dataesr/scientific-paragraphs-categorization huggingface dataset:
The work was supported by the  Agence Nationale de la Recherche  through grant number  ANR-09-BLAN-0218  TOPPAZ, by the  European Union  through the  Network of Excellence BioSim  ( LSHB-CT-2004-005137 ), the Specific Targeted Research Project  TEMPO  ( LSHC-CT-2006-037543 ) and  ErasysBio+ Circadian  and  Cell Cycle Clocks in Cancer (C5Sys)  ( ANR-09-SYSB-007-04 ), and by grants from  'La Ligue Contre le Cancer' (Comites de la Drome et du Rhone)  and by the  Hospices Civils de Lyon -Groupement des   Hopitaux du Nord (Junior research  grant  2009 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Genome sequencing, assembly and automated annotation In order to identify the genetic bases of our two metal-tolerant mesorhizobia and to use them as references to map sequence reads from the transcriptome data sets, the draft genomes of the two studied strains were first sequenced using half a 454 run (Titanium kit) with paired-end reads from an 8 kb genomic bank for each isolate. After the assembly, the comparison with M. huakuii MAFF 303099 genome (chromosome accession number: BA000012, plasmid pMLa: BA000013 and pMLb: AP003017) led for both genomes to the identification and organization of 1 chromosomal (~6 Mb) and 1 plasmidic (~250 Kb) scaffolds. These genomes were integrated into the MicroScope platform  [13]  to perform automatic and expert annotation of the genes, providing 6,908 genomic objects for STM 2683 and 7,065 for STM 4661.
Genome sequences are also available from European Nucleotide Archive under accession numbers CAUM01000001-CAUM01000191 for strain STM 2683 and CAAF010000001-CAAF010000089 for strain STM 4661. The general genome characteristics for the two analyzed strains are listed in Table  1. As expected, CDS located on the plasmids were less conserved. We found that only 12% and 15% of CDS located on plasmids of STM 2683 and STM 4661 respectively possessed at least one homolog in the other strain. Despite the lower conservation observed for genes located on plasmids, we did not identify an over-representation of operons or genes that were associated with metals. Such results suggest that plasmids harbor accessory genes which are not specialized in metal adaptation in the strains STM 2683 and STM 4661 contrary to the model C.
metallidurans CH34 where most metal-responsive genes are plasmidborne  [14]. In order to estimate genomic divergence between the two strains, we explored the proportions of homologous CDS as a function of the identity percentage. Homologous genes present in the two strains were retrieved with the comparative genomics phyloprofile tool in MicroScope. Using an alignment threshold of 80% identity over at least 80% of the query sequence and target size, approximately 4,200 homologous genes, present in both strains, were identified (4,183 CDS from STM 2683 presented at least one homolog in STM 4661 and 4,186 CDS from STM 4661 presented a minimum of one homolog in STM 2683). These results show that approximately two thirds of the genomes are conserved in the two sequenced metal-tolerant strains (data not shown).
RNAseq analysis, mapping and statistical analyses using DESeq The universal bacterial rRNA subtraction kit (Microbe Express, Ambion) allowed for the removal of most rRNAs. Qualitative analyses of RNA samples prior and after depletion indicated that total RNA was of high quality (RIN values ranging from 7 to 10) and that most 16S and 23S rRNA peaks were removed after depletion (Additional file 1). The mRNA samples were sequenced in 36 bpcycles using the illumina HiSeq2000 (San diego, CA) with SBS technology. A lane of a FlowCell was used per sample. Image analyses and basecalling were conducted using the HiSeq Control Software (HCS 1. 1. 37. 8) and RTA component (RTA 1. 7. 48). The RNAseq data are available from NCBI GEO datasets under the accession number GSE45693. The number of reads which passed the initial quality filter varied from 68.
Interestingly, sequence reads were successfully assigned to all predicted genomic objects, suggesting that all CDS were transcribed and that sequencing was deep enough to cover the full transcriptomes. All read mapping data for STM 2683 and STM 4661 are accessible from the Microscope interface  [15]. Using the MicroScope automated RNASeq pipeline, mapping results were then translated into raw read counts for each gene and processed through the DESeq statistical package  [16]  to normalize and test for differential expression between conditions (see Methods). Basically, DESeq estimates library size factors to normalize gene read counts between samples by assuming that a majority of genes have comparable expression levels in all samples. It then estimates gene expression dispersion due to biological and technical variations within each condition, and models it using negative binomial distributions.
Because we observed a wide magnitude in the read count numbers per CDS, a logarithmic transformation of these data was performed. A logarithmic base-2 transformation of fold changes was used to represent expression differences. The Additional file 2 reports the descriptive statistics obtained from our quantitative RNAseq datasets. The variances obtained in expression statistical analyses (Additional file 2) were low (ranging from 0. 058 to 0. 075), indicating that most predicted genes presented similar expression levels across treatments. Box plots can be used to compare the general characteristics of large datasets. These were produced in order to compare the distributions of our RNAseq data between treatments but also between strains (Figure  2 ). The median read number per CDS was above 1,000 (log value > 3).
Quantitative PCR on selected genes The reliability of our RNAseq data can be assessed by comparing the differential expression of a set of regulated genes using an alternative approach such as quantitative real time PCR (qPCR). The relative expression of five genes present in both studied microbial genomes was estimated using qPCR. Three genes presenting significant differential expression values after DESeq analyses in our RNAseq data (genes encoding for a metal-translocating P IB -type ATPase: MESS2v1_740030 / MESS4v1_360013, a periplasmic binding protein of the ABC-type transporter: MESS2v1_300037 / MESS4v1_520016, and a putative Signal peptidase II: MESS2v1_740019 / MESS4v1_360023 in STM 2683 / STM 4661, respectively) were chosen and analyzed using two reference genes (recA and glnA) whose expression was unaltered by metal treatment.
9 was found for both isolates when plotting the log2 (Metal / control) values obtained for the five selected genes using the genomewide RNAseq approach against the qPCR data (Additional file 7C and F). Differences in the amplitude of the deregulation between the two techniques could be attributed to the PCR step used to amplify libraries prior to Illumina sequencing or to differences resulting from the mRNA purification procedure. Nevertheless, the high correlation between the two approaches shows that RNAseq data can be used to assess the global gene expression levels in our Mesorhizobium strains and more particularly to identify the genes specifically induced or repressed by Zn or Cd. To estimate the biological variance of our data, the relative expression ratios of the same target genes were also studied by qPCR in STM 2683, using total RNA isolated from independent biological replicates as starting materials, and the ratios were compared to the results obtained using pooled RNA samples (Additional file 8).
Identification of genes regulated by metals in Mesorhizobium strains STM 2683 and STM 4661 Transcriptional profiles obtained using the genome-wide RNAseq approach was performed on pooled samples. The high reproducibility between treatments, as exemplified by the high correlation factors of read counts and relative expression values of the RNAseq datasets allowed us to obtain adjusted p-values (FDR) with DESeq. Putative CDS presenting FDR values < 0. 1 in a "Metal" vs "Control" experiment are listed in Tables  4  and 5  for STM 2683 and STM 4661, respectively. A total of 72/6,844 and 68/6,994 putative CDS (or 1. 05% and 0. 97% CDS for STM 2683 and STM 4661, respectively) were found to be significantly differentially expressed by one or both metals for STM 2683 and STM 4661, respectively. These putative differentially expressed CDS are classified into six categories: transport, sequestration, regulation, oxidoreduction, others and unclassified.
These products were then purified on a gel to select a size range at 200 pb and enriched by PCR to create the final cDNA library. The efficacy of the library construction was checked in a quality control step that involved measuring the adapter-cDNA size and concentration on an Agilent DNA 1000 chip. Sequencing libraries were denatured with sodium hydroxide and diluted to 6 pM in hybridization buffer for loading onto a single lane of an Illumina HiSeq 2000 flowcell V1. 5. Cluster formation, primer hybridization and single-read, 36 sequencing cycles were performed on cBot and HiSeq2000 (Illumina, San Diego, CA) respectively. After sequencing, the sequences or reads that passed the quality filter were mapped on the annotated genomic objects identified in the genomes of STM 2683 and STM 4661 using ssaha2 software  [55].
PCR efficiency (E) for each amplicon was calculated using the linear regression method on the log (fluorescence)per-cycle-number data using Stratagen MXpro software. All qPCRs were performed in three technical replicates using either total pooled RNA used for RNAseq (two replicates for each mesorhizobial strain) or total RNA isolated from three biological samples prior to pooling so as to estimate biological variability (three replicates on STM 2683). Data for each sample were expressed relative to the expression levels of recA or glnA by using the mathematical model described previously, which determines the relative quantification of a target gene in comparison to a reference (ref) gene between treatment and control samples  [57]. The relative expression ratio (R) of a target gene is calculated based on efficiency (E) and the threshold cycle (Ct) of an unknown sample versus a control and expression in comparison to a reference gene.
The average relative quantity for each gene under study was calculated and log2-transformed. Means and standard deviations of these final log2 ratios were calculated using data from three technical replicates. Mean comparison was performed with a multiple comparison of Conover-Iman, using XLSTAT software, to determine significant differences in gene expression levels between inducible genes and reference genes and to determine significant differences between the metal treatments (Cd or Zn condition) and the control metal-free treatments.
The plates were incubated at 28°C with shaking at 450 rpm. OD 600nm and fluorescence (excitation filter at 485 nm and emission filter at 535 nm) were recorded 48 hours post inoculation using a spectrofluorometer plate reader (TECAN Infinite M200). Three transcriptional assays were performed for each bacterial strain carrying the promoter-gfp fusion or the promoter-less vector. For the analysis, optical density and fluorescence data were first corrected with the values obtained from the media. Corrected fluorescence values were then normalized to the average OD 600nm at each time point.
Acknowledgments This work was supported by the  Agence Nationale de la Recherche  Programme « Contaminants, Ecosystèmes et Santé » (CES 2008-12, APTITUDE). G. M. , received a PhD grant from the  Ministère de la Recherche et de l'Education Nationale. We thank  Dr. Klonowska A. and  Dr. Cartieaux F. for help in qPCR assays.
Genotyping Genomic DNA was obtained from all subjects enrolled in the study. We then obtained the genotypes for 31 SNPs that span approximately 320 kb of genomic DNA in the promoter region, exon 1 and intron 1 of PARK2. Based on the tag SNP information available from the International HapMap project database (www. hapmap. org/) for the Chinese population, which we know to strongly resemble the Vietnamese situation, these SNPs represent over 80% of the common genetic information of the target region. These SNPs were genotyped on the high-throughput SEQUE-NOM MassARRAY platform, which uses the iPLEX assay to incorporate mass-modified terminal nucleotides in the SBE step, which are then detected by MALDI-TOF MS  [30]  or the ultrahigh throughput Illumina platform. This platform uses the GoldenGate assay followed by a bead-based technology to resolve individual SNP genotypes  [31].
Human cytokine ELISA Macrophages were seeded into 24-well plates at a density of 5610 5 cells per well and Schwann cells at a density of 5610 4 cells per well. Cells were treated with stimuli for 6-24 hours; the supernatants were collected, cleared by centrifugation and assayed using Milliplex MAP 42-plex human cytokine kit on a Milliplex Analyzer 3. 1 Luminex 200 machine (Millipore, Chicago, IL) according to the manufacturer's instructions. Alternatively, supernatants were analyzed using custom Q-Plex chemiluminescent multiplex ELISA arrays measuring human IL-1b, IL-6, IL-8, IL-10, MCP-1 and TNF (Quansys Biosciences, Logan, UT). Array images were acquired and analyzed using the Quansys Q-View imager and software.
Statistical analysis The expression levels of IL6 and CCL2 in M. leprae sonicate stimulated and non-stimulated whole blood assays for all 62 subjects were used as quantitative traits in an eQTL analysis. Association between expression levels of CCL2 and IL6 and SNP alleles in PARK2/PACRG was tested by means of the Likelihood Ratio Test as implemented in the GENMOD procedure of the SAS software version 9. 2 (SAS Institute, Cary, NC, USA) and assuming a dominant genetic model since this is the model providing best evidence of association with leprosy  [32]. Due to the known strong impact of gender on leprosy risk, we adjusted the analysis for sex of subjects.
Image Acquisition and Data Analysis Images were acquired with a Nikon Eclipse Ti using a plan Apochromatic 3100 oil-immersion objective with a 1. 4 numerical aperture. A Nikon Intensilight C-HGFI lamp was used to illuminate the coverslips. Dichroic filters for Cy3 (Semrock Cy3-4040B) and DAPI (Semrock DAPI-1160A) were used. Stacks of 51 Images were acquired in z-steps of 0. 2 mm using a Photometrics Coolsnap HQ 2 camera. Images were analyzed z-step by z-step fitting a two-dimensional Gaussian to detect FISH spots and to extract integrated intensity, as previously described  (Thompson et al. , 2002; Zenklusen et al. , 2008). Only the signal measured at the focal plane for each detection was used for statistical analysis. The number of nascent transcripts at the TS was estimated by dividing the integrated intensity at the TSs by the median integrated intensity of the spots in the same image.
ACKNOWLEDGMENTS We thank  Daniel Larson  and  Robert H. Singer  for sharing algorithms,  J. Boulay  for technical assistance,  A. Aguilera  and  C. Cullin  for the gift of yeast strains, and  T. H. Jensen  and  F. Stutz  for critical reading of the manuscript. This work was supported by the  CNRS  (to D. L. ), the  Danish National Research Foundation  (to D. L. ), and the  ANR  ( ANR-08-Blan-0038-01  to D. L. and  ANR   2010-blan-1222-03  to X. D. ). S. C. was supported by the  Association pour la Recherche sur le Cancer. This research was carried out within the scope of the  Associated European Laboratory LEA Laboratory of Nuclear  RNA.
For some experiments, protein shape was visualized in samples measured at 12% contrast (12% D 2 O). For these studies, the scattering intensity of the protein was enhanced by preparing nHDL with deuterated apoA1. Both SANS at multiple levels of contrast and mass spectrometry studies independently confi rmed that 70% of the nonexchangeable H atoms were substituted by D atoms during protein expression in D 2 O with deuterated nutrients, which corresponds to a level of contrast of 92% D 2 O. Using this information, calculations indicate that, under the conditions employed, the lipid phase (both head groups and acyl chains) contributed <7% of the intensity across all scattering angles examined in the 12% contrast experiment (supplementary Fig. I  ). We established this value by calculating contributions to intensity coming from the protein and lipid using a modifi cation of the SASSIM program  ( 39 ).
25 UltraMicro Tip Columns (Nest Group, Southborough, MA). The samples were prepared for SCX chromatography by adding acetonitrile (5% v/v fi nal) to the cross-linked peptide solution and adjusting to pH 3. 0 with H 3 PO 4 prior to being loaded onto the columns. The column was washed with PBS, pH 3. 0 and eluted with 5% acetonitrile, 20 mM sodium phosphate buffer, pH 3. 0 with steps of 300 and 500 mM NaCl. A FASTA database of potential cross-linked peptides of apoA1 was generated using the program xComb v1. 3  ( 40 ). The Uniprot FASTA for apoA1 was used as the input fi le and the parameters for the database generation included two potential missed cleavages, both intra-and interprotein cross-links, amine to amine cross-linker, no missed cleavage necessary, and a minimum peptide length of four amino acids.
The samples were measured at 6-8°C in 12% ( q range 0. 005-0. 304 Å Ϫ 1 ) and 42% D 2 O solution ( q range 0. 007-0. 453 Å Ϫ 1 ). The radius of gyration (R g ) was obtained based on the Guinier approximation ( 36 ) from the corresponding scattering curves. The SANS data collected were processed as follows. The program GNOM  ( 37 )  was used to deconvolute the scattering intensity curves into the distance distribution function P(R ). Subse quently, the program DAMMIN  ( 38 )  was used to produce low-resolution models (n = 32) of the protein component from the P(R) function obtained for the sample measured in 12% D 2 O ( q range 0. 005-0. 256 Å Ϫ 1 ). The P(R) function obtained from the 42% D 2 O scattering intensity curve ( q range 0. 007-0. 453 Å Ϫ 1 ) intensities calculated with CRYSON ( 42 ) matched the experimental data.
Atom clashes in the all-atom model, which resulted from manual adjustment of chain residues and individual lipid molecules, were removed by performing a short geometry optimization in vacuum. The CHARMM22 force fi eld was used for protein  ( 43 ) , and CHMARMM27 for lipids  ( 44 ). The vacuum model of nHDL DMPC was further solvated in a box of TIP4P water molecules  ( 45 ) , with walls 15 Å away from the particle. Sodium ions were added to compensate the negative charge of the two apoA1 chains, and then NaCl ion pairs were inserted to obtain a physiological salt concentration of 344 milliosmolar (standard PBS buffer). The solvated system was energy minimized [using the program GROMACS  ( 46 ) ]. The protocol for geometry optimization was as follows: the lipoprotein particle relaxed gradually (fi rst the solvent, then the lipid, and fi nally the protein).
Electron microscopy studies Negative stained nHDL samples (dilution 1:300) were obtained by applying them to the clear side of the carbon-mica interface and staining with 2% (w/v) uranyl acetate. Images were recorded under low-dose conditions with a CM12 (Philips) electron microscope equipped with an LaB6 fi lament and working at 120 kV. Images have been recorded on an Orius SC1000 CCD camera (Gatan Inc. ). The experimental SANS intensities, the Protein Data Bank fi les of the SANS shapes for the protein and lipid components of nHDL examined, and the all-atom Turtle model of nHDL DMPC can be downloaded from the site http://www. lerner. ccf. org/ cellbio/hazen/data /.
Biochemical characterization of nHDL preparations formed using native human apoA1 and perdeuterated human apoA1 Reconstituted nHDL particles generated for SANS analyses in the present study were prepared with either isolated human apoA1 or recombinant human perdeuterated apoA1, as described under Materials and Methods. Before collect in a data-dependent mode and analyzing the data using the xComb FASTA database in Proteome Discoverer 1. 1 (Thermo Scientifi c) to fi nd precursor masses of potential cross-links. Observed monoisotopic masses within 5 ppm of the theoretical mass of cross-linked peptides of interest were collated into a "parent list" and the Orbitrap MS was programmed to specifi cally search for the peptides in this list and perform CID MS/MS on the specifi c peptides. The subsequent MS/MS analyses using the parent list utilized the same chromatographic method as detailed above in the screening experiment.
Computational modeling of nHDL DMPC In earlier SANS with contrast variation studies  ( 15, 27 )  we matched computational models of HDL at multiple contrast levels (0, 12, 42, and 90% D 2 O) and established that two contrast levels (12 and 42% D 2 O) are suffi cient to produce a consistent model for the entire particle. Thus, thirty-two low-resolution structures obtained from the 12% contrast SANS dataset were averaged, and the SANS shape closest in features to the average shape (reference shape) was further used for modeling. The allatom model of nHDL DMPC was constructed by separately fi tting an all ␣ -helix apoA1 dimer into the reference low-resolution shape envelope, and by packing 160 DMPC molecules into the low-resolution structure of the lipid component (42% contrast SANS dataset, that was similarly averaged, and reference shape used for modeling).
Following energy minimization, the crude proposed three-dimensional model obtained for the apoA1 chains within nHDL DMPC is shown in Fig. 4B  (stereo views in supplementary Fig. IV ), and its superposition onto the lowresolution structure of apoA1 is given in Fig. 4C. It should be noted that this hypothetical exercise was done not to claim that this was the precise structure of apoA1 within nHDL DMPC , but rather, to help build a model that displayed overall architecture that matched the experimental data collected by the SANS studies, and would then likely also match previously reported MS cross-linking, ESR, and FRET data on reconstituted nHDL particles  ( 11, 12, 15, 21, 22 ). To assess the goodness of fi t of the protein component of the Turtle model with the experimentally determined.
SAR acquisitions may then be used, together with an electromagnetic backscattering model (EBM) able to simulate the reflectivity of a snowpack from a set of physical descriptors, in order to constrain a physical snowpack model. In this study, we introduce a variational data assimilation scheme coupling TerraSAR-X radiometric data into the snowpack evolution model Crocus. The physical properties of a snowpack, such as snow density and optical diameter of each layer, are simulated by Crocus, fed by the local reanalysis of meteorological data (SAFRAN) at a French Alpine location. These snowpack properties are used as inputs of an EBM based on dense media radiative transfer (DMRT) theory, which simulates the total backscattering coefficient of a dry snow medium at X and higher frequency bands.
After evaluating the sensitivity of the EBM to snowpack parameters, a 1D-Var data assimilation scheme is implemented in order to minimize the discrepancies between EBM simulations and observations obtained from TerraSAR-X acquisitions by modifying the physical parameters of the Crocus-simulated snowpack. The algorithm then re-initializes Crocus with the modified snowpack physical parameters, allowing it to continue the simulation of snowpack evolution, with adjustments based on remote sensing information. This method is evaluated using multi-temporal TerraSAR-X images acquired over the specific site of the Argentière glacier (Mont-Blanc massif, French Alps) to constrain the evolution of Crocus. Results indicate that X-band SAR data can be taken into account to modify the evolution of snowpack simulated by Crocus.