dataesr/scientific-paragraphs-categorization huggingface dataset:
Data were analysed by global fitting to a 1:1 Langmuir binding model of both the association and dissociation phases for at least five concentrations simultaneously using the BIAevaluation 3. 2 software (GE Healthcare). The apparent equilibrium dissociation constants (K D ) were calculated from the ratio of the dissociation and association rate constants (k d /k a ). Although the interaction of the ecotin dimer with proteases is likely more complex than a simple 1:1 binding model, data fitting using this model yielded satisfactory chi2 values (,4) and was used for comparison purposes.
Crystallization, Structure Determination, and Refinement The ecotin/MASP-3 SP complex was concentrated to about 7 mg/ml in a buffer containing 50 mM triethanolamine-HCl pH 7. 4, 145 mM NaCl and 100 mM sulfobetain NDSB195. Reproducible crystals were obtained by the vapour diffusion method at 20uC using a reservoir solution containing 18-22% (w/ w) PEG2KMME, 0. 2 M ammonium sulfate, 0. 1 M sodium acetate pH 4. 7. PEG 400 (3% w/v) was also often added to improve crystal quality. Very thin plate-like crystals grew in two weeks. Several datasets were collected on the ESRF beamlines ID14-eh1, ID14-eh2, ID29 and BM14. These were integrated and merged using XDS  [36]. The crystals belong to the P2 1 2 1 2 space group, with cell dimensions a = 66. 7 A ˚, b = 164. 6 A ˚, c = 90. 6 A ˚. Their diffraction limit is about 3.
2 A ˚, with a high mean Wilson B factor of about 60 A ˚2. Their solvent content is about 54%, with one tetramer per asymmetric unit. The structure was solved by molecular replacement using Phaser  [37] , defining the two positions of the SP domain and inhibitor search models. The ecotin search model was a mutant version extracted from the Protein Data Bank (PDB) entry 1XXF describing its complex with the factor XIa catalytic domain  [38]. For the SP domain, a truncated version of the MASP-2 SP domain was used  [25] , in which the tips of the more variable loops (463-467, 484-495, 504-510, 526-529, 556-567, 577-581, 604-611, 685-686) were removed. A clear unique solution was obtained. Moreover, several residue substitutions from the models were visible in the initial electron density maps. Numerous runs of iterative model building and refinement were performed, using several graphics and refinement softwares (O  [39] , Coot  [40] , CNS  [41] , BUSTER  [42] , Refmac  [43]  to check and improve the accuracy of the model.
Bulk solvent correction and Translation Libration Screwmotion (TLS) refinement were used, each chain defining one TLS group. Non-crystallographic symmetry (NCS) restraints were included in the refinement, carefully excluding only the flexible zones for which the two copies display significant different electron density because the molecules are in a slightly distinct environment. An illustration of the quality of the final electron density map together with the corresponding model is provided (Fig. S1 ). Missing parts in the current model include residues 1-5 and 89 in ecotin, together with the following MASP-3 segments: 456-458, 508-511, 578-593 and 705-709. The coordinates and structure factors of the ecotin/MASP-3 SP complex are accessible (PDB code 4IW4).
Comparative Analysis of Protease/ecotin Binding The fact that the low amidolytic activity of MASP-3 SP domain was significantly inhibited by ecotin prompted us to further investigate its interaction with this inhibitor and compare it with other serine proteases, since ecotin is known as a pan-serine protease inhibitor. Surface plasmon resonance spectroscopy was used to analyze the interaction of different proteases with ecotin. As shown in Fig. 3 , the SP domain of MASP-3 readily bound to immobilized ecotin. Kinetic analysis of the binding data at different concentrations (0. 22-4. 48 mM) yielded association and dissociation rate constants of 1. 34610 3 M 21. s 21 and 8. 06610 24 s 21 , respectively, and a resulting apparent equilibrium dissociation constant (K D ) of 601 nM (Table  3 ). These ecotin binding properties were compared to those of the catalytic domains of MASP-1, MASP-2, C1r, and C1s, as well as of trypsin and factor XI.
Three peaks were obtained by gel filtration when using equimolar amounts of protease and ecotin, as shown in Fig. 4A. The major peak 1 contained equal amounts of enzyme and inhibitor, as judged by N-terminal sequencing and SDS-PAGE analysis (Fig. 4B ), and corresponded to the tetrameric complex submitted to crystallization. The intensity of the second peak increased when the inhibitor was in excess and was identified as a trimeric complex between the ecotin dimer and the protease, as previously observed for rat trypsin  [53]. The third peak corresponded to the uncomplexed protease and the ecotin dimer (molecular mass 32 kDa) and its intensity increased when the protease was in excess. Crystallization of the ecotin/MASP-3 SP domain tetramer was successful and reproducible. Four coherent datasets were merged to yield a more complete and redundant dataset which was used to solve the structure and refine it to 3.
The tetramer is almost perfectly symmetrical, except for slight differences at the edges of the interfaces and for some local differences in the crystal contacts of the two copies of each protein. Compared to other ecotin/protease complex structures, the most similar tetramer is the one formed by the D102N rat anionic trypsin and Y69F/D70P ecotin (  [54] , PDB code 1EZU). The  conformations observed at the primary and secondary interfaces are strikingly conserved in both cases (Fig. 5C, D, E ). The global r. m. s. d value between these two tetrameric structures is indeed only 0. 95 A ˚(for 678 aligned residues), and 0. 83 A ˚for the SP domain alone (for 202 aligned residues, with 39. 6% sequence identity). In contrast, the MASP-3 480-490 loop features a large insertion compared to trypsin (Fig.
Unit cell lengths (A ˚l) a = 66. 7, b = 164. 6, c = 90. favoured region d 670 (91. 9%) Residues in Ramachandran allowed region d 39 (5. 3%) Residues in Ramachandran outlier region d 20 (2. 7%) a Statistics on a merged dataset resulting from 4 crystals collected at ID14-eh2, ID29, ID14-eh1, BM14, ESRF, Grenoble. b Statistics for the high-resolution bin (3. 25-3. 20 A ˚) are in parentheses. c Statistics for the high-resolution bin (3. 28-3. 20 A ˚) are in parentheses. d Including prolines and glycines -Statistics provided by RAMPAGE [65]. doi:10. 1371/journal. pone. 0067962. t004.
Acknowledgments We thank  Jean-Pierre Andrieu ,  Izabel Be  ´rard,  Delphine Blot  and  Isabelle Bally  from the  IBS platforms of the Partnership for Structural Biology in Grenoble  for assistance and access to the protein sequencing, mass spectrometry, crystallization and BIAcore facilities, respectively. Access to the  ESRF  beamlines  ID14-eh1 ,  ID14-eh2 ,  ID29  and  BM14  is greatly acknowledged. We thank  Sandor  for construction of the pNT-Bac vector containing the MASP-3 ap-SP segment,  Ludovic Lenclume  for production of PAR1 and  Evelyne Gout  for baculovirus amplification and insect cells infection.
This work was supported by the  Commissariat al'Energie Atomique , the  Centre National de la Recherche Scientifique , the  UniversiteJoseph Fourier (Grenoble, France)  and partly by a grant from the  French National Research Agency  ( ANR-09-PIRI-0021 ). RKG was supported by a post-doctoral scholarship of the  Embassy of France in India. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
6 Resolution 6 Unit cell lengths (A ˚l) a = 66. 7, b = 164. 6, c = 90. favoured region d 670 (91. 9%) Residues in Ramachandran allowed region d 39 (5. 3%) Residues in Ramachandran outlier region d 20 (2. 7%) a Statistics on a merged dataset resulting from 4 crystals collected at ID14-eh2, ID29, ID14-eh1, BM14, ESRF, Grenoble. b Statistics for the high-resolution bin (3. 25-3. 20 A ˚) are in parentheses. c Statistics for the high-resolution bin (3. 28-3. 20 A ˚) are in parentheses. d Including prolines and glycines -Statistics provided by RAMPAGE [65]. doi:10. 1371/journal. pone. 0067962. t004.
EXPERIMENTAL PROCEDURES Materials-Pyrococcus abyssi asparagine synthetase A was a generous gift from D. Kern. Radioactive L-[ 14 C]tyrosine (483 mCi/mmol) was from Amersham Biosciences (Velizy-Villacoublay, France) and L-[ 14 C]aspartate (200 mCi/mmol) was from PerkinElmer Life Sciences. Database Screening for AsnRS Sequences-The P. falciparum genome encodes two copies of AsnRS, a cytoplasmic version (PlasmoDB ID PF3D7_0211800) and an apicoplastic one (Plas-moDB ID PF3D7_0509600)  (14). The cytoplasmic P. falciparum AsnRS gene was identified by blasting the sequence of yeast cytoplasmic AsnRS (NP_011883. 1) against the PlasmoDB database. Sequence alignments were computed with Tcoffee software.
RNA Seq Data of aaRS mRNA Expression in Sexual and Asexual Stages- The study was performed in the laboratory of Xinzhuan Su  (18) , and data were retrieved from PlasmoDB for each P. falciparum cytosolic aminoacyl-tRNA synthetase gene. Proteomic Data of P. falciparum Life Cycle Stages-Data were retrieved from Florens et al. (19). We considered proteins (i) expressed specifically in a single developmental stage and (ii) with sequences covered by at least three peptides. Thus, we used 27, 18, 31, and 66 protein sequences, corresponding to 50,027, 9629, 24,152, and 55,394 amino acids, identified in the sporozoite, merozoite, trophozoite, and gametocyte stages, respectively. Cloning and Expression of Recombinant P. falciparum and H. sapiens AsnRSs-Genes coding for both the P. falciparum and human AsnRSs were amplifed by PCR from either P.
falciparum and H. sapiens AsnRS samples (20 M) were incubated in HEPES-KOH, pH 7. 0, 50 mM NaCl, 10% glycerol and were analyzed with a Zetasizer Nano S (Malvern, Orsay, France). Five intensity measurements were recorded at 20 °C, and the data were processed with the manufacturer's software, assuming that the enzyme particles were spherical. This method measures distributions of particle diffusion coefficients (D) that were transformed via the Einstein equation (D ϭ kT/6p 0 R h ) into hydrodynamic radii (R h ) and thus apparent particle sizes. Corrections for solvent refractive index and viscosity were applied, and the contribution of the solvent components was subtracted. Preparation of L-[ 14 C]Asparagine-This procedure was adapted from Roy and collaborators  (21). The reaction mixture (200 l), containing 50 mM HEPES-NaOH, pH 7.
Apparent kinetic parameters were determined from Lineweaver-Burk plots. Data were expressed as averages of at least three independent experiments. Aminoacylation plateaus of Plasmodium total RNA were performed in the presence of 0. 5 M of the relevant aminoacyl-tRNA synthetases (aaRS; P. falciparum recombinant AspRS, TyrRS, and AsnRS). Values were measured after 60-min incubations at 37 °C.
Expression of Asparaginylation Molecular Partners and Comparison with Other Aminoacylation Systems in P. falciparum tRNA Concentrations-We investigated the expression levels of tRNA Asn , tRNA Tyr , tRNA Asp , and tRNA Lys in non-synchronized in vitro cultures of P. falciparum. Transfer RNA Tyr and tRNA Asp are unique isoacceptors, which are each encoded by a single tRNA gene similar to tRNA Asn , but they decode fewer codons (4. 4 and 6. 4%, respectively) than tRNA Asn (11. 2%) (Codon Usage Database). On the contrary, frequencies of asparagine and lysine codons are comparable (11. 2 and 10. 4%, respectively), but tRNA Lys is encoded by two tRNA genes (tRNA Lys  AAA and tRNA Lys AAG ). Northern blots and aminoacylation detection showed that two of the four selected tRNAs, tRNA Asn and tRNA Tyr , are globally expressed at the same level, independent of their use in translation (Fig.
Amino Acid Availability-Based on genome analysis, Plasmodium possesses biosynthetic pathways for Asn, Glu, Asp, Gly, Pro, and Gln  (36). However, its growth depends on a supply of a complete set of exogenous amino acids. Thus, during the blood stage, Plasmodium development relies mostly on hemo-  A, cloverleaf structure of tRNA Asn transcripts: the motifs involved in tRNA folding are present in both the plasmodial (green) and the human (blue) tRNA Asn sequences. The few differences are spread across their sequences and do not involve residues strategic to the structure and are presumed to be harmless for folding and aminoacylation. B, sequence alignments of human and plasmodial tRNA Asn sequences: the human genome codes for 35 tRNA Asn genes partitioned into two isoaccepting families either with an AUU anticodon (two genes coding for a unique isodecoder tRNA sequence) or a GUU anticodon (GtRNAdb, Genomic tRNA Database).
Asparagine Content of P. falciparum Stage-specifically Expressed Proteins Data from stage-specific proteomes were retrieved from Ref. 19. They relate to four distinct stages of the parasite: sporozoites (the infectious form injected by the mosquito), merozoites (the invasive stage of the erythrocytes), trophozoites (the form multiplying in erythrocytes), and gametocytes (the sexual stage). For each stage, amino acid contents and amino acid repeats were determined. Global proteome asparagine content is not strictly conserved among the different stages; for example, there is 1. 8-fold more asparagine in sporozoite proteins than in trophozoites proteins (Fig. 5A ). This observation is strengthened when looking at the frequency of asparagine repeats (Fig. 5B ): asparagine repeats are more abundant in sporozoites (2.
Amino acids concentrations in human blood are derived from Ref. 57. C, comparison of tRNA availability in H. sapiens (gray) and P. falciparum (black). Bars (arbitrary units) represent the ratio between the number of tRNA gene copies encoded by each genome (tRNA isoacceptor genes were combined, GtRNAdb, Genomic tRNA Database) and the corresponding amino acid frequency (Codon Usage Database). Lower bars correspond to the rarest tRNAs. Note that scales on the y axes are different for H. sapiens (left) and P. falciparum (right). L, liter.
Molecular dynamics simulations The crystal structure of the elongation factor Tu in complex with the ribosome was taken from the Protein Data Bank, entries 2XQD and 2XQE  (Voorhees et al. 2010). Protonation states of histidines were assigned by visual inspection. The simulations included protein residues within a 24 Å sphere, centered on the GTP binding site. In addition to crystal waters, a 26 Å sphere of water was overlaid and waters that overlapped ribosome, crystal waters, the Mg ion, or GTP were removed. Two additional water molecules, which coordinate the Mg ion in the apo EF-Tu complex were placed by superimposing the GTP molecules of these two structures. Throughout the molecular dynamics (MD) simulations, protein atoms between 20 and 26 Å from the sphere's center were harmonically restrained to their experimental positions.
Simulations were done with the SSBP solvent model  (Beglov and Roux 1994; Simonson 2000 ), which treats the region outside the 26 Å sphere as a uniform dielectric continuum with a dielectric constant of 80. Newtonian dynamics was used for the innermost region, within 20 Å of the sphere's center, and Langevin dynamics for the outer part of the sphere, with a temperature bath at 292 K. The CHARMM27 force field was used for the protein and RNA  (Mackerell et al. 1998; Foloppe and MacKerell 2000)  and the TIP3P model for water  (Jorgensen et al. 1983). Electrostatic interactions were computed without any cutoff, using a multipole approximation for distant groups  (Stote et al. 1991). Calculations were done with the CHARMM program  (Brooks et al. 2009). The mutant His85Gln protein was set up in a similar way to the wild-type, except that the glutamine residue had to be positioned in place of the histidine.
This was done by superimposing the GTP ligands of the EF-TU:Ribosome and RasGap systems (PDB entry 1WQ1)  (Scheffzek et al. 1997 ) and extracting the appropriate glutamine residue, Gln61. MD simulations for the resulting system were then run for 1 nsec. The position of Gln85 remained stable throughout with hydrogen bonds between its amide group and the γ-phosphate of the GTP ligand and the phosphate of the ribosomal residue A2662, and between its amide oxygen and the catalytic water molecule.
2010). All geometry optimizations and reaction path calculations were performed with the DFT-QC/MM potential. To include the system beyond the explicit 24 Å sphere, we used our recent QC/MM implementation of the stochastic solvent boundary potential  (Aleksandrov and Field 2011) , which treats the region outside the explicit sphere as dielectric continuum, and includes its effect in the self-consistent field procedure (SCF). The starting coordinates of the complexes were taken after 200 psec of MD simulation on the systems described in the Materials and Methods. The QC(DFT)/MM calculations were performed with the pDynamo software  (Field 2008) , whereas the QC(MP2)/ MM computations were carried out with pDynamo and its interface to the ORCA program  (Neese 2008). No truncation or cut-off was used to calculate nonbonding interactions.
Microeukaryotes have vital roles for the functioning of marine ecosystems, but still some general characteristics of their current diversity and phylogeny remain unclear. Here we investigated both aspects in major oceanic microeukaryote lineages using 18S rDNA (V4-V5 hypervariable regions) sequences from public databases that derive from various marine environmental surveys. A very carefully and manually curated dataset of 8291 Sanger sequences was generated and subsequently split into 65 taxonomic groups (roughly to Class level based on KeyDNATools) prior to downstream analyses. First, we calculated genetic distances and clustered sequences into Operational Taxonomic Units (OTUs) using different distance cut-off levels. We found that most taxonomic groups had a maximum pairwise genetic distance of 0.
Introduction Decoding the complexity of marine microeukaryotic diversity is one of the biggest challenges of modern microbial ecology, given the astonishingly large diversity detected in molecular surveys  [1] [2] [3] [4] [5] [6]. Thousands of high-quality environmental Sanger sequences derived from clone libraries of the 18S rDNA genes are now available in public databases, and represent an important resource to investigate some aspects of the general architecture of protist diversity that still remain unclear. Pair-wise distances among environmental sequences are generally used to cluster them into Operational Taxonomic Units (OTUs) at different distance levels. The number of OTUs at each clustering threshold, defined here as ''clustering pattern'', is a useful proxy of the diversity magnitude and it can also be used to characterize intra group distances.
Clustering patterns have already been described for whole protist communities  [7] [8] [9] [10] , but it is expected that the analysis of singular groups can highlight interesting diversity differences among lineages. These features are better reflected in the shape of phylogenetic trees from where we can infer the ''phylogenetic structure'' of a group, that is, the specific diversification patterns drawn by the branches (number, length and relative positions) of a phylogenetic tree  [11]. Very little has been done to investigate these structures in specific groups of marine microbial eukaryotes. The clustering pattern, based on pair-wise genetic distances, has the advantage of being easily comparable among datasets and strongly related to sequence similarity. Indeed, OTU counts provide an estimate of present diversity in each taxonomic group.
Significant ribogroups are the MALV within Alveolata  [17] , the MAST within Stramenopiles  [18] , and the RAD within Rhizaria  [9]. Here we used publicly available 18S rDNA Sanger sequences obtained from molecular surveys aimed to study the diversity of marine planktonic protists by a culture-independent approach. We classified these sequences into separate taxonomic groups, combining classical taxonomy (Class level) with ribogrouping, and analyzed the genetic diversity in each group by OTU clustering and phylogeny. Our main objective was to get an improved representation of marine protist diversity. This will serve as a frame for interpretation and comparison with data obtained by High Throughput Sequencing (HTS) technologies like 454 or Illumina  [19]. HTS sequences (that is, reads) need to be validated against data retrieved independently; otherwise they can produce strongly biased views of diversity  [20, 21].
Results In this study we carried out an analysis of very carefully curated 18S rDNA environmental sequences derived from marine surveys both from oxic and anoxic water samples (see Table  S1 ). A first filtering step retained 13,270 sequences of marine planktonic protists obtained from clone libraries done with universaleukaryotic primers (Fig. S1 ). These were classified into 65 taxonomic groups and only sequences containing the V4-V5 regions were kept (8291 sequences; Fig. S2 ). Some of these groups were well-defined classical taxa (mostly at the class level) whereas the rest were ribogroups deriving exclusively from molecular environmental surveys (Table  1  and Table  S2 ). Alveolata sequences constituted more than half of the dataset, being MALV-II (with 1815 sequences), Dinophyceae, MALV-I and Ciliophora the most represented.
Stramenopiles were second in the number of sequences and included more taxonomic groups than Alveolata (21 versus 10). The largest groups within Stramenopiles were Bacillariophyceae, Chrysophyceae, MAST-3 and MAST-1. Rhizaria were represented by 682 sequences, distributed among several cercozoan and radiolarian groups. The recently proposed CCTH supergroup (Cryptophyta, Centroheliozoa, Telonemia, Haptophyta, Burki et al. [22] ), was present in the dataset with 522 sequences, mainly from Prymnesiophyceae and Cryptophyceae. The remaining groups contained less than 90 sequences, with the exceptions of Choanoflagellatea and Prasinophyceae. Finally, 427 sequences remained unidentified (could not be assigned to even a supergroup), and were labeled as Novel.
Justifying the target 18S rDNA region The rationale of choosing the V4-V5 region (,550 bp) for most analyses was to maximize the number of sequences with shared positions, since many clone libraries targeted this region. We investigated how well this partial region represented the variability of the complete 18S rDNA gene. This test also included the V9 region (,160 bp). For the three separate datasets (Stramenopiles, Alveolata and Rhizaria) we plotted the pair-wise distances calculated with the two partial regions (V4-V5 and V9) with respect to the distances computed using the full-length gene (Fig. 1 ). The V4-V5 region gave better results, with higher correlation coefficients (R) in the three cases (0. 84 to 0. 97) as compared with the values derived from the V9 region (0. 47 to 0. 80).
3A ) recovered the monophyly of all groups, except Cryptophyceae. The Rhizaria tree (Fig. 3B ) showed the grouping of Chlorarachniophyta and Monadofilosa (from the phylum Cercozoa), while Radiolaria was not well defined as described in previous phylogenies  [23] : the class Polycystinea did not appear monophyletic and was separated into the respective orders except Collodaria and Nassellaria that were grouped (as Nassellaria*). These trees confirmed that the final dataset did not contain misclassified sequences. A nexus file of the trees is available as supporting material (Nexus file S1).