dataesr/scientific-paragraphs-categorization huggingface dataset:
2e )  23. In addition to the DrII HTH domain, the DALI search found another similar structure to the Dss1 HTH domain: a DNA-binding domain of the bacterial quorum-sensing transcription regulator SdiA  24  (PDB ID: 4Y13). In Dss1, the HTH and S1 domains interact with each other through an interface between a loop that connects the last two β-strands of the S1 and C-terminus of the first helix of the HTH (Fig. 1b ). The structure of Cg-Dss1 70-900 D477N comprises an additional unique element, an N-terminal helix (residues 77-90), that protrudes from the core of the protein (Fig. 1b ). The catalytic domain of Cg-Dss1 is very similar to the RNB domains of the other RNase II family members and can be superimposed on them with an RMSD between 1. 6 and 2. 0 Å (Supplementary Fig. 3a, b ). Cg-Dss1 also possesses the S1 domain (residues 831-900 in Cg-Dss1; Fig.
The activity of these variants was tested in RNA cleavage assays (described in detail in the Supplementary Note 2, Supplementary Fig. 5 ). We obtained crystals for Dss1 70-900 D477N in complex with Suv3  in the presence of a dsRNA substrate with a 3′ 8 nt overhang (annealed 20Tx and 12Bx oligonucleotides; Supplementary Table  2 ) and ATP/Mg 2+. These  rystals belonged to the C 2 2 2 1 space group (Table  1 ). The structure was solved by molecular replacement using two search models: (i) the refined Cg-Dss1 structure described above and (ii) a homology model of Candida glabrata Suv3 protein prepared with Swiss-Model 26 based on the published structure of the human enzyme  7  (PDB ID: 3RC3). The final model was refined at 3. 55 Å resolution (Fig. 2a, b ; Supplementary Fig. 1c ). The tracing of the model was confirmed by calculating anomalous difference maps from the data sets that were collected for crystals of the mtEXO complex in which either Dss1 70-900 or Suv3  was selenomethionine-substituted (Supplementary Fig.
We assume that the 17 to 16 nt truncation is a result of the cleavage of the last nucleotide located at the active site of the Dss1 nuclease (Fig. 4b ). Therefore, the observed fragment length was 1 nt shorter than the length of RNA within the catalytic channel of Cg-mtEXO that was predicted based on the complex structure. For fl-Cg-Dss1 protein alone, the additional band observed in the presence of the antibody was 8 nt in length (Fig. 4c ). This corresponds to the length of the RNA that can be accommodated in the RNAbinding channel of Dss1 that was predicted based on the RNase II and Dis3L2 structures in complex with longer RNAs. mtEXO but not Dss1 alone degrades structured RNAs. The data presented so far support a model in which the RNA is directly fed by Suv3 ATP-dependent helicase activity into the Dss1 RNA-binding channel and toward the active site.
We verified that mtEXO from C. glabrata also cleaves dsRNA that contains a 3′ overhang only it the presence of ATP, whereas Cg-Dss1 that lacks intrinsic helicase activity is unable to process dsRNA (Supplementary Fig. 9c ). However, no biochemical data are currently available on mtEXO activity toward structured RNA, such as excised group I introns, the accumulation of which is toxic to the cell  29. Therefore, we investigated whether mtEXO has any further advantage over Dss1 alone in degrading structured RNAs. To test this, we combined 5′ 32 P-labeled RNAs with either fl-Cg-mtEXO or fl-Cg-Dss1 alone in the presence of ATP/Mg 2+ and performed kinetic time-course exoribonuclease assays. We first analyzed RNA that does not form any secondary structure: R36 (see Supplementary Fig. 10  for sequence).
Given the unusual features of Suv3 among SF2 enzymes, different modes of ATP/ADP binding between Suv3 and NS3, and different structures of the auxiliary domains of the two helicases, their comparisons are only an approximation. Nevertheless, the nature of the possible movements of the two RecA domains can be analyzed. Importantly, these analyses show that the movements of Suv3 can be accommodated with the mtEXO complex. One can envisage that RecA1 and C-terminal domains of Suv3 form a relatively rigidly placed platform that interacts with Dss1. RecA2, which does not form contacts with Dss1, is free to move during ATP hydrolysis and the resulting RNA translocation. Analyses of the AMPPNP-bound structure of Hs-SUV3 7 (PDB ID: 3RC8) indicate that the conformational state of Suv3 in our mtEXO complex structure corresponds to the ATP-bound state.
1 molar ratio and supplemented with 0. 5 mM MgCl 2 and 0. 5 mM ATP. Annealing of the oligonucleotides resulted in a 12 bp duplex region with a 3′ 8 nt overhang. Sitting-drops were set up at 18 °C with an equal volume of the protein complex and reservoir solution. Optimized crystallization conditions from the Index Screen (Hampton Research) contained 0. 2 M ammonium citrate tribasic (pH 7. 0) and 18% (w/v) PEG 3350. Native and selenomethionine derivative crystals that were grown using the hanging-drop method were cryoprotected in 30% glycerol and flash frozen in liquid nitrogen. Structure solution and refinement. X-ray diffraction data for selenomethionine Cg-Dss1 70-900 D477N crystals were collected at beamline I04 at Diamond Light Source, UK. The crystals belonged to space group P 1 and diffracted X-rays to ~2.
7 Å. Because of radiation damage, data sets were collected from different regions of the crystal. Diffraction data were processed and scaled with XDS  43. To improve the signal-to-noise ratio and multiplicity, three data sets that were collected at selenium peak wavelength (0. 9785 Å) were merged in Aimless from the CCP4 Program Suite  44, 45. The Cg-Dss1 70-900 D477N structure was solved using SAD in the AutoSol module in Phenix  46  with two protein molecules in the asymmetric unit. Manual model building was performed in COOT  47  and the structure was refined in phenix. refine  46 with 5% of unique reflections flagged for R free calculation. In the final model, 96% of the residues were in the most favored region of the Ramachandran plot, and 0. 26% were localized in the disallowed region according to MolProbity  48.
For the purpose of refinement, the RNA chains were traced as 5′-CACUGA-3′ and 5′-AGAUAC-3′ for molecules I and II, respectively. However, because the RNA fragments co-purified with the protein, we expected them to have a mixture of various sequences. Initial X-ray data sets for the mtEXO complex (Cg-Dss1 70-900 D477N and Cg-Suv3  ) were collected beamline 14. 1 at Berliner Elektronenspeicherring-Gesellschaft für Synchrotronstrahlung in standard collection mode. A fina  dataset with helical crystal rotation was collected at microfocus beamline 23-2 at the European Synchrotron Radiation Facility, Grenoble. The structure was solved by molecular replacement in PHASER  49  using the previously solved structure of Cg-Dss1 70-900 D477N and the Cg-Suv3 homology model that was prepared in Swiss-Model  26  based on the human SUV3 structure (PDB ID: 3RC3) as search models.
To confirm the tracing of the model, we produced crystals of the Dss1 70-900 -Suv3  complex, in which either Dss1 (14 methionines) or Suv3 (21 methionines) was substituted with selenomethionine (when both proteins were SeMet-modified, the crystals did not diffract X-rays). X-ray  iffraction data were collected at selenium peak wavelength at Deutsches Elektronen-Synchrotron, Hamburg. Anomalous difference maps were calculated in Phenix to localize the selenium atoms of methionine residues. Anomalous difference peaks were observed for 30 of 35 methionines that were present in our model, confirming the correctness of our tracing. The electron density maps for the N-terminal portion of Cg-Suv3 were of poor quality, and the low sequence conservation of this domain between Homo sapiens and C. glabrata made it very difficult to use the human structure to trace this part of the mtEXO complex.
It contains five methionines, so anomalous difference maps could be used to guide model building for this region. However, because of the poor quality of the electron density maps, the ND structure of Cg-Suv3 has to be treated with caution. Although RNA was present in the crystallization drops, we did not observe electron density for the nucleic acid, with the exception of a 6 nt fragment near the active site of Cg-Dss1, which co-purified with Cg-Dss1 protein, similar to the structure of Cg-Dss1 70-900 D477N alone. The RNA that was added to the crystallizations of mtEXO apparently promoted the formation of crystals but was not incorporated in the structure. Small-angle light scattering data collection. X-ray scattering experiments for the complexes of full-length Cg-mtEXO and a complex with a truncated ND of Suv3 (Cg-Dss1-Suv3 183-699 ) were performed using the laboratory SAXS system Xeuss 2.
0 (XENOCS, Grenoble, France), which was equipped with a MetalJet D2 microfocus X-ray generator (0. 134 nm wavelength). Protein samples were injected in the lownoise liquid sample cell and incubated during measurements at 293 K. The details for the samples are shown in Supplementary Fig. 9. SAXS data were collected in 12-18 subsequent 10-min frames (total exposure time = 2-3 h) using a Pilatus3 1 M silicon pixel detector (Dectris, Switzerland). Data reduction and buffer subtraction were performed using the Foxtrot package. During the processing procedure, all of the frames were checked for radiation damage. Structural parameters that characterized the studied complexes (radius of gyration [R g ], Porod volume) were calculated in Primus from the ATSAS package  50. The pair distance distribution function (P[R]) was calculated using Gnom  51.
Molecular modeling of SAXS data. Low-resolution models of Cg-mtEXO and Cg-Dss1-Suv3 183-699 complexes were obtained using the ab initio modeling program Dammin  52  based on the experimental SAXS data. For each studied sample, at least 10 independent models were generated and subsequently averaged and filtered using Damaver  53. The full-length protein structures from the Cg-mtEXO complex for the molecular dynamics simulation were built in Modeller 9. 17  54. The Cg-Dss1 70-900 D477N crystal structure was used as a template, and missing parts were added in Modeller. The generated models were superimposed on the corresponding subunits from the crystal structure of the Cg-mtEXO complex. Residues 43-172 and 185-684 from Cg-Suv3 and 77-900 from Cg-Dss1 were excluded from the conformational sampling procedure.
7 ). Recombinant proteins and protein complexes (100 µl, 1 mg ml -1 ) were fractionated at room temperature on Superdex 200 Increase 10/300 column (GE Healthcare) equilibrated with SEC buffer that contained 20 mM Tris-HCl (pH 7. 5), 150 mM NaCl and 1 mM DTT at 0. 5 ml min -1. Elution of proteins was monitored by the following in-line detectors: UV 280/254 nm (1220 Infinity LC, Agilent Technologies), light scattering (DAWN HELEOS II, Wyatt Technology) and differential refractometer (Optilab T-rEX, Wyatt Technology). Data analysis and molecular weight calculations were performed using ASTRA 6 software (Wyatt Technology) using differential refractive index for a concentration calculation. RNA degradation assays with FAM-labeled RNAs. RNA degradation assays were performed in buffer that contained 10 mM Tris-HCl (pH 7.
Acknowledgements We thank  Roman Szczęsny  and  Janusz Bujnicki  for critically reading the manuscript,  Prof. Dr Claudia Höbartner  for helpful comments on alkaline hydrolysis ladders and  Iwona Ptasiewicz  for excellent technical assistance. This work was funded by  National Science Center SYMFONIA  grant ( 00463  to M. N. and P. G. ), National Science Center  FUGA grant  ( UMO-2012/04/S/NZ1/00036  to Z. W. ) and National Science Center OPUS grant ( 2014/15/B/ST4/04839  to M. K. ). This work was also supported by the  Centre for Preclinical Research and Technology (European Union   POIG. 02. 02. 00-14-024/08-00 ). M. N. was a recipient of Ideas for Poland awards from the  Foundation for Polish Science.
Data availability. Coordinates and structure factors for Cg-Dss1 70-900 D477N and Cg-mtEXO (Cg-Dss1 70-900 D477N in complex with Cg-Suv3  ) are deposited in the Protein Data Bank under accession numbers PDB: 6F3H and 6F4A. All ot er data are available from the corresponding author upon reasonable request.
Genome Analysis Genome assembly was performed de novo using A5 with default parameters  [17]. tRNAs and rRNAs were detected using ARAGORN v1. 2. 36  [18]  and the RNAmmer Prediction Server 1. 2  [19] , respectively. MLST 1. 8 server was used to determine the ST  [20]. The genome was subjected to BLAST analysis against Resfinder 3. 0  [21]  the Antibiotic Resistance Database (ARDB)  [22]  and the Comprehensive Antibiotic Resistance Database (CARD)  [23]. PHASTER detected putative phage sequences in the genome  [24]. Capsular serotype was determined using the automated WGSbased serotyping bioinformatics tool, PneumoCaT (Pneumococcal Capsule Typing)  [25]. The presence of genomic islands (GIs) was determined using IslandViewer 4  [26]. The sequences of gyrA and parC were extracted and compared with reference sequences for parC (accession no.
SNPs-based Phylogenetic Analysis The sequenced genome was aligned against the chromosome of SP49 using the Burrows-Wheeler Aligner (BWA). SNP-calling was performed by mapping the genome of LAU-23F to 24 genome sequences of S. pneumoniae strains retrieved from NCBI using the BioNumerics v7. 6. 1 beta software (Applied Maths, Sint-Martens-Latem, Belgium). A neighbor-joining (NJ) tree of categorical differences was drawn in BioNumerics by using synonymous mutations from the filtered wgSNPs data as input.
Results Dome Fuji isotope and temperature records. We used the second DF ice core (DF2; 77˚19′ S, 39˚42′ E, 3810 m above sea level)  20  to obtain a 720-kyr deuterium excess (d = δD-8δ 18 O) record. The δD and δ 18 O values of the ice between the depths of 2399. 5 and 3035. 1 m (297-715 kyr BP) were measured at 10-cm intervals. The new DF2 data were combined with earlier data from the first Dome Fuji core (DF1  21, 22  ) and were plotted on the AICC2012 time scale  23. The relationships among δD, d, ΔT site and ΔT source were quantified using a mixed cloud isotopic model (Methods). In this study, temperatures are expressed as deviations, Δ, from the modern value (the average of the past 2 kyr). ΔT source is a proxy for temperature in moisture source regions  19, 22  , and the major moisture source for modern precipitation at DF is estimated to lie in the South Atlantic and Indian Oceans between 38 and 65˚S, based on backwardtrajectory calculations  [24] [25] [26]  (Fig.
The isotope data are given using conventional δ notation: δ = R sample / R VSMOW -1, where R sample and R VSMOW are the isotopic ratios (D/H and 18 O/  16  O) of the sample and Vienna Standard Mean Ocean Water (VSMOW), respectively. To improve the precision of the measurements, 45% of the samples were measured two to four times. The analytical precisions (1σ), which are based on the differences between the duplicate analyses of individual samples, were 0. 44‰ (δD), 0. 05‰ (δ 18 O) and 0. 52‰ (d). Combining the record and the time scale. To obtain a complete isotopic record over 720 kyr, we used published data sets from the first Dome Fuji (DF1) core for shallow depths ranging from 0. 0 to 2399. 5 m. For the portion of the record derived from the DF1 core  21, [56] [57] [58]  , the resolution was ca.
23 to ±0. 75‰, which is not significant when compared with the ca. 6‰ amplitude of the glacial cycles (Supplementary Fig. 3 ). Furthermore, general circulation models generally support the interpretation of ΔT source in Antarctica  73, 74. SST records. In total, 17 SST records from ocean sediments  50, [75] [76] [77] [78] [79] [80] [81] [82] [83] [84] [85] [86]  within the DF moisture source region (Fig. 1 ) were collected from published databases. Various proxies (alkenones, Mg/Ca and faunal) were used to reconstruct the SSTs within that region. Six of the profiles reflect annual mean SSTs, whereas nine of the profiles reflect summer SSTs. Two of the profiles were produced by averaging summer and winter SST records  85. The SST values are expressed in terms of deviations from the modern value, ΔSST (Supplementary Fig.
1  and Supplementary Fig. 4 ). Albedo data. The albedo climatology was derived from data collected by the TIROS-N satellite. This data set was obtained from the climate data archive of the Joint Institute for the Study of the Atmosphere and Ocean (http://www. jisao. washington. edu/). The albedos of the DF region and the moisture source region are 0. 78 and 0. 46, respectively. Significance of the correlation coefficient. The uncertainty of the linear correlation coefficient was estimated using the Fisher Z-transform. For the entire record, the 90% confidence ranges of the correlations (R 2 ) of CO 2 with δD, ΔT site and ΔT source are 0. 68-0. 73, 0. 76-0. 80 and 0. 75-0. 79, respectively. For the lukewarm period, the ranges of the correaltion of CO 2 with δD, ΔT site and ΔT source are 0. 60-0.
70, 0. 72-0. 79 and 0. 77-0. 83, respectively. Thus, the correlation between ΔT site (and ΔT source ) and CO 2 is significantly stronger than that between δD and CO 2. The correlation between ΔT source and CO 2 is slightly higher than that between ΔT site and CO 2 , but it is statistically insignificant. Spectral analyses and the obliquity component. Spectral analyses were conducted with the Blackman-Tukey method (30% lag) using the Analyseries software package  87  (Fig. 3  and Supplementary Fig. 5 ). The amplitudes of the records were normalized to a standard deviation of 1. The data shown in Fig. 3  were resampled using linear interpolation to a 700-yr interval, which is the average resolution of the composite CO 2 record, and then smoothed using a 1-kyr cutoff low-pass filter. The data in Fig.
S5  were resampled using linear interpolation to a 100-yr interval. The insolation data  88  and the 41-kyr obliquity components (Fig. 4 ) were calculated using a Gaussian filter using the Analyseries software package (f = 0. 0244 (1/kyr) with a bandwidth of 0. 00488). The uncertainties associated with the phase analysis were of three types: (i) ice-age versus ice-age phase analysis error (σ phs ). The relative lags between the temperature proxies were as reliable as possible because they were estimated from the same ice sample. The phase analysis between ΔT site and ΔT source (Supplementary Fig. 5 ) is shown with a confidence interval. (ii) Ice-age versus gas-age phase analysis error (σ CO2 ). Determining the exact phase lag between CO 2 concentrations and temperatures was complex because the air was younger than the surrounding ice.
Acknowledgements We thank  Maki Nakada ,  Hironobu Yamada  and  Satoru Kikuchi  ( NIPR ) for supporting the sample preparation and the isotopic measurements of the ice. We acknowledge support from a  JSPS   Postdoctoral Fellowship for Research Abroad. This study was supported by  JSPS KAKENHI  (grant numbers  21221002 ,  26550013 ,  17H06104  and  17H06320 ). This study was also supported by the  ANR Dome  A and ASUMA projects; and by  National Institute of Polar Research (NIPR)  through Project Research  KP305.
Data were analyzed with the BD FACSDiva™ software (BD Biosciences) or FlowJo (TreeStar, Ashland, OR). All antibodies are rat monoclonal antibodies from BD biosciences: anti-B220 (clone RA3-6B2) conjugated with pacific blue, anti-CD19 (clone 1D3) conjugated with Alexa Fluor 700, anti-mouse Igk light chain (clone 187. 1) conjugated with Phycoerythrin-Cyanin7, anti-IgM (clone R6-60. 2) conjugated with Peridinin chlorophyll protein-cyanin5. 5. Ba/F3 cells were similarly transduced with empty MIE, MIE-PAX5A or MIE-PAX5B and then GFP-positive cells were isolated by fluorescence-activated cell sorting (FACS) in MoFlo Astrios (Beckman Coulter).
3 μg/mL of primary antibody overnight at +4° C (mouse anti-Pax-5 mAb (A-11), Santa Cruz Biotechnology). After incubation with secondary antibodies conjugated to horseradish peroxidase (Cell Signaling Technology), the immunoreactive bands were visualized by using the enhanced chemiluminescence lighting system (Amersham™ ECL™ Prime Western Blotting Detection Reagent, GE Healthcare) and data was acquired with Chemi-Smart 5000 and Bio-1D software (Vilber Lourmat). Bands were quantified by using ImageJ software.
Flow cytometry and cell growth Transduced pro-B cells and Ba/F3 cells were stained with AlexaFluor700-conjugated anti-CD19 (1D3) antibody (BD Pharmingen). For cell-viability assays, cells were stained with Annexin-V-PE and 7-AAD (BD Biosciences #559763). Flow cytometric data were acquired on a Fortessa X20 or LSR II flow cytometer (BD Biosciences), and data were analyzed using FACSDiva (BD Biosciences) and FlowJo software (TreeStar).
Probe-signal intensities were normalized and summarized by the Robust Multiarray Average (RMA) method using Affymetrix's Expression Console software. The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus  [43]  and are accessible through GEO Series accession number GSE104890 (https://www. ncbi. nlm. nih. gov/geo/query/ acc. cgi?acc=GSE104890). For the volcano plots, permutation analyses were performed with dChip software  [44]  allowing the calculation of false discovery rate p-value and the fold difference volcano plots were generated using GraphPad prism software. The gene ontology analysis has been performed with the AutoCompare ZE software  [45]  using Gene Ontology database  [18, 19] , p-values have been calculated with the ZE test.
Statistical analysis Experiments have been performed at least as three independent conditions. All statistical analyses were performed using Excel (Microsoft) and GraphPad Prism software, version 7 (GraphPad Software). Statistical differences were determined using a 2-tailed Student's t test or RM one-way ANOVA with Tukey's correction or one-way ANOVA with Sidak's correction for multiple comparisons or Pearson correlation, as mentioned in legends. All data are presented as mean ± SD or SEM. A p-value of less than 0. 05 was considered statistically significant, the null hypothesis being rejected at the 0. 05 level ( *** p < 0. 0005, ** p < 0. 005, * p < 0. 05).
Cols. (  8 ) and (  9 ⊙ kpc -2 , Σ IR =(L IR /2)/[π(R circ ALMA ) 2 ] , where L IR is given in Table  3  and R circ ALMA in Col. (6). Col. (11) IR8=L IR /L 8µm color index. The 8 µm rest-frame luminosities were derived from the observed Spitzer-MIPS 24 µm photometry as in  Elbaz et al. (2011). L 8µm , hence also IR8, can only be determined from the observed 24 µm luminosity for galaxies with 1. 5≤z≤2. 5. subsequently re-calibrated the WFI astrometry to match the HST Guide Star Catalog (GSC2). More modern astrometric data are now available in this field such as Pan-STARRS1  (Chambers et al. 2016). We used the PanStarr DR1 catalogue provided by  Flewelling et al. (2016)  to search for possible offsets in the different regions of the whole 10 ′ ×15 ′ GOODS-South field. We found residual distortions that we believe to be due to some combination of distortions in the WFI mosaic images and in the GSC2 positions, and zonal errors registering the HST ACS images to the WFI astrometry.
github. com/gbrammer/eazy-photoz 3 Publicly available at http://astro. berkeley. edu/ mariska/FAST. html thesis model to fit the observed photometry up to the IRAC 4. 5 µm band. We assumed a solar metallicity, a  Salpeter (1955)  IMF and a  Calzetti et al. (2000)  attenuation law with A V ranging from 0 to 4. The dust side of the SED of the galaxies (from the Spitzer IRS-16 µm and MIPS-24 µm to the ALMA flux densities) was modeled using the IR emission spectra for dust heated by stellar light from  Draine & Li (2007)   (  Noll et al. 2009). Following  Draine et al. (2007) , we fixed the slope of the distribution of intensities of the interstellar radiation field (ISRF, U), α, to α=2 and adopted an upper limit of U max =10 6 U ⊙ for the ISRF in units of the solar ISRF. The best-fitting SED was used to determine for each galaxy its total dust emission, L IR , and a dust mass, M dust , listed in Table 3.