop–helix region’ . This new element of secondary structure is named Nα to indicate its position at the N-terminus of the domain and, most importantly, to maintain the canonical nomenclature of MH2 domains . A Cα trace of the Nα-MH2 domain and the electron-density map at contour levels of 1σ and 2σ are shown in Fig. 2f). A few additional structural differences are observed in the length of the helices that form the helical bundle and in the area adjacent to the ‘loop–helix region’ comprised of helix α2, a loop and strand β8, referred to here as the ‘H2 region’ . Also significant is the reduced length of the L3 loop that connects β10 and β11. This loop in Smad MH2 domains comprises an interaction motif for phosphorylated residues, and is fundamental to receptor binding and to the quaternary structure and function of the Smad proteins . To observe the effect of the differences in and around the L3 area, we have represented the surface charge distribution of the Expansion Nα-MH2 domain and that of Smad2 for comparison  and highlighted the presence of positively charged patches in the Smad2 MH2 domain that are absent in Expansion.At a first glance, the most obvious structural difference when superimposed on Smad2 MH2 domains is the presence of the Nα helix, which is formed by the N-terminal residues 34–47 and covers one side of the core β-sandwich  is a new addition to the canonical MH2 fold characteristic of Smad proteins. This novel structural element packs against and interacts with the triple-helical bundle and covers the outer surface of the β-sandwich core, which represents the interface between adjacent monomers in the functional trimer of the Smad proteins. Previous results have suggested how cancer-derived mutations, which map to the same area in the Smad proteins, inhibit the formation of the functional heterotrimer  onto one monomer of the Smad2 MH2 homotrimer (shown in light grey), the Nα helix overlaps with the area occupied by the ‘loop–helix region’ of the adjacent monomer in the trimer (in the figure this second MH2 is shown in dark grey). This structural ‘clash’ most certainly compromises the formation of homotrimers by the Nα-MH2 domain in a manner similar to that observed for the Smad MH2 domains. Furthermore, it will also prevent the formation of heterotrimers with the MH2 domain of Smad proteins.The N-terminal helix observed in Expansion Nα-MH2 , the linker preceding the MH2 domain does not adopt a defined tertiary structure. However, in several structures of Smad complexes segments of the linker have been observed to adopt different conformations when folding upon interaction with other proteins . However, no electron density could be observed for this predicted helix, likely reflecting a degree of flexibility in this area. Patches of positive electron density observed in a difference-density map (mFo − DFc) suggested that the region comprising the first 24 residues extends into a solvent channel of the crystal structure; however, any effort to improve the model in this region did not improve the refinement statistics and the model was therefore truncated at the N-terminus.The secondary-structure predictions of the Expansion family of proteins suggested the presence of a second helix at the very N-terminus of the protein Fig. 1a. Howev3.3.4.X-S motif at the C-terminus of the MH2 domain, leading to heterotrimer formation through the MH2 domain of two R-Smads with the common Smad4. Formation of the heterotrimer triggers the subsequent translocation of Smads to the nucleus. Mutations in the L3 loop of the Smad proteins abolish the formation of heterotrimers and hence signalling in the TGF-β pathway . In the Expansion Nα-MH2 domain the region of amino acids 162–165 that would correspond to the β8 strand in Smads lacks a defined secondary structure; it instead bears characteristics of random coil similar to most of the adjacent H2 region, apart from helix α2. In Smad proteins the H2 region extends from strand β7 in the upper β-sheet, with helix α2 followed by a short loop that connects to strand β8 continuing to strand β9. In the Nα-MH2 domain strand β7 is followed by a large loop connected to a reoriented helix α2, followed by an extended region (corresponding to strand β8) continuing to strand β9 .The Smad MH2 domain is commonly known to support protein interactions, and interestingly the overall composition of the Expansion Nα-MH2 domain remains largely the same despite the low degree of sequence identity. However, the H2 region that has been established as a protein–protein interaction site in Smad proteins  also shows that the interaction occurs through β-sheet augmentation of strand β8  an intrinsic folding property of this area. Of interest in the remodelling of the H2 region of the Expansion Nα-MH2 domain as a potential protein-interaction site is the consideration of the degree of specificity that this remodelling might provide.In the Smad proteins the H2 region and the β8 strand are implicated in protein–protein interactions by β-sheet augmentation, similar to common PDZ domains  speculated that the different flanking regions of the β-sandwich in the C-terminal regulatory domain of IRF-3 and Smad-MH2 developed on the β-sandwich scaffold of the FHA protein to facilitate phosphorylation signalling in higher organisms.IRF proteins are only found in vertebrates, whereas the Smad MH2 domain and the FHA domain co-exist in metazoans and the FHA domain is also found in prokaryotes. Durocher  al. 2000 found th4.We have determined the structure of the Nα-MH2 domain present in Expansion at 1.6 Å resolution. The addition of the N-terminal helix, the differences in the L3 loop and its lack of a role in the canonical TGF-β signalling pathway support the classification of Expansion as a new family of proteins that share the presence of the MH2 domain with Smads. Furthermore, the structural differences between the Smad MH2 and Expansion Nα-MH2 domains could have evolved to host a different range of protein-interaction partners, with implications for different cellular functions which apparently have been conserved in protostomes .For these reasons, we suggest that Expansion should not be termed a ‘Smad-like’ protein. Furthermore, we propose that the Smad/FHA family of structures should be ‘expanded’ to also include the Expansion Nα-MH2 domain.Expansion Nα-MH2, 4r9pPDB reference: 10.1107/S1399004715001443/kw5112sup1.pdfSupporting Information.. DOI:


To ensure proper gene regulation within constrained nuclear space, chromosomes facilitate access to transcribed regions, while compactly packaging all other information. Recent studies revealed that chromosomes are organized into megabase-scale domains that demarcate active and inactive genetic elements, suggesting that compartmentalization is important for genome function. Here, we show that very specific long-range interactions are anchored by cohesin/CTCF sites, but not cohesin-only or CTCF-only sites, to form a hierarchy of chromosomal loops. These loops demarcate topological domains and form intricate internal structures within them. Post-mitotic nuclei deficient for functional cohesin exhibit global architectural changes associated with loss of cohesin/CTCF contacts and relaxation of topological domains. Transcriptional analysis shows that this cohesin-dependent perturbation of domain organization leads to widespread gene deregulation of both cohesin-bound and non-bound genes. Our data thereby support a role for cohesin in the global organization of domain structure and suggest that domains function to stabilize the transcriptional programmes within them.Chromosomal compartmentalization has been recognized as important for genome function. High-resolution techniques such as Hi-C, ChIP- and 4C-seq offer novel insights into cohesin's dynamic role in shaping the nuclear architecture. Recent developments in sequencing-based chromosomal contact mapping  using a combination of Hi-C, high-resolution 4C-seq and 3D DNA FISH. Quantification of chromosomal contacts at multiple scales showed that cohesin/CTCF co-occupied sites are focal points of chromosomal contact insulation, associated with both the borders of topological domains and finer-scale structures within such domains. Our analysis suggests that domain demarcation arises from a remarkably selective and complex hierarchy of cohesin/CTCF-anchored long-range interactions. Importantly, cohesin-deficient post-mitotic nuclei exhibit global architectural changes associated with a decrease in long-range cohesin/CTCF contacts, universal relaxation of domain structure and nuclear decompaction. These structural changes are accompanied by extensive perturbation of gene expression involving not only a deregulation of cohesin-bound genes, but also a widespread transcriptional response of cohesin-free genes, likely as a result of domain relaxation. Taken together, these observations show that selective cohesin/CTCF contacts constitute a key mechanism underlying chromosomal domain architecture, and suggest that this architecture functions to stabilize mammalian transcriptional programmes.et al, et al, et al, et al, 1-purified NSC cells; Supplementary Figure S4) exhibited the characteristic decrease in contact probability with increased genomic separation  and recapitulated the topological domain structures that have been recently described  between multiple elements separated by a cohesin/CTCF site. We performed the analysis at multiple distance scales  to induce a deletion within the Rad21 gene and within 96 h, Rad21 protein levels had dropped to 11% of control levels . Hi-C contact maps generated from Rad21Lox/Lox and Rad21Δ/Δ ASTs revealed global differences in chromosomal contacts both within and between domains  and increased inter-domain contacts (red), while domain borders remain similar . Thus, Hi-C analysis of Rad21-deficient cells supports a role for cohesin in maintaining the proper organization of interphase chromosomes.Contact insulation analysis in Rad21 loss. According to the Hi-C data, intra-domain contacts in the region decrease, whereas inter-domain contacts are increased in Rad21Δ/Δ cells. 3D DNA FISH analysis of two probes separated by 500 Kb and designed to hybridize to the borders of the same active domain indicated a significant increase in inter-probe distance in Rad21-deficient nuclei  , further supporting our observations from the inter-probe distance analysis. Finally, we also observed that nuclear volumes of Rad21-deficient ASTs were 26% larger on average compared to controls . We found that controls , suggestet al, Rad21Δ/Δ cells. The results indicate that there is a significant decrease in the intensity of the above described cohesin–cohesin contacts  and computed the mean Hi-C contact intensity between all 2 Kb genomic bins located up to 40 Kb upstream and downstream of each binding site. The data were pooled for thousands of pairs, quantifying average contact intensities at the point of the cohesin/CTCF interaction and the regions flanking it . ConsistInterestingly, no significant contact enrichments were detected between cohesin/CTCF sites and non-cohesin/CTCF sites . EnrichmRad21Lox/Lox and Rad21Δ/Δ ASTs with extensive upregulation and downregulation of hundreds of genes. Such extensive transcriptional changes can be indicative of an indirect activation of a general cellular programme ; however, a comprehensive analysis of the genes deregulated as a result of Rad21 deficiency did not reveal a significant overlap with known transcriptional modules nor an enrichment for particular functional categories (Supplementary Table S1), suggesting that ASTs respond to cohesin deficiency in a way that is unlikely to be controlled by common secondary signalling and transcriptional regulators.We used RNA-seq to determine whether the global domain perturbation we observe in cohesin-deficient ASTs has an effect on the transcriptional status of these cells. Genome-wide analysis  showed rAnalysis of cohesin/CTCF binding at or near the TSSs of deregulated genes showed that the majority of deregulated genes do not have a cohesin/CTCF binding site within 10Kb of their TSS , howeverDeptor from its neighbouring silent gene Col14a1 (Deptor (2.6-fold) and upregulation of Col14a1 (7.1-fold). Similarly, loss of cohesin–cohesin loops at the endothelin-converting enzyme-1 (Ece1)  and olfactomedin-like protein 3 precursor (Olfml3) loci (Igfbp5) and regulator of G-protein signalling 3 (Rgs3) loci  loci  is assocWe present several lines of evidence in support of a central role for cohesin in the organization of chromosomal domain structure. Using Hi-C in NSC and AST cells, we show that chromosomal domain architecture is tightly correlated with cohesin/CTCF binding sites, and that in cells lacking functional cohesin complexes, the stability of this architecture is perturbed. Using 3D DNA FISH, we demonstrate that the changes in domain structure of cohesin-deficient cells identified by Hi-C reflect domain decompaction. Using high-resolution 4C-seq, we show that cohesin/CTCF sites interact preferentially to define both intricate loop structures within domains and the borders of megabase-scale chromosomal domains. In Rad21-deficient cells, many of these preferential contacts are lost, accompanied by a general relaxation of the chromosomal domain structure. Thus, domain decompaction comes about as a result of the reduction in cohesin/CTCF distal contacts, which in turn results in more non-specific contacts between domains, indirectly reducing the effective insulation around cohesin binding sites.et al, et al, et al, The recent discovery of Hi-C contact domains  genes at some level. Nevertheless, a global effect of chromosomal structures on gene regulation may be mostly associated with maintenance of epigenetic stability and regulation of gene expression noise, rather than classical changes in gene regulation. Moreover, the regulatory effect of cohesin-mediated domain structure may become critical in cycling cells, which must tolerate highly dynamic chromosomal processes and then re-model their chromosome architectures in order to stabilize appropriate gene expression programmes. Further insights from Hi-C and 4C-seq studies combined with extensive epigenetic data and thorough models of gene regulation will be needed in order to eventually develop a comprehensive and quantitative understanding of the complex ways in which chromosomal architecture sets the stage for gene regulation.et al Rad21Lox/Lox AST cells. Hi-C and 4C-seq libraries were prepared according to previously described protocols with minor adjustments (Lieberman-Aiden et al, et al, et al, et al et al Mouse NSCs were generated from ESCs and cloned using a protocol described in Conti The data analysed in this study has been deposited in the GEO database with ID number GSE49018.


Welding-induced deformation not only negatively affects dimension accuracy but also degrades the performance of product. If welding deformation can be accurately predicted beforehand, the predictions will be helpful for finding effective methods to improve manufacturing accuracy. Till now, there are two kinds of finite element method (FEM) which can be used to simulate welding deformation. One is the thermal elastic plastic FEM and the other is elastic FEM based on inherent strain theory. The former only can be used to calculate welding deformation for small or medium scale welded structures due to the limitation of computing speed. On the other hand, the latter is an effective method to estimate the total welding distortion for large and complex welded structures even though it neglects the detailed welding process. When the elastic FEM is used to calculate the welding-induced deformation for a large structure, the inherent deformations in each typical joint should be obtained beforehand. In this paper, a new method based on inverse analysis was proposed to obtain the inherent deformations for weld joints. Through introducing the inherent deformations obtained by the proposed method into the elastic FEM based on inherent strain theory, we predicted the welding deformation of a panel structure with two longitudinal stiffeners. In addition, experiments were carried out to verify the simulation results. Welding-induced deformation not only negatively influences manufacturing accuracy but also degrades the appearance of product. There are too many factors which have influences on the final deformation during welding process, so it is not easy to find a reasonable method to reduce or control welding distortion when only relying on experiments or experiences. However, if welding deformation can be predicted beforehand, the simulation results will be helpful to reduce welding deformation especially in large and complex welded structures. Therefore, it is very important and urgent to develop an effective method to accurately predict welding deformation.Till present, researchers have proposed two numerical approaches based on FEM to estimate welding deformation. One is thermal elastic plastic FEM . In thisBecause of the limitation of thermal elastic plastic FEM, another method named inherent strain method was proposed –5 to effAt present, there are two methods which can be used to obtain the inherent deformations for a welded joint. One is the experiment method and the other is thermal elastic plastic FEM. Because the longitudinal shrinkage and longitudinal bending are very small in many cases, it is hard for the experiment method to obtain their accurate values , 7. On tx, y, and z directions at a small number of locations of a typical joint before and after welding are measured by experiment, and the inherent deformations can be estimated based on these three dimensional (3D) coordinates.To overcome the above disadvantages of both experiment method and thermal elastic plastic FEM, we proposed a new method named inverse analysis method to obtain the inherent deformations for typical joints. This method is a new approach which is based on the combination of experiment and elastic FEM. In the inverse analysis, the coordinates in As an example, the inherent deformations of a fillet welded joint were calculated by the proposed method in the present study. Using the estimated inherent deformations, the welding deformation of a panel with two longitudinal stiffeners was predicted by the elastic FEM. Meanwhile, experiments were carried out to verify the simulation results. Through comparing the simulated results and the measurement results, the effectiveness of the developed computational approach based on inverse analysis has been verified.δxi), transverse shrinkage (δyi), longitudinal bending (θxi), and transverse bending (θyi). Another type of deformation is a combination of the above components. According to inverse analysis theory, if the distribution of the inherent deformation is expressed in terms of a small number of parameters, each component of inherent deformation can be determined based on the measured values of deformation at limited locations. In this study, an inverse analysis for obtaining inherent deformation in typical joint was proposed under the following hypotheses.There are four basic components in a typical joint. The four components are longitudinal shrinkage, transverse shrinkage, longitudinal bending, and transverse bending (angular distortion). The first two components are the in-plane deformation and the last two components are out-of-plane deformation.n parameters, the total number of parameters is 4n.If the distribution function of each component of inherent deformation is expressed by The distribution range (length and width) of inherent deformations in a joint can be determined according to the results obtained by the thermal elastic plastic FEM analysis.m points are measured before and after the welding. The joint has no deformation before welding, while it deforms after welding. Through measuring the 3D coordinates before and after welding at limited locations, the basic deformation can be determined.The 3D coordinates of In principle, the welding distortion in a typical joint is mainly caused by four components of inherent deformations, namely, longitudinal shrinkage . Thus, the necessary condition for determining the inherent deformation is (3m − 6) > 4n.Since the 3D coordinates measured at ai  according toai represents the components of inherent deformation and a = {a1,…, an4}, Fj(ai) is the deformation of fillet joint which is computed by the elastic FEM using the inherent deformation ai, and Fkm is the measured deformation.Based on the above idea, 17 points on the fillet joint as shown in ai and the deformation of the fillet joint Fj(ai) is nonlinear, therefore, the inherent deformation ai cannot be determined from the measured value Fjm by a single step. It must be determined through an iterative process based on the following Taylor expansion:ai is the correction value of the approximate solution at the previous step. Fjm is the measured deformation. Fj(ai) can be computed by the elastic FEM using the inherent deformation ai. The iterative procedure to obtain ai used in inverse analysis is shown in Fj/∂ai] is the slope of the curve Fj(ai) at a certain point; ai is calculated by an iterative process until the convergence criterion is met.Since the relationship between the inherent deformation Fj/∂ai] is 3m − 6 and 4n, respectively, while the number of rows and columns in matrix {Fjm − Fj(ai)} is 3m − 6 and 1, respectively. Thus, Δai should becalculated using the following equation:The number of rows and columns in matrix , [D], and [K] are strain-displacement matrix, elastic stress-strain matrix, and stiffness matrix, respectively. Using the inherent deformations shown in As the result of inverse analysis, each component of inherent deformations, namely, longitudinal shrinkage, transverse shrinkage, longitudinal bending, and transverse bending (angular distortion), is summarized in z-direction (angular distortion) is shown in In this study, angular distortion and transverse shrinkage are investigated by means of experiment and numerical simulation. As an example, the distribution of the displacement in To clarify if the average values of each component of inherent deformations can be used to accurately predict welding deformation, the deflection along the neutral plane is plotted in In order to investigate the calculated precision of welding deformation for relatively large structure using the inherent deformations obtained by the proposed inverse analysis, one experimental mock-up as shown in In the experiments, in order to avoid the influence of welding sequence on the final distortion, all members in the welded structures were tack-welded before welding. The length of each tack weld bead is approximately 15 mm. The experimental material, the welding methods, and the welding condition are the same as those of the experimental model as mentioned in In the experiments, 3D photography technique was also used to measure welding distortion. The detailed description can be found in . After tThe welding deformation of the panel structure, whose dimensions are the same as those of the mock-up, was predicted by elastic FEM based on inherent strain theory. The mesh of the model is shown in The final deflection of panel model is shown in Using the 3D coordinates of the 17 points measured before and after welding, the four components of the inherent deformations in a fillet joint can be estimated by the inverse analysis.Using the average value of the four components of inherent deformations along welding line obtained by inverse analysis, the welding distortion of fillet joint was simulated by the FEM based on inherent strain theory. The good agreement between the predictions and the measured data demonstrates that the average value of each inherent deformation component along the welding line estimated by the proposed inverse analysis can be regarded as equivalent value.Using the inherent deformations of the fillet joint, the welding deformation in a panel structure with two longitudinal stiffeners was predicted. Through comparing the simulated result and the measured data, we found that the inherent deformations estimated by the inverse analysis can accurately predict the total welding deformation for the panel structure. The elastic FEM analysis can be completed in a very short time and the short computing time is very meaningful for practicing engineering analysis.In this work, a new method based on inverse analysis was proposed to obtain the inherent deformations for a fillet joint. Using the estimated inherent deformations, the welding deformation of a panel structure with two longitudinal stiffeners was simulated. Through comparing the prediction and the measurements results, the following conclusions can be drawn.


P. falciparum and L. major as examples, we investigate the extent to which HMM/HMM comparisons can identify new domain occurrences not already identified by sequence/HMM approaches. We show that although HMM/HMM comparisons are much more sensitive than sequence/HMM comparisons, they are not sufficiently accurate to be used as a standalone complement of sequence/HMM approaches at the genome scale. Hence, we propose to use domain co-occurrence — the general domain tendency to preferentially appear along with some favorite domains in the proteins — to improve the accuracy of the approach. We show that the combination of HMM/HMM comparisons and co-occurrence domain detection boosts protein annotations. At an estimated False Discovery Rate of 5%, it revealed 901 and 1098 new domains in Plasmodium and Leishmania proteins, respectively. Manual inspection of part of these predictions shows that it contains several domain families that were missing in the two organisms. All new domain occurrences have been integrated in the EuPathDomains database, along with the GO annotations that can be deduced.Identification of protein domains is a key step for understanding protein function. Hidden Markov Models (HMMs) have proved to be a powerful tool for this task. The Pfam database notably provides a large collection of HMMs which are widely used for the annotation of proteins in sequenced organisms. This is done via sequence/HMM comparisons. However, this approach may lack sensitivity when searching for domains in divergent species. Recently, methods for HMM/HMM comparisons have been proposed and proved to be more sensitive than sequence/HMM approaches in certain cases. However, these approaches are usually not used for protein domain discovery at a genome scale, and the benefit that could be expected from their utilization for this problem has not been investigated. Using proteins of  With the continuous improvement of genome sequencing technologies, an increasing number of new genomes are emerging everyday, enhancing basic knowledge on the diversity of organisms and providing valuable data to understand their biology and evolutionary relationships. A survey of the Uniprot database indicates, however, that this knowledge is highly unbalanced, with most of sequenced Eukaryotes being related to Plant and Unikont super-groups see . Since fLeishmania and Plasmodium species, where around 80% of the amino acids in proteins are not covered by any domain identified so far.Several approaches and databases have been developed to define and identify domains. One of the most widely used domain schemes is the Pfam database A significant improvement over sequence/profile approaches has been accomplished by profile/profile methods Leishmania major, that causes a cutaneous form of leishmaniasis, and the apicomplexan Plasmodium falciparum which is responsible for the deadliest form of human malaria. More specifically, our aim is to use HHPRED to identify new domain occurrences not already identified by HMMER using standard thresholds on these two species. We show that although HHPRED outperforms HMMER in terms of sensitivity for identifying divergent occurrences, it is not sufficiently accurate to be used as a standalone annotation tool on these particular domains. Hence, a post treatment is required to be able to distinguish between true and false positives. We propose to use domain co-occurrence property for this purpose. The co-occurrence property results from the tendency of most protein domains to preferentially appear along with few favorite domains in the same protein. This enable us to assess the occurrence of a particular domain in a protein by looking at the other domains of the same protein. We present the results achieved by this combined approach on L. major and P. falciparum species, and we show that it greatly improves the domain coverage and the functional annotations that can be attached to these organisms. Interestingly, many new domain families that had never been seen before in these organisms were discovered. We discuss these results and give a few examples that illustrate the new insights that can be deduced from these predictions and their relevance for improving the understanding of the biology of these human pathogens.Here we use HHPRED to help annotate proteins of two main human pathogens, the kinetoplastid L. major and P. falciparum. All Pfam domains that can be identified by HMMER with the recommended score thresholds are considered as known in the following, and our aim is to identify new domain occurrences. Alignments were done both in global  and local mode . Contrary to previous HMMER versions, the last HMMER version 3.0 only handles local alignments. Hence, we used HMMER version 2 to determine the known domain occurrences in global alignment mode. Moreover, as the Pfam26 HMMs cannot be handled by HMMER2, we used the Pfam23 release instead of Pfam26 for the global mode experiments. L. major and P. falciparum protein sequences were downloaded from Trytrip (http://tritrypdb.org/) and PlasmoDB databases (http://plasmodb.org/), respectively. Each protein sequence was first transformed into an HMM by computing a multiple alignment of homologous sequences. This was done in two ways. The first approach (hereafter denoted as phylum specific) involves using only homologous sequences of species belonging to the same phylum as the target organism—for P. falciparum we use 6 Apicomplexa, and 6 Trypanosomatidae for L. major (see phylum non-specific) involves using the HHBlits approach hhsearch procedure. hhsearch computes a score for each HMM pair i.e. the probability that the two HMMs will emit the same sequence of residues i.e. the least likely domain) was removed. The remaining matches are hereafter denoted as potential domains.The aim of this work is to boost Pfam domain predictions using profile/profile comparison in order to enrich our knowledge on the protein domain catalogue (and hence protein functions) of the two major pathogens ajor see . The secL. major proteome. Note that this observation concerns a very specific case: namely, all well-conserved domains have been already identified, and the method is challenged on the difficult cases only. Hence, it does not imply that HHPRED lacks accuracy for the general case. Most importantly, we can see in the figure that for moderate and high e-value thresholds, the two approaches show very different results, and HHPRED detects a higher number of domains than HMMER at same FDR. Although HHPRED does not ensure high precision results, it is more sensitive than HMMER at moderate and low precision. Hence, provided that we can filter out the false positives, numerous new domain occurrences can be expected from HHPRED predictions. At the genome scale, this kind of post-treatment must be done in a fully automatic way, and we propose to use the CODD procedure First, we wanted to estimate the overall quality of new predictions achieved by HHPRED. Several sets of potential domains of increasing size were formed using e-value thresholds ranging from i.e. that are observed in the same proteins a significantly higher than expected number of times. These domain pairs are stored in the list of Co-occurring Domain Pairs (CDP). Next, given a set of potential Pfam domain occurrences, CODD selects those that form, with another domain of the same protein, a pair in the CDP list. Domains selected this way are assigned as being certified. Three certification types can be considered. The first and most accurate one is to use already known Pfam domains of the protein to certify the presence of the potential domains. A complementary solution is to use the other known InterPro (i.e. non-Pfam) domains. This usually increases the number of certifications. However, because of the heterogeneity of the InterPro database, the certifications achieved this way may be of lower quality than those achieved with Pfam domains. These first two solutions certify domains solely in proteins in which at least one domain is already known. To overcome this limitation, a third solution is to certify the potential domain by another potential domain of the protein. With this solution, all pairs of potential domains of the protein are enumerated, and the two domains are certified if the pair belongs to the CDP list. Finally, CODD uses a shuffling procedure to provide an estimate of the FDR associated with the certified domains The CODD procedure is a computational approach which enables us to select the most likely domains among a set of potential domains, while controlling the false discovery rates associated with the predictions. Like the FDR estimation method used above, CODD relies on the tendency of the domains to appear preferentially with few other domains. The principle is as follows  were ran to detect the potential domains below a predetermined e-value threshold, and the CODD procedure was applied, using the remaining known domains of each protein for the certification. The FDR associated with the predictions was estimated, and we computed the number of discarded domains that are recovered as well as the number of new domains that are discovered. P. falciparum, around 98% of the domains predicted by HMMER+CODD belong to the discarded known-domains, and 437 out of the 561 discarded domains (78%) are recovered. For HHPRED+CODD, the results are very different: 94% of the discarded domains are recovered, while 300 certified domains are completely new. To get a rough idea about the number of false positives in both approaches, we computed the number of new domains that overlap a discarded domain. For HMMER+CODD this number equals zero, which was expected because all known domains (and hence the discarded ones) were identified with HMMER. For HHPRED+CODD, this number equal 2, which represents 0.6% of the 300 new domains, and 0.2% of the total number of certified domains, i.e. far less than the 3% estimated FDR. Similar results are achieved on L. major.We first thought to assess this approach on the already known domains using a cross-validation procedure. We selected the proteins of L. major and P. falciparum in both modes and using different e-value thresholds. For each threshold, the number of certified domains among the potential domains below this threshold was computed, and the FDR associated with these predictions was estimated. For comparison, we also included the results achieved by CODD on new domains predicted by HMMER2  and HMMER3  for different e-value thresholds. As we can see, and in accordance with our first test, HHPRED greatly outperforms HMMER when used in conjunction with CODD. Moreover, the CODD procedure improves the accuracy of the approach, and FDRs as low as We then ran the CODD procedure on all potential domains detected by HHPRED—with both the phylum specific and non-specific approaches—using already known Pfam domains for the certifications. This was done in the local and global alignment modes of HHPRED. The phylum specific and non-specific approaches approaches give close results in terms of accuracy. The non-specific approach outperforms the specific one for Leishmania whereas the species-specific approach achieves better results for Plasmodium proteins. This can be explained by the fact that homologous proteins in Leishmania species usually have high sequence identity. Hence, the multiple alignments built from these sequences may lack diversity. The same trend holds for the two other types of certification , which corresponds to an increase of around P. falciparum and L. major. Domain pairs in the CDP list have been selected on the basis of the whole set of Uniprot proteins. Because P. falciparum and L. major likely possess specific domain-combinations, a question remains about the impact of these specificities on the certification process. First, it is important to note that a combination absent from the CDP list does not totally impede the certification of the domains involved in this combination: in proteins with more than two domains, when a domain P. falciparum and L. major, and compared it to the domain combinations found in any Uniprot proteins restricted to Vertebrates, Fungi, Plants, Bacteria, and Archaea. The number of domain pairs present in P. falciparum and L. major are 976 and 1008, respectively. Among these, 96 and 159 are not found in the other phyla. We then identified the highly co-occurrent domain pairs of P. falciparum and L. major using the same procedure as the one used to select the CDP list. With a p-value of 1%, we found 834 and 922 highly co-occurrent domain pairs in P. falciparum and L. major, respectively. Among these, only 19 and 41 are missing in the original CDP list, respectively.One issue we have eluded so far concerns the specificities of the domain combinations in species like P. falciparum and L. major, respectively. Among these, We next investigated GO annotations that could be deduced from all newly identified domains. Some domains have been associated with specific GO terms by the InterPro consortium. The policy is to associate with a given domain the annotations shared by all annotated proteins possessing this domain. This stringent policy potentially misses numerous domain-annotation associations, because a single protein possessing a domain One point that is important to bear in mind is the question of the functional conservation of the divergent domains identified by our approach. It is a well known fact that the functional similarity of two homologous proteins is generally a function of their sequence similarity (see for example http://www.atgc-montpellier.fr/EuPathDomains/), along with the GO annotations that can be deduced from all these new domains. EuPathDomains is a protein domain database dedicated to most of the eukaryotic pathogens present from the EuPathDB portal (http://eupathdb.org/eupathdb/).All new domain occurrences are available in P. falciparum and L. major proteins by combining CODD and HHPRED in local alignment mode, respectively. For a first investigation we chose to focus our discussion on the domains identified by global alignment and that had never been observed on any protein of the studied organism, since they are likely to be the more relevant in terms of functional novelty. To further reduce these examples to a number that can be handled manually, we chose to examine only domains identified by the phylum specific approach and which are not identified by HMMER+CODD at 10% FDR. This represents a set of 36 and 37 domains in P. falciparum and L. major, respectively. In our analyses, we considered known functions of the protein on which the domain was found. Particular attention was given to the position in the protein sequence where the novel domain was discovered as well as to the description and GO annotations associated with this domain. We then tried to investigate the functional relationship with the biological function of the protein. For some of these predictions, we found direct support in the literature. We also took into consideration other species where the domain is known and tried to find common points and explanations that could help to understand the association of this domain to the protein. In the case of hypothetical proteins, this may suggest the attribution of new functions. When a predicted domain could be specific to one developmental stage, we looked at the transcriptional profiles of the protein. From all this information, we tried to infer biological knowledge that could be gained from these predictions. We discuss below several examples that have been found in the two species. Interested readers can find the full analysis in A survey of knowledge gained by the HHPRED+CODD approach can serve as a starting point for developing new hypotheses to gain further insight into the biological mechanisms of these parasites. Hence, we sought to analyze and characterize the specificities of newly discovered domains and their contribution to the understanding of parasite biological functions. We then tried to assess the functional relevance of these novel annotations based on the known and predicted properties of the corresponding protein in each parasite. For this purpose, we performed a detailed case by case manual analysis of the new domains families observed in each species. As shown in WH2 domain known for its interaction with actins, was detected in the protein PFL0925w, currently named “formin 2, putative” in PlasmoDB.At first sight, we noticed that the majority (about DENN and TFIID_90k) do provide or precise functions to proteins in which the previously identified domains were either not very informative or had no precise biological function attached to it (i.e. WD40). WD40 domains, which are among the 10 most currently found domains in eukaryotic proteins, indicate interaction properties with other proteins, peptides or nucleic acids and hence, WD40 proteins are involved in a wide variety of functions such as signal transduction, cytoskeleton assembly, RNA maturation, chromatin dynamics, vesicular trafficking, etc. WD40 domains is therefore invaluable to better qualify the functions of this otherwise highly diverse WD40 proteins family. Example for such a refinement are listed in PF3D7_1138800.In some occurrences, the new domains , that could be used by salivary gland-sporozoites to invade the insect-host tissues T. gondiiLysM domain was identified on PFA0130c, a member of the “serine/threonine protein kinase, FIKK family” that could play an important role in erythrocyte modelling LysM domain are found in a variety of enzymes involved in bacterial cell wall degradation A series of new domains putatively involved either in invasion or egress were also discovered. A “DHQ_synthase domain, that was predicted at position 1–171 of the PFB0280w protein. DHQ stands for 3-dehydroquinate and indeed, the enzyme encoding 3-dehydroquinate synthase activity, which is involved in the first steps of the shikimate pathway, has yet to be identified in Plasmodiumhttp://sites.huji.ac.il/malaria/). The shikimate pathway allows the synthesis of aromatic amino acids and is present in plants and microorganisms. It has been shown to be active in Plasmodium and is considered as an attractive drug target because it is absent from mammalian cells DHQ synthase activity corresponds to the second step) are still elusive in PlasmodiumPFB0280w, which is currently described as bi-functional enzyme encoding steps 5 and 6 of the shikimate pathway—it harbours the EPSP and the SKI domains, both involved in the shikimate pathway—, could therefore be a malarial ortholog of the arom protein, a penta-functional enzyme typically found in fungi. Interestingly, in T. gondii, a DHQ-synthase domain has also been found in a penta-functional enzyme homologous to the fungus arom protein.A very interesting discovery concerns a Rad21_Rec8_N and Rad21_Rec8 domains in the conserved Plasmodium protein PF14_0380 that did not have any known GO function. Both predicted domains suggest involvement in the mediation of sister chromatid cohesion during mitosis and meiosis, as part of the cohesin complex. The indication in PlasmoDB that PF14_0380 interacts with PFC0155c protein, annotated as “DNA directed RNA pol. Subunit I” further supports this hypothesis.Finally, this method could even provide functions for proteins previously totally devoid of both domains and annotations, thanks to the use of potential domains for the certification process. We predicted, for example, the P. falciparum, several L. major novel domains are complementary to known protein features and confirm functions associated with them. For example, we predicted the Ku-c domain in the C-terminal region of the LmjF29.1050 protein, which already possesses the Ku-N and Ku70/Ku80 domains. Besides these predictions, several other domains suggest new functions for proteins with no or only very general functions. As for P. falciparum, a strikingly high number of domains in this case were predicted in association with the ubiquitous WD40 domains. Among the most interesting predictions, we can cite, for example, the Rhomboid domain, predicted in the LmjF24.1580 protein. Rhomboid domains belong to proteins of a large family of intra-membrane serine proteases. Their conservation throughout almost all branches of life suggests involvement in key biological events with various functions: triggering of signaling events in Drosophila, association with pathogenesis in protozoan parasites, and parasite proliferation in T. gondiiRhomboid-like proteases had been described as being localized in the secretory pathway or belonging to mitochondria. Prior to this study, no Pfam Rhomboid domain have been described in L. major, whereas partial Rhomboid domains have been described in other Leishmania species. In LmjF24.1580, the presence of a mitochondrial like N-terminal targeting sequence suggests a putative mitochondrial function for this protein Rhomboid proteases seem to display different functions in distinct organisms, so it is unlikely that a single widespread function is conserved among all species. Examples of mitochondrial function associated with oxidative stress signaling have been described in yeast, or in Parkinson's disease in humans, whereas Rhomboid proteases conserved in extracellular pathogens have been associated with host cell invasion or, in the case of the extracellular ameba Entamoeba histolytica, to immune evasion As for RNA polymerase II (RNAP II) transcription system (except for SL-RNA). This is mainly illustrated by the absence of several RNAP II-related transcription factors (TF). Indeed, although several basal TFs have been identified in Leishmania species, several others seem to be missing in these species and other trypanosomatids P. falciparum. While almost all proteins necessary for the basal transcription apparatus have been identified, there appears to be a lack of specific TFs AP2 domain P. falciparum have failed. In these conditions, the discovery of DNA binding domains involved in transcriptional regulation may be of great interest in P. falciparum and L. major. We retrieved from the Pfam website a list of domains associated with GO terms related to transcription, and searched for occurrences of these domains in our predictions at 5% FDR . We discuss below the most interesting discoveries of this analysis in P. falciparum and L. major.Parasitic protists have often evolved transcriptional regulation mechanisms different from classical higher-eukaryotes models TFIID_90kDa domain known to be found in subunits of transcription factor TFIID in the protein PF3D7_1138800 , annotated “conserved Plasmodium protein, unknown function”. Currently, this very large P. falciparum protein predicted to be nuclear, has domain annotations solely upstream of position 1500 for a series of WD40 domains. The available proteomics data showing tracks in diverse extracts among which nucleus is also in agreement with the proposal that this protein could be a novel subunit of TFIID.We predicted, for example, a TFIIA_gamma_N and TFIIA_gamma_C domains on the PF3D7_0933700 protein currently annotated “conserved Plasmodium protein, unknown function” is of great interest. This little protein is currently totally devoid of domain annotation in PlasmoDB, although it has several GO annotations related to DNA-dependent transcription. Interestingly, the TFIIA_gamma subunit is characterized by a conserved structure, with 4 helices in the N-terminal domain and 12 beta barrels in the C-terminal domain. Such domains are indeed predicted for PF3D7_0933700, at the proper position, further suggesting that this protein is indeed the gamma subunit of TFIIAThe discovery of both TFIIE_alpha domain in the protein PF3D7_1145800. The general transcription factor TFIIE has an essential role in eukaryotic transcription initiation together with RNA polymerase II and other general factors. We also identified a HTH_9 domain at the beginning of the protein. This protein is currently annotated “conserved Plasmodium protein, unknown function”, but PlasmoDB reports GO annotations in agreement with our observation, in particular the GO:0005673 annotation “transcription factor TFIIE complex”. Therefore this protein likely corresponds to the TFIIE_alpha peptide, as suggested by our study.We also discovered a Auxin_resp domain (PF06507) of the very large P. falciparum protein PF14_0463, currently annotated “chloroquine resistance marker protein (CRMP)”. This domain occurs in several plant transcription factors that are responsive to the Auxin hormone, and their conserved structure includes a N-terminal DNA binding domain and a C-terminal protein-protein interaction domain PF14_0463 has a single domain, PFI12047  at positions 793-943, which is also a DNA binding domain. Interestingly, this Auxin_resp domain has so far been identified in four other Apicomplexan proteins . All of them also have a DNMT1-RFD domain upstream, highlighting structural conservation in the phylum. In addition, PF14_0463 is currently reported to be nuclear, and to interact with a large number of proteins, including several nuclear proteins , which is in accordance with transcription factor activity. Note that GeneDB currently recommends that the “chloroquine resistance marker protein” annotation should be discontinued.Another interesting prediction was the discovery of the RNA_pol_Rpb1-3 and RNA_pol_Rpb1-4, were discovered in two proteins encoded next to each other by the apicoplast genome: PFC10_API0016 and PFC10_API0017rpoC and rpoD, respectively. Interestingly, at present, domains RNA_pol_Rpb1-1 and RNA_pol_Rpb1-2 have been annotated for PFC10_API0016, upstream of our newly discovered RNA_pol_Rpb1-3 domain and a RNA_pol_Rpb1-5 domain has been annotated for PFC10_API0017, upstream of our newly discovered RNA_pol_Rpb1-4 domain. This discovery is another example where our new domains confirm and further define the structure and function of an already annotated protein. Note that the two genes encode a prokaryotic-type RNA polymerase that is known to be split into two polypeptides in Archae and chloroplasts Two domains, LmjF.28.1740 is a hypothetical protein in which we identified a novel domain called NusB. NusB is a prokaryotic transcription factor involved in the antitermination process, i.e. the phenomenon whereby RNA polymerases terminate transcription at specific sites or read through terminators, which is crucial for the regulation of gene expression Escherichia coli, it has been described to act as a dimer in Mycobacterium tuberculosisNusB in an inactive form until it is recruited for the antitermination process CarD_CdnL_TRCF has been identified in LmjF.32.2230. This gene is annotated as “ATP-dependent RNA helicase putative” and bears domains related to this helicase function. The CarD_CdnL_TRCF domain then adds a new function to the protein, putatively related to a repair mechanism during transcription. Indeed, TRCF (Transcription-Repair-Coupling Factor), for instance, is known to bind to UvrA, the DNA damage recognition protein, in order to increase strand repair during transcription A novel domain called LmjF.33.2810 gene is annotated as a “transcription elongation factor-like protein”. We were able to complement this annotation by the Med26 domain (PF08711). Med26, or TFIIS helical bundle-like domain, is present in the N-terminal part of the TFIIS protein. This protein, also called Med26 protein, is part of a large complex of 33 proteins called Mediator, largely conserved from plants to humans Mediator is able to link DNA transcription regulators (activators and repressors) to the pol II initiation machinery mainly through physical interaction with DNA specific signals and pol II subunits TFIIS seems to be a multifunctional protein acting as a transcription elongation factor involved in increasing the RNAP II transcription rate as well as a protein involved in controlling the early stages of the transcription cycle Med26 domain has also been found in LmjF.33.2820, a hypothetical protein bearing TFIIS-associated interpro non-PFAM domains. Interestingly, we also discovered a TFIIS C domain in this protein, which is a zinc finger motif that is also found in the TFIIS.The P. falciparum, our approach also allowed us to relate proteins already involved in the transcription process to novel domains associated with RNAP II transcription. RPB1 is the largest subunit of pol II, constituting, through different subunits, the DNA binding domain of pol II. We identified the novel RPB1_1 domain in LmjF.16.1350, annotated as the DNA-directed RNA polymerase I largest subunit and already bearing different RPB1 domains. Additionally, TF_Zn Ribbon is a zinc finger motif found in transcription factor IIB (TFIIB), one of the subunits involved in eukaryotes in promoter recognition and interaction with pol II. This domain has been identified in the LmjF.25.0440 protein, annotated as a putative transcription factor.As for P. falciparum and L. major, HHPRED+CODD enabled us to discover We have shown that profile/profile approaches like HHPRED can boost protein domain annotation. This is especially useful for species that have greatly diverged from the classical plant and Unikont model organisms, like most eukaryotic pathogens. Although the approach does not seem to be sufficiently accurate to be used as a standalone tool for identifying the divergent domain occurrences that have not been identified by classical sequence/profile approaches, it is much more sensitive than these latter, and actually enhances the annotations of several hundred proteins when used in combination with the co-occurrence domain discovery approach (CODD). For One issue of our approach is that it applies to multi-domain proteins only. First, it is worth noting that these proteins are thought to represent a large part (around 80%) of Eukaryotic proteins P. falciparum and L. major showed that the approach identifies key domains that were missing to date. For example this analysis revealed one of the missing enzymes involved in the first step of the shikimate pathway, an attractive drug target in P. falciparum because of its absence in mammalian cells. Importantly, several predictions reveal new domains in proteins currently devoid of any domain annotation. This is for example the case for the P. falciparum protein PFI630c, which is the gamma subunit of TFIIA according to our analysis. Our approach is fully automatic and can be applied on any genome. Hence, it could be of great help for annotating all genomes that are phylogenetically distant from classical model organisms, and we intend to apply it to all other pathogens in EuPathDomains.All predictions along with the GO annotations that can be deduced have been integrated in the EuPathDomains database, a protein domain database dedicated to eukaryotic pathogens. Close analysis of some of the predictions involving Pfam domain families that were unknown in We used HHPRED from the HH-suite 2.0 in our experiments. First, each query protein sequence was used to build a multiple sequence alignment (MSA). This was done using two approaches, using either only the homologous proteins in close species, or every sequenced homologue, via the HHblits method L. major, six species were included: four Leishmania species  and two Trypanosoma species (Trypanosoma cruzi and Trypanosoma brucei) (http://tritrypdb.org/tritrypdb/). For P. falciparum, six species were analyzed: P. falciparum, P. vivax, P. yoelii, P.berghei, P. chabaudi and P. knowlesi. For each L. major and P. falciparum protein, we extracted its homologs in the set of selected closest species from the OrthoMCL database L. major and P. falciparum proteins have at least one homologue in the selected species, respectively. The majority of L. major proteins , these paralogs were also considered. Each query protein sequence was aligned against its homologs using Muscle For HHblits proceeds in a Psi-blast-like manner by iteratively aligning additional homologous sequences on the query protein. HHblits was run with default parameter values—3 iterations, local alignment mode, and hhmake procedure of HHPRED. hhmake was run with default parameters, except for the maximum sequence identity parameter that we set at Leishmania proteins. Each HMM was then compared with all HMMs of the Pfam database. We considered, for the following experiments, hits with e-values ranging from 0.1 to 10. As explained in section Results, the experiments were done using local and global alignment modes, using Pfam 26 and Pfam 23 HMMs, respectively. From each alignment of a protein-HMM and a domain-HMM, the position of the potential domain on the query sequence was deduced. Each potential domain overlapping an already known domain of the protein  was discarded. Similarly, when two potential domains overlapped on the protein sequence, the one with the greatest e-value (i.e. the least likely) was removed.All generated MSAs were then transformed into an HMM profile using the i.e. the probability i.e. that are observed in the same proteins a significantly higher number of times than expected at random. This is achieved with the Fisher's exact test to cope with potentially small sample sizes. A p-value is computed for each domain pair, and pairs below a given threshold are stored in a set CDP). Next, from the target-species proteins that possess both known and potential domains, we build a list of  domain pairs Let Let Thus, we have Moreover, we used a bootstrap procedure i.e. a pair of the CDP set). The domains selected this way are said to be certified. The certification can be done on the basis of the already known Pfam domains of the protein, but also on the basis of the other known InterPro (non Pfam) domains, or even on the basis of the other potential Pfam domains of the protein.CODD is a computational approach which enables us to select the most likely occurrences among a set of potential domain occurrences , while controlling the false discovery rates associated with the predictions CODD provides an estimate of the FDR associated with the certified domains This approach is similar to that proposed in Figure S1Sensitivity and accuracy of HHPRED+CODD and HMMER+CODD using the known Interpro domain occurrences for certifications. This figure reports the number of new domains (x-axis) certified by HHPRED+CODD  and HMMER+CODD (blue) using local (left) and global (right) alignments for various FDR thresholds (y-axis).(PDF)Click here for additional data file.Figure S2Sensitivity and accuracy of HHPRED+CODD and HMMER+CODD using the potential domain occurrences for certifications. This figure reports the number of new domains (x-axis) certified by HHPRED+CODD  and HMMER+CODD (blue) using local (left) and global (right) alignments for various FDR thresholds (y-axis).(PDF)Click here for additional data file.Table S1List of considered associations between domains and GO terms.(XLS)Click here for additional data file.Table S2List of the 36 P. falciparum domain predictions that were manually analysed.(XLS)Click here for additional data file.Table S3List of the 37 L. major domain predictions that were manually analysed.(XLS)Click here for additional data file.Table S4List of all predicted domains in P. falciparum.(XLS)Click here for additional data file.Table S5List of all predicted domains in L. major.(XLS)Click here for additional data file.


Streptococcus pneumoniae. It kills cells by forming pores assembled from oligomeric rings in cholesterol-containing membranes. Cryo-EM has revealed the structures of the membrane-surface bound pre-pore and inserted-pore oligomers, however the molecular contacts that mediate these oligomers are unknown because high-resolution information is not available. Here we have determined the crystal structure of full-length pneumolysin at 1.98 Å resolution. In the structure, crystal contacts demonstrate the likely interactions that enable polymerisation on the cell membrane and the molecular packing of the pre-pore complex. The hemolytic activity is abrogated in mutants that disrupt these intermolecular contacts, highlighting their importance during pore formation. An additional crystal structure of the membrane-binding domain alone suggests that changes in the conformation of a tryptophan rich-loop at the base of the toxin promote monomer-monomer interactions upon membrane binding by creating new contacts. Notably, residues at the interface are conserved in other members of the CDC family, suggesting a common mechanism for pore and pre-pore assembly.Pneumolysin is a cholesterol-dependent cytolysin (CDC) and virulence factor of  Streptococcus pneumoniae (pneumococcus)458911137The cholesterol-dependent cytolysin (CDC), pneumolysinAlthough high-resolution X-ray structures have been determined for several CDCs, pneumolysin has proved to be elusive. Consequently, structure-function analysis has relied on models based on the structures of the other CDC toxins. Critically, the lack of high-resolution data means that the interactions enabling pneumolysin monomers to pack together to form the pore and pre-pore complexes is not known. In this work, we have determined the structure of pneumolysin at 1.98 Å resolution. The side-by-side packing arrangement in the crystal demonstrates the packing of monomers in the pre-pore complex. Additional structural and mutagenesis data has identified residues that are likely to contribute towards oligomerisation during pre-pore formation.E. coli and purified by affinity and gel filtration chromatography. Crystals of the full-length toxin were grown at 4 °C and at pH 8.5. The best crystals were obtained from protein containing substitutions Asp385Asn and Cys432Ala. Neither mutation prevents pore formation16Full-length pneumolysin and a truncated form comprising the membrane-binding domain (domain 4) were produced by expression in The tryptophan-rich loop, projects from the base of domain 4 in the structure of full-length pneumolysin, reflecting the likely membrane-binding conformation . NotablyIn the structure of full-length pneumolysin, domain 4 is offset by ~30° relative to the plane of the long axis of domains 1–3, such that the toxin resembles a bend rod from the side . The rel2 and 962.8 Å2, respectively. Although most of the residues at the interface are polar, there are relatively few polar intermolecular interactions: salt bridges between Asp8 and Arg226 and Glu434 and Arg399 and hydrogen bonds between the side-chain of Asn339 and the carbonyl group of Pro87, and between the hydroxyl group of Tyr461 and the amine and carbonyl groups of His407. Thus, the major contribution towards oligomerization of monomers on the membrane is likely to be surface complementarity, leading to exclusion of water. Notably, of the 85 residues that are buried, 41 are identical and 63 are conserved in at least three of the other CDCs for which structures are available, suggesting that the interface is likely to be relatively well conserved in other CDCs  at the interface. Leu11Arg, Ser68Glu, Asn86Arg, Thr88Glu, Arg147Ala, Asp205Arg Arg226Ala Thr304Arg, Asp338Ala, Ser68Glu, Asn86Arg, Arg147Glu, Asp338Arg were designed to disrupt the interface at the top of toxin (domains 1–3) and Arg437Ala to disrupt the domain 4/domain 4 interface. Although mostly polar in nature, these residues do not form intermolecular polar contacts, but rather exclude water at the interface Three double mutants were also created with mutations in domain 4: Arg339Ala + Glu434Ala; Glu434Ala + Tyr461Ala; and Glu434Ala + Arg437Ala. Importantly, with the exception of Arg147, which lies on the domains 1/3 boundary and Thr304 within domain 3, mutagenesis was restricted to residues in domains 1 and 4 that undergo relatively little positional changes upon pore formation. Regions undergoing large conformational changes, including residues 155–186 and 253–285 that form the membrane-spanning β-hairpins and domain 2, which rotates to allow the hairpins to penetrate the membrane, were excluded to ensure that the mutations did not prevent pore formation itself. All mutants were produced and purified as for wild-type pneumolysin. As with wild-type protein they eluted from a gel-filtration column as single peaks, corresponding to monomers, and circular dichroism and fluorescence spectroscopy  confirmeAlmost all the mutations reduced the ability of pneumolysin to lyse sheep red blood cells, but by different degrees . The mosMutations within domain 4 also reduced the haemolytic activity of pneumolysin. Replacement of Tyr461 with an alanine residue lead to a five-fold decrease in activity, whereas the Tyr461Phe mutation had little effect, suggesting that exclusion of water at the monomer interface is more important than the hydrogen bonds to His407. Disruption of the small polar network involving Glu434 and Arg437 of one monomer and Gln402 and R399 of the adjacent monomer  reduced the hemolytic activity by 6 to 10-fold. In the crystal structure, Glu434 not only forms a salt bridge with Arg399 but also interacts with Arg437 that in turn forms part of the binding interface by packing against the adjacent monomer. Interestingly, these interactions are only possible when the tryptophan-rich loop is flipped outwards in the putative membrane-binding conformation. When the loop is folded back, as in the domain 4 structure or in the structure of perfringolysin O , Glu434 em, max from 347 nm to 354 nm, consistent with buried tryptophan residues becoming exposed to the polar solvent. Plotting the λem, max against the concentration of guanidine-HCl gave a simple two-state transition in which the midpoint was ~1.4 M guanidine-HCl  in the fluorescence intensity that was accompanied by an decrease in the λo 342 nm , presumaIt has been shown that pneumolysin oligomerises spontaneously in solution but only at high protein concentrations, revealing weak interactions between monomers, even in the absence of a cholesterol-containing lipid bilayer21Monomers are parallel in the crystal structure but must be slightly offset on the cell membrane to create the ring-shaped pre-pore and pore oligomers. Furthermore, pores vary in size, typically with between 30–50 subunits, so there must be some tolerance in the intermolecular packing (ranging from an offset of 12° in a 30mer to 7.2° in a 50mer). Notably, most of the packing interactions in the crystal are within the central portion of the binding interface  and are therefore likely to allow some leeway in the angle between monomers.Most of the contacts between pneumolysin monomers are between residues in domains 1 and 4, at the top and bottom of the toxin, respectively. These domains are believed to change conformation the least during pore formation, with domain 4 serving as a fixed membrane anchor throughout and domain 1 acting as a bridge between domain 2, which rotates as the pre-pore collapses down to form the pore, and domain 3, which rearranges to form the β-hairpins that penetrate the membraneRecently it has emerged that pneumolysin and several other CDC are lectins that probably have dual receptors on host cells involving a carbohydrate ligand as well as cholesterolS. pneumoniae serotypes. Disruption of pneumolysin oligomerisation is an attractive potential strategy for the future design of such inhibitors and the structure described here forms the basis for rational approaches.Pneumolysin is a target for inhibitors for the treatment of pneumococcal disease because of its importance for pneumococcal pathogenicity and its conservation in the different 6 tag. Freshly transformed E. coli BL21 (DE3) were grown to an OD600 of 0.6–0.8, induced with 0.1 mM IPTG and incubated at 18 °C, with shaking at 220 rpm overnight. Cells were harvested by centrifugation at 3,500 g for 15 minutes at 4 °C and resuspended in lysis buffer  with a protease inhibitor tablet (Roche). Cells were lysed by sonication and cell debris was removed by centrifugation. The supernatant was then loaded onto an nickel-Sepharose column , pre-equilibrated with lysis buffer. After loading, the column was washed with 50 ml lysis buffer without Tween 20 and pneumolysin was eluted using a linear gradient of imidazole between 0 and 1 M. Pneumolysin was further purified by gel filtration using a Superdex 200 16/60 column in 20 mM Tris-HCl at pH 7.5. Domain 4 was expressed as a maltose-binding protein fusion and purified by affinity chromatography on a amylose-Sepharose column . Domain 4 was released by overnight digestion with TEV protease and separated from maltose-binding protein by gel-filtration on a Superdex 200 16/60 column. Mutations were introduced into pneumolysin by PCR and proteins were expressed and purified as for the wild-type toxin.The gene encoding pneumolysin from serotype D39 was amplified by PCR and cloned into the polylinker of a modified pET-based expression vector. Protein was synthesised with an N-terminal His2, 30 mM MgCl2, 20% v/v glycerol, 14% w/v PEG 4K, 6 mM phosphocholine chloride at 4 °C. Domain 4 was crystallised in 30% w/v PEG 2000 MME containing 100 mM potassium thiocyanate at 20 °C. All crystals were stored in liquid nitrogen and were maintained at 100 K during data collection. Diffraction data were collected at Diamond Light Source and were processed with MosflmPneumolysin was crystallised using the sitting-drop vapor diffusion method by mixing equal volumes of pneumolysin (10 mg/mL) and 100 mM Tris-Bicine pH 8.5, containing 30 mM CaClSheep red blood cells  were washed by pelleting 10 ml defibrinated sheep blood at 1734 g, at 4 °C and resuspending the cell pellet in chilled phosphate-buffered saline. Two-fold serial dilutions of pneumolysin in phosphate-buffered saline was aliquoted into a round-bottomed 96-well microtitre plate, and mixed with an equal volume of 1% v/v sheep blood. The plates were incubated for 30 minutes at room temperature, and intact red blood cells and cellular debris were pelleted by centrifugation at 1734 g, at 4 °C. The supernatant was transferred to corresponding wells in a flat-bottomed 96-well microtitre plate and the absorbance of each well was measured at 410 nm. Inhibition assays were carried out in a similar way except that dilutions of cholesterol were added to a fixed amount of pneumolysin (0.626 μM). This concentration of pneumolysin was sufficient to lyse the erythrocytes even for the mutants with reduced haemolytic activity.Fluorescence data were collected in a Fluoromax-4 (Horiba Jobin Yvon) instrument at a final protein concentration of 1 μM pneumolysin, using a low-volume quartz fluorescence cuvette (300 μl). Proteins were excited at 280 nm with a 2.5 nm slit width and fluorescence was detected between 300 and 400 nm at 1 nm intervals with a 2.5 nm slit width. All spectra were collected at 20 °C. Samples were allowed to equilibrate for 150 seconds before spectra were collected and buffer blanks were subtracted from all datasets.Liposomes were generated by addition of L-α-phosphatidylcholine  to cholesterol  and dihexadecyl phosphate  to 5 ml of a 1:1 methanol/chloroform mix in a glass volumetric flask (5 ml). The mixture was solubilized by agitation and the liquid removed under a dry stream of nitrogen on ice. The nitrogen was stopped once all visible liquid had evaporated and the lipids were a translucent yellow gel sticking to the sides of the flask. The lipids were suspended in 5 ml of PBS by vortexing and then sonicating at room temperature, for 90 seconds.How to cite this article: Marshall, J. E. et al. The Crystal Structure of Pneumolysin at 2.0 Å Resolution Reveals the Molecular Packing of the Pre-pore Complex. Sci. Rep.5, 13293; doi: 10.1038/srep13293 (2015).