dataesr/scientific-paragraphs-categorization huggingface dataset:
Both peptides have a 310 helix involving the Pro7-Ala8-Cys10 sequence (CIA numbering). The ensembles of CIA and CnIA (PDB code 1B45) superimpose with an RMSD of 1. 26 Å (calculated using MOLMOL). Similarly, CIB is structurally very similar to MII, where both peptides have a central α-helical region comprising residues 6-11 in CIB and residues 7-11 in MII. The ensembles of CIB and MII (PDB code 1MII) superimpose with an RMSD of 0. 55 Å (calculated using MOLMOL). The conformational heterogeneity observed for CIA is common to most α-3/5 conotoxins. Indeed, Favreau et al. reported similar conformational heterogeneity in solution for α-3/5 conotoxin.
Both peptides have a 3 10 helix involving the Pro7-Ala8-Cys10 sequence (CIA numbering). The ensembles of CIA and CnIA (PDB code 1B45) superimpose with an RMSD of 1. 26 Å (calculated using MOLMOL). Similarly, CIB is structurally very similar to MII, where both peptides have a central α-helical region comprising residues 6-11 in CIB and residues 7-11 in MII. The ensembles of CIB and MII (PDB code 1MII) superimpose with an RMSD of 0. 55 Å (calculated using MOLMOL). The conformational heterogeneity observed for CIA is common to most α-3/5 conotoxins. Indeed, Favreau et al. reported similar conformational heterogeneity in solution for α-3/5 conotoxin CnIA, but this also holds true for α-3/5 GI and α-3/5 MI  [26, 35, 36]. This heterogeneity could be due to cis to trans isomerization of a peptidic bond, but at this stage there is no data to support this hypothesis  [26].
Mass Spectrometry Solvents used for LC/MS were of HPLC grade. The LC/MS system consisted of a Waters (Milford, OH, USA) Alliance 2695 HPLC, coupled to a Waters Micromass ZQ spectrometer (electrospray ionization mode, ESI+). All the analyses were carried out using a Chromolith (Fontenay sous Bois, France) HighResolution RP-18e (4. 6 × 25 mm, 15 nm-1. 15 µm particle size, flow rate 3. 0 mL/min) column. A flow rate of 3 mL/min and a gradient of 0-100% B over 2. 5 min were used. Eluent A: water/0. 1% HCO 2 H; eluent B: acetonitrile/0. 1% HCO 2 H. UV detection was performed at 214 nm. Electrospray mass spectra were acquired at a solvent flow rate of 200 µL/min. Nitrogen was used for both the nebulizing and drying gas. The data were obtained in a scan mode ranging from 100 to 1000 m/z or 250 to 1500 m/z to in 0.
Electrophysiology Measurements cDNAs of rat nAChR subunits used in this study were provided by J. Patrick (Baylor College of Medicine, Houston, TX, USA) and subcloned into the oocyte expression vector pNKS2. cRNA was synthesized with the SP6 mMessage mMachine Kit (Ambion, Austin, TX, USA) and adjusted to a concentration of 0. 5 mg/mL. nAChR subunit RNAs were mixed in the ratios 1:1 (α3/β2), 5:1 (α4/β2), and 2:1:1:1 (α1/β1/δ/γ). Xenopus laevis (Nasco International, Fort Atkinson, WI, USA) oocytes were injected with 50 nl aliquots of cRNA (Nanoject automatic oocyte injector, Drummond Scientific, Broomall, PA). Antagonist dose-response curves were measured as described previously  (Dutertre et al. , 2005)  in ND96 (96 mM NaCl, 2 mM KCl, 1 mM CaCl 2 , 1 mM MgCl 2 , and 5 mM HEPES at pH 7. 4). In brief, current responses to acetylcholine were measured 1-6 days after cRNA injection and recorded at -70 mV using a Turbo Tec 05X Amplifier (NPI Electronic, Tamm, Germany) and Cell Works software.
A standard concentration of 100 µM ACh for α3β2, α4β2 nAChRs and (α1) 2 δγβ muscle nAChR and a standard concentration of 100 µM nicotine for the α7 nAChR was used to keep the data comparable to previous studies. A fast and reproducible solution exchange (<300 ms) was achieved with a 50-µL funnel-shaped oocyte chamber combined with a fast vertical solution flow fed through a custom-made manifold mounted immediately above the oocyte. Agonist pulses were applied for 2 s at 4-min intervals. Following one minute of perfusion directly after the agonist application, peptides were applied in a static bath for 3 min. IC 50 values were calculated from a nonlinear fit of the Hill equation to the data (Prism version 4. 0; GraphPad Software, Inc. , San Diego, CA). Data are presented as means ± S. E. M.
NMR Spectroscopy Lyophilized synthetic peptides were resuspended to a final concentration of ~2. 5 mM in 90%H 2 O:10%D 2 O. 2D 1 H-1 H TOCSY, 1 H-1 H NOESY, 1 H-1 H DQF-COSY, 1 H-15 N HSQC, and 1 H- 13 C HSQC spectra were acquired at 290 K using a 600 MHz AVANCE III NMR spectrometer (Bruker, Karlsruhe, Germany) equipped with a cryogenically cooled probe. All spectra were recorded with an interscan delay of 1 s. NOESY spectra were acquired with mixing times of 200-250 ms, and TOCSY spectra were acquired with isotropic mixing periods of 80 ms. Two-dimensional spectra were collected over 4096 data points in the f2 dimension and 512 increments in the f1 dimension over a spectral width of 12 ppm. Standard Bruker pulse sequences were used with an excitation sculpting scheme for solvent suppression.
Slowly exchanging amide protons were detected by acquiring a series of one-dimensional and TOCSY spectra over a 24 h period, following dissolution of the peptides in D 2 O. The two-dimensional NOESY spectra of CIA and CIB were automatically assigned and an ensemble of structures calculated using the program CYANA  [47]. Torsion-angle restraints from TALOS+ were used in the structure calculations. Distance restraints between the beta carbons and sulfur atoms of the cysteine residues that are disulfide bonded were included in the structure calculations. Restraints were included between Cys I-Cys II and Cys II-Cys IV. The final structures were visualized using Pymol.
Patients and blood samples The multicenter cohort FFABRY prospectively gathers clinical data and biological samples from patients with an enzymatic and/or genetic diagnosis of FD. The patients were sorted according to their phenotype: patients with a missense mutation and the absence of acral pain or cornea verticillata were referred to as non-classic Fabry patients, others were referred to as classic. Legal authorizations were obtained from the Comité consultatif sur le traitement de l'information en matière de recherche dans le domaine de la santé (n°14. 324bis) according to the relevant French legislation. Clinical data were prospectively collected through a standardized online form. Blood samples were collected at the time of inclusion. The samples were centralized in our research unit for isolation of peripheral blood mononuclear cells (PBMCs) using Ficoll-Hypaque™ gradient centrifugation technique before congelation at -80 °C in fetal-calf-serum (Life Technologies, Saint-Aubin, France, Catalog # 10270106) supplemented with 10% Dimethyl Sulfoxide at -80 °C.
Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available due to the individual person's data that are involved but are available from the corresponding author on reasonable request. 13  Nephrology and Renal Transplantation Department, Institut Francilien de Recherche en Néphrologie et Transplantation (IFRNT) ,  Henri-Mondor/ Albert-Chenevier University Hospital, APHP, Créteil, France. 14University of  Paris-Est-Créteil (UPEC) ,  DHU (Département Hospitalo-Universitaire) VIC (Virus-Immunité-Cancer) ,  IMRB (Institut Mondor de Recherche Biomédicale) ,  Team 21 ,  INSERM U 955 , Créteil, France. 15Internal Medicine Department,  Tours University Hospital, University of Tours ,  UMR INSERM 1253 , Tours, France. 16Internal  Medicine Department ,  Dupuytren University Hospital, Limoges, France.
Relationship between members of the Clavaminate synthase-like family. According to our knowledge, αKAOs encompass 11 phylogenetically unrelated enzyme families according to the InterPro database  20  (Table  S6 ). Enzymes that transform free L-amino acids, such as KDO1 and KDO5, are found in four different families represented by enzymes called VioC, MpDO, SadA and GriE (Table  S6 )  17, [21] [22] [23] [24]. Because they possess different folds (Table  S6 ), alignment of their whole structures is not possible. However, a structural alignment of the 2-His-1-carboxylate facial triad of their structures is possible and can help to define a spatial arrangement of functional groups (Fig. S5 ). KDO1 and KDO5 belong to the Clavaminate synthase-like family (CSL), which is classified in the IPR014503 InterPro family.
In order to analyze the sequence diversity and the relationships between proteins of this family, we performed a sequence similarity network (SSN) using the EFI-EST  25. In SSNs, the most related proteins are grouped together in clusters. The network reveals five highly populated sub-families for which there was no reported experimental data (Fig. 3A ). Mapping the annotation retrieved from Uniprot shows mis-annotation for the family as close homologs were assigned different functions or remote homologs are assigned identical functions (Fig. 3B ). For instance, the sub-family highly connected to the sub-family containing AsnO, brings together CAS annotated proteins. KDO5's subfamily is fully disconnected from other CSL dioxygenases, showing an early evolution away from them. However, sequences in the KDO5 sub-family share on average 70% identity and are found in two different taxonomic classes (data not shown), indicating that, although these sequences have evolved, the proteins maintain the same enzymatic activity  16, 26.
Active site profiles within CSL family. Enzymes catalyzing the same chemical transformation while sharing low sequence identity, present identical residues in their active site as evolutionary pressure tends to conserve the residues playing a critical role in the catalysis  27. Because loop or subdomain insertions can disrupt sequence alignment, these conserved residues are better identified in protein structures. Previously, it has been shown that, in general, substrate specificity is linked to the presence of a few distinctive amino acids in the active site  28. To understand what makes CSL dioxygenases specific to a range of substrates, we carried out an analysis of the active sites of all its members. Homology modeling and subsequent classification of active sites was performed using ASMC (Active Site Modeling and Clustering) software  29.
e. Arg in G12 or Gln/Glu in the other groups of Clade III). Interestingly, G4 and G6 groups do not display this negatively charged sub-pocket, but a hydrophobic (motif NPIN from P12 to P15) and positively charged (motif PYRA/V) sub-pocket respectively (Fig. 5 ). The consequent assumption is that enzymes from G4 might catalyze the hydroxylation of hydrophobic substrates, while those from G6 might transform amino acids with a negatively charged side chain, such as glutamate or aspartate. The sub-pocket we describe here cannot be found in the crystallographic structures of other αKAO known to transform hydrophobic substrates or aspartate, such as P3H2, P4H, AspH, all classified in another InterPro family (IPR007803) (Table  S6 ). Indeed, the substrate/product binding pocket of these enzymes are not structured the same way as in CSL enzymes (Fig.
0, 50 mM NaCl, 10% glycerol at a flow rate of 0. 3 ml/min. The oligomerization state of the targeted protein was determined according to its elution volume compared to a calibration curve obtained with proteins of known global molecular weight. Crystallization, data collection and structure determination of KDO1 and KDO5. The initial screening was carried out on a mosquito crystal liquid handler (TTP Labtech, Cambridge, UK) using sitting drops of 150 µl of protein. For KDO1, larger crystals were grown using equal volume drops of KDO1 at 9. 3 mg/ml in 0. 050 M Tris-HCl, 0. 2 M NaCl, 0. 001 M DTT, pH 8. 0 and of reservoir solution, by hanging drop vapor diffusion. For KDO5, crystallization experiments were carried out using equal volume drops of KDO5 at 5 mg/ml in buffer, 0. 050 M Tris-HCl, 0.
X-ray diffraction data sets were collected at the SOLEIL Synchrotron (Saint Aubin, France), on beamline Proxima 1 of a Dectris Pilatus 6 M detector, or on beamline Proxima 2 A of a Dectris EigerX 9 M or ADSC Q315r detector (Tables  S1  and S2 ). Data processing was carried out at the synchrotron facility using XDS with the xdsme script  36. To solve the KDO1 structure, molecular replacement was carried out using PDB entry 2WBO  17, 37  as the model. The electron density maps were viewed and fitted in COOT  17, 37  and fitted with the sequence corresponding to UNIPROT C7QJ42. To solve the KDO5 structure, since molecular replacement with various models failed, a heavy-atom soaking approach was followed. The crystals used to solve the structure were obtained by being soaked for 20 mins. in 26% polyethylene glycol 3350, 0.
2 M Imidazole malate, 0. 15 M Li 2 SO 4 at pH 7. 0 with 0. 2 mM K 2 ReCl 6 in a cryosolution composed of 30% CM5. A data set spanning 360° of data was recorded at the rhenium L3 absorption edge. Four rhenium sites were located using SHELXD  38. Initial Re-SAD phases were estimated and refined using PHASER  39, 40  and then improved and extended by density modification, including NCS averaging, using the PARROT program  39, 40. A first model could be built automatically by BUCCANEER  37, 41  and the rebuilding completed using COOT  17, 37  with the sequence corresponding to UNIPROT J3BZS6. The structures were subjected to various cycles of rebuilding COOT and refinement with BUSTER  42. To take into account the anisotropic fall-off in resolution for KDO5-Lys and KDO5-α-KG datasets, STARANISO  43  was used.
These data were used in all subsequent model building and refinement cycles. The structures have been analyzed with PISA and PLIP  44  servers to calculate the surface buried in the interfaces and the interactions made by the ligands  45. Of the four monomers in the asymmetric unit, the monomer with the lowest Local Ligand Density Fit (LLDF) score and the strongest electron density for the ligand is considered to be the most representative  46. Sequence similarity network. The initial set of proteins, containing all members of the Clavaminate synthase-like InterPro domain (IPR014503), was collected in May 2017 (587 sequences). Homologs to KDO1 and KDO5 retrieved from Uniprot using a Z-score threshold value of 150 were added to the set. The list of proteins (UniProt IDs) was provided to SSN-EFI (http://efi.
Active site classification. To the set of CSL family, we added 153 homologs to KDO1 and KDO5 retrieved from Uniprot using a threshold Z-score value of 150. The entire set was clustered based on 100% sequence identity to obtain a non-redundant set of 608 proteins. Only proteins sharing at least 22% of sequence identity with at least one alpha αKAO for which structures are available were kept (see following paragraph). In total 523 proteins were used for the active site classification, using ASMC software with three main steps  29. Firstly, homology models for our set were built using structures templates, the crystal structures of CAS1 in complex with α-KG and proclavaminic acid (PDB 1DRT, chain A), VioC with (2S, 3S)-hydroxy-arginine (2WBQ, A), AsnO with succinate and (2S, 3S)-hydroxy-asparagine (2OG7, A), OrfP with succinate and (3R, 4R)-dihydroxy-L-arginine (4M2G, A), KDO1 and KDO5  17, 19, 31, 32.
Comparing lids and dimer interfaces between members of the family. Homology models built were structurally aligned on KDO5 structure. We examined the residues that are structurally aligned with the extremities of the lid loop highlighted in this work. The lid corresponds to residues from 230 to 242 in KDO5. Dimer interfaces formed by αKAOs monomers for each homology model were examined using an alternative version of the ASMC option (unpublished). In this version, the residues in contact between chain A and B of the KDO5 crystal structure are provided to ASMC to form logo sequences. Interface residues are retrieved using the BioPython/GetInterfaces. py script (provided by www. blopig. com). Residues are considered in contact if any of their atoms are less than 4. 5 A from any atoms of residues of the other chain.
Acknowledgements The authors would like to thank  V. Pellouin ,  C. Pellé ,  P. Sirvain  and  A. Fossey-Jouenne  for excellent technical assistance. This work was supported by  Commissariat  à l' énergie atomique et aux énergies alternatives (CEA), the  CNRS  and the  University of Evry Val d'Essonne. The authors are grateful to  Dr. Alain Perret ,  Dr. Carine Vergne-Vaxelaire  and  Dr. Bret Church  for helpful discussion and to The Faculty of  Medicine and Health, University of Sydney , for hosting KB as a visitor scientist. We acknowledge synchrotron  SOLEIL (Saint-Aubin, France)  for provision of radiation facilities on the PROXIMA-1 and PROXIMA-2A beamlines.
Acknowledgements J. P. and J. C ˇ. acknowledge the  Charles University Centre of Advanced Materials (CUCAM)  ( OP VVV Excellent Research Teams , project number  CZ. 02. 1. 01/0. 0/0. 0/15_003/0000417 ) and the  Czech Science Foundation  ( P106/12/G015 ). J. C ˇ. , P. P. , and D. S. gratefully acknowledge the financial support from the  European Union Seventh Framework Programme  ( FP7/2007-2013 ) under grant agreement no. 604307  ( CASCATBEL  project). P. P. and D. S. also acknowledge the funding received from the  Spanish Ministry of Economy and Competitiveness  through the  CATPLASBIO  project (Ref. CTQ2014-602209-R ).
Acknowledgements This material is based upon work supported by the  U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences , and was conducted at  Argonne National Laboratory , operated for the  U. S. Department of Energy  under contract number  DE-AC02-06CH11357. Computational resources have been provided by the  Laboratory Computing Resource Center of the Argonne National Lab  (Project MDCounterIons  FY-16 ) and the PhLAM cluster financed by the  Agence Nationale de la Recherche  through the  LABEX CaPPA  ( ANR-11-LABX-0005-01 ) and the  Ministry of Higher Education and Research, Hauts de France council and European Regional Development Fund (ERDF)  through the  Contrat de Projets Etat-Region (CPER CLIMIBIO ).
Crystallographic studies. Single crystal X-ray diffraction data were collected using a Bruker APEX II X-ray diffractometer. The diffractometer is equipped with a graphite monochromated X-ray source using Mo K α radiation (λ = 0. 71073 Å). Reflection intensities were collected using four orientations of the crystal in φ, and 0. 5°scans in ω over 180°. All the data were collected at 100 K using and Oxford Cryosystems 700 series cryostat. The unit cells were determined using the APEX II suite of software. Corrections for absorption were performed using SADABS  40. Structure solutions and refinement were carried out using SHELXS and SHELXL respectively  41. Computational details. All cluster geometries were optimized with the Turbomole package at the density functional theory level (DFT), using the PBE0 density functional with an ultrafine integration grid, m4, and converging the structure when the Cartesian norm reached 10 -4 atomic units  42, 43.
Metal-ligand chemical bonds were analyzed through the topology of the electronic density with the QTAIM theory implemented in the AIMall package  34, 53, 54. Natural Localized Molecular Orbitals (NLMOs) were computed with the NBO6 program  55. Data availability. The data that support the findings of this study are available from the corresponding authors upon reasonable request. Crystallographic information files have been depostited with the Cambridge Crystal Structure Database under accession codes 1588065 (Rb), 1588066 (Cs), 1588067 (Me 4 N). These data can be obtained free of charge from The Cambridge Crystallographic Data Centre via the Internet at www. ccdc. cam. ac. uk/data_request/cif. The data supporting the quantum chemical calculations and structures are available on the free platform Zenodo with the identifier 10.
Mass Spectrometry Electrospray ionization-mass spectrometry (ESI-MS) experiments were performed using a Bruker HCT Ultra ETD II quadrupole ion-trap (QIT) equiped with an ESI source, Esquire control 6. 2 and Data Analysis 4. 0 software package (Bruker, Bremen, Germany). The ESI parameters were capillary and end plate voltages set respectively to +3. 5 and +3. 0 kV in negative ion mode. The skimmer and the capillary exit voltages were set respectively to -30 and -80V and the injection low mass cut-off (LMCO, corresponding to the "trap drive" parameter) value was m/z 40. Sample solutions were either infused into the ESI source at a flow-rate of 3 µL. min -  by means of a syringe pump (Cole-Palmer, Vernon Hills, Illinois, USA) for full scan data or injected into the ESI source at a flow-rate of 100 µL.
We therefore explored the possibility of using bacteria labeled for a long period. We obtained the median value of the isotope fraction [ 12 C 15 N/( 12 C 14 N+ 12 C 15 N)] for all of the pixels in a population of E. coli labeled for 128 minutes (Supplementary Figure  14A ); each bacterium therefore has a percentage, p, of its own pixels above this median and (100-p) below it. A histogram was then used to give an idea of the diversity of incorporation (Supplementary Figure  14B ). Since the form of the histogram depends on the arbitrary choice of the bin, we used kernel density estimation (Supplementary Figure  14C ); this entails replacing each sample point of the data with a Gaussian-shaped kernel, and then summing these kernels (via Matlab). This gave distributions that could readily be compared with one another.
g. , for 4 and 8 min) should be much smaller. To quantify this, we wrote a program in Visual Basic 6 to simulate the effect of the random loss of the pool to different degrees in different cells. We set the program's variables for the isotope concentrations to the values corresponding to our growth rate calculations. We then used a random distribution of losses of the pool that gave the maximum CV we observed experimentally (20% after labeling for 2 min); exactly the same distribution of losses of the pools was subsequently used for the other labeling times. For a couple of 100 cells that initially had a pool of small molecules of 3%, the program gave CVs of 20, 14, 7. 8, 3. 9, 1. 9, 0. 94, and 0. 47% for 2, 4, 8, 16, 32, 64, and 128 min labeling, respectively (Supplementary Table  2 ); these values are significantly different from the corresponding experimental values of  18, 20, 17, 12, 8, 6 , and 5%.
ACKNOWLEDGMENTS For technical and statistical assistance, we thank  Laurent Quillet ,  Josselin Bodilis ,  Sylvaine Buquet ,  Sylvie Bertin , and  Angela Flores Ribeiro. For advice, we thank  Arieh Zaritsky ,  Conrad Woldringh ,  Itzhak Fishov ,  Alfonso Jimenez-Sanchez ,  Silvia Zaoli ,  Marco Lagomarsino-Cosentino , and  Dick D'Ari. For support, we thank the  Epigenomics Project, Genopole ,  DYCOEC  ( GDR 2984 ) and the  European Network in Systems Biology  ( GDRE 513 ),  Conseil Général de l'Eure , the  Labex SynOrg  ( ANR-11-LABX-0029 ), the  Région Haute-Normandie  ( CRUNCH network ) and the  European Regional Development Fund  ( ERDF 31708 ).
Solid state 13 C{ 1 H} and 29 Si{ 1 H} NMR spectra were recorded with a Bruker Avance 500 spectrometer (Karlsruhe, Baden-Württemberg, Germany) equipped with a 4 mm H/X MAS probe, operating at a Larmor frequency of 500. 1, 125. 8, and 99. 35 MHz for 1 H, 13 C, and 29 Si, respectively. Samples were filled into a 4 mm ZrO 2 rotor and spun at 10 kHz for direct polarization (DP) or cross polarization (CP) experiments under high-power 1 H decoupling. No significant difference in relative signal intensities between spectra recorded with DP or CP conditions indicates quantitative measurements. 29 Si CPMAS NMR spectra were recorded with a 5 s recycle delay and 750 transients. All experimental data were zero-filled to double the number of experimental points. Chemical shifts were calibrated with respect to standard tetramethylsilane, TMS (0.