dataesr/scientific-paragraphs-categorization huggingface dataset:
We would also like to thank  Dean Hegg  for advice on aerosol sampling,  Angela Hong  and  Jennifer Murphy  for helpful discussions about NO y vertical gradients, and  Chad Mangum  for laboratory assistance at  USU. We thank  Sarah Doherty  for the use of the ISSW spectrophotometer and  Stephen Warren  for graciously allowing M. C. Zatko  to borrow snow sampling instruments and gear and providing comments about this work. We thank  Jonathan Raff  for helpful discussions about soil microbial activity as well as  Joost de Gouw  and  Gail Tonnesen  for useful discussions about boundary layer HONO. Finally, we thank  Lyatt Jaeglé ,  Joel Thornton , and  Thomas Grenfell  for their helpful comments. Joel Savarino  and  Joseph Erbland  have been partly supported by a grant from  Labex OSUG@2020  (Investissements d'avenir - ANR10 LABX56 ) during the development of the TRANSITS model.
Acknowledgments The authors thank  U. Haisch ,  W. Shepherd ,  F. Sala  and  J. Silk  for discussions and  S. Profumo  for helpful comments on this manuscript. FD thanks  J. Silk  for his kind hospitality at the  Institut d'Astrophysique de Paris  where part of this work was completed. PP thanks  S. Profumo  for his kind hospitality at  UC Santa Cruz , where this work was initiated. FD is supported by the  U. S. Department of Energy  grant number  DE-SC0010107  (FD). P. P. acknowledges support of the  European Research Council  project  267117  hosted by  Université Pierre et Marie Curie -Paris 6,  PI J. Silk. BJK is supported by the  John Templeton Foundation  Grant  48222  and by the  European Research Council (Erc)  under the  EU   Seventh Framework Programme  (FP7/2007-2013)/ Erc Starting Grant  (agreement n.
Phylogenetic and Structure Prediction Analyses Tric1 (At3g49560) and Tric2 (At5g24650), also known as HP30-1/HP30-2  (Rossig et al. , 2013) , PRAT2. 1/PRAT2. 2 (Pudelski et al. , 2010) , and PRAT3/ PRAT4  (Murcha et al. , 2015) , were selected for investigation. The presence of a PRAT domain (PF08294) and a SAM domain (PF00536) was identified using the Conserved Domains Database  (Marchler-Bauer et al. , 2011). Plant orthologs to Tric1 and Tric2 were identified by sequence homology using BLASTN  (Altschul and Koonin, 1998)  within each database representative of each evolutionary clade using Phytozome 9. 1  (Goodstein et al. , 2012)  from Physcomitrella patens, Selaginella moellendorffii, Zea mays, Oryza sativa, Solanum tuberosum, Vitis vinifera, Eucalyptus grandis, Brassica rapa, Capsella rubella, Medicago truncatula, Glycine max, Ricinus communis, Populus trichocarpa, Cucumis sativus, Volvox carteri, and Chlamydomonas reinhardtii.
Potential orthologs in nonplant genomic databases of Cyanidioschyzon merolae, Dictyostelium discoideum, Homo sapiens, Caenorhabditis elegans, Saccharomyces cerevisiae, Ectocarpus siliculosus, and Neurospora crassa also were searched, with no orthologs identified. All identified orthologs were further manually curated to exclude proteins with a similarity threshold above 1e 240 so as to confirm specific Tric orthologs and exclude orthologs to the other PRAT family members  (Murcha et al. , 2015). Protein alignments were performed using Clustal  Omega (www. ebi. ac. uk; Sievers et al. , 2011)  and drawn using BOXSHADE (http://www. ch. embnet. org/software/BOX_form. html). Transmembrane domains were identified using TMHMM  (Krogh et al. , 2001). Phylogenetic analysis was carried out and drawn using MEGA 5.
Protein Uptake Assays Mitochondrial protein import assays were carried out according to  Duncan et al. (2015). To investigate the intramitochondrial location of precursor proteins such as Tim23-2  (Murcha et al. , 2003) , OMT (GenBank accession no. X99853. 1; Murcha et al. , 2004) , and Tim22  (Murcha et al. , 2003) , outer membrane ruptured mitochondria were prepared following the import reaction and prior to the addition of PK as described previously  (Murcha et al. , 2005b). For large-scale in vitro import experiments for analysis by BN-PAGE, 250 mL of mitochondria was incubated in 360 mL of the import master mix with 50 mL of 35 S-labeled precursor protein. Chloroplast protein uptake assays were carried out as follows: 30 mg of protein was incubated in import buffer (3 mM ATP, 10 mM Met, 10 mM Cys, 20 mM potassium gluconate, 10 mM NaHCO 3 , 3 mM MgSO 4 , 330 mM sorbitol, 50 mM HEPES-KOH, pH 8, 0.
RNA-Seq Analysis RNA-seq data were analyzed using the TopHat/Cufflinks pipeline (version 2) by estimating transcript abundances in fragments per kilobase of exon per million fragments mapped values  (Trapnell et al. , 2012). The TAIR10 genome assembly was used for read mapping, and significant differential expression for all genes in the Arabidopsis genome was determined with FDR , 0. 05. For all genes, fold changes are presented as log 2 fold change values.
Accession Numbers Sequence data from this article can be found in the Arabidopsis Genome Initiative under the following accession numbers: Tric1 (At3g49560), Tric2 (At5g24650), Tim23-2 (At1g72750), Tim17-2 (At2g37410), Tim22 (At3g10110/ At1g18320), RISP (At5g13430), MPP-a (At3g16480), and tRNA Ala (At3g62245). Sequencing data are available from the National Center for Biotechnology Information Gene Expression Omnibus database under accession number GSE76287.
1 This work was supported by the  Australian Research Council  ( Future Fellowship Grant  no. FT130100112  and  Discovery Grant  no. DP150100293  to M. W. M. and  Discovery Grant  no. DP130102384  to J. W. ); by the  French National Program Investissement d'Avenir  administered by the  Agence Nationale de la Recherche  (grant no. ANR-10-IDEX-0002-02 ), the  University of Strasbourg , and the  Centre National de la Recherche Scientifique ; by the  Deutsche Forschungsgemeinschaft  ( Heisenberg fellowship  no. PH73/6-1  to K. P. ); and by the  Swedish Foundation for International Cooperation in Research and Higher Education  (to E. G. , J. W. , and M. W. M. ).
Monitoring of biofilm development in a flow-cell model Monitoring of biofilm development by K. pneumoniae CH1034 in a flow-cell system with confocal microscopy showed initially the formation of microcolonies leading to the development of a flat structure after 7 h of incubation (T 7h ) (Additional file 1: Movie S1). At T 9h , a three-dimensional structure was observable and potential detachment from this mature biofilm was then assessed. Bacteria in the flow-cell effluent were harvested throughout the experiment, and CFU determination of the resulting suspensions indicated that the number of viable cells decreased in the first 3 h of the experiment, from 5. 10 6 CFU/mL (T 1h ) to 1. 10 5 (T 3h ), owing probably to the elimination of planktonic non-adhering cells (Fig. 1a ). Observation of the harvested samples by optical microscopy revealed mainly individual bacteria (data not shown).
pneumoniae, as well as 19 of the 44 annotated ncRNA genes (excluding tRNA and rRNA genes), were differentially expressed in at least one of the ten possible pairs of conditions (|fold-change| > 5 and adjusted P-value < 0. 01) (Fig. 2a ), with fold-changes ranging from -2 780 to 2 182 (Additional file 2: Table  S1 ; Additional file 3: Table  S2 ). To validate the RNA-seq efficiency, 20 genes differentially expressed between the 13 hold biofilm bacteria and the bacteria collected in the effluent (10 genes overexpressed and 10 genes underexpressed; P-value < 0. 01) were randomly selected. Their relative expression levels were determined by RT-qPCR with total RNA extracted from cells harvested in two conditions: bacteria in the effluent and 13 h-old biofilm. Results indicated a high correlation between RNAseq and RT-qPCR data (r = 0.
97; P-value < 0. 0001; Pearson's correlation test) (Additional file 4: Figure  S1 ). PCA performed with Z-score values of the 2 052 CDS and 19 ncRNA genes indicated that the first principal component (PC1) accounted for 36. 52 % and the second principal component (PC2) for 27. 88 % of the total variation in the dataset (Fig. 2b ). A plot of these Z-score values against a heatmap (Additional file 5: Figure  S2 ) and the proximity of points in the PCA (Fig. 2b ) demonstrated the high reproducibility of the data among the replicates. In addition, such analysis clearly indicated that all bacterial states (planktonic, sessile and bacteria in the effluent) exhibited specific transcriptional profiles (Fig. 2b  and Additional file 5: Figure  S2 ), and suggests that bacterial cells in the effluent are not pieces of biofilm mechanically detached from the biomass.
pneumoniae lifestyles through K-means clustering K-means clustering was then used to visualize the distribution of the expression levels of the 2 052 CDS and the 19 ncRNA genes differentially expressed (|fold-change| > 5 and adjusted P-value < 0. 01) in the different conditions (Fig. 3a  and b ). Owing to the high reproducibility of data, Z-score values were able to be calculated with average values from normalized DEseq counts. This clustering indicated that the clearest representation was obtained with K = 10 for the CDS analysis and K = 5 for the ncRNA genes analysis, and showed different transcriptomic profiles between conditions. In Fig. 3a , with clusters ranging from 76 to 499 CDS for clusters 8 and 10 respectively, column clustering confirmed that dispersed cells were transcriptionally closer to 7 h-old biofilm cells than to those in all the other conditions, whereas stationary phase cells were the most different group of this dataset.
GFP-tagged strain construction The K. pneumoniae CH1034 GFP-tagged strain was constructed after replacement of the SHV-1 β-lactamaseencoding gene (chromosomal ampicillin resistance) by the selectable aadA7-gfpmut3 cassette. Briefly, the aadA7-gfpmut3 cassette flanked by 60-bp fragments, which correspond to the encoding upstream and downstream regions of shv, was generated using pKD4 plasmid as template, primers shv-GFP-Fw and shv-GFP-Rv and Phusion high-Fidelity DNA polymerase (Thermo Fisher Scientific, Waltham, Massachusetts, USA) according to the manufacturers' recommendations. Primers were designed on the basis of information about the K. pneumoniae CH1034 genome sequence previously deposited in the ENA/EMBL-EBI database under the accession number: PRJEB9899  [50]. The PCR fragment was then transformed by electroporation into the 0.
7. 12-r1039)  [53] , which allows a maximum of two mismatches within the first 32-bp. Counting was performed with the software HTSeq-count using the union mode. As data come from a strand-specific assay, the read has to be mapped to the reverse strand of the gene. Analysis of the reads mapped to intergenic regions confirmed the overall quality of the genome annotation and therefore strengthen the choice to focus on CDS and ncRNA features. Differentially expressed CDS and ncRNA genes between any pair comparisons of the five groups were determined by a negative binomial test with the DESeq package of R/Bioconductor. Transcripts were considered as differentially expressed using the following criteria: Pvalue < 0. 01 and |fold-change| > 5. Transcriptome sequencing data were deposited in the Gene Expression Omnibus (GEO) database under the GEO accession number: GSE71754.
Primers were designed on the basis of K. pneumoniae CH1034 genome sequence information  [50]  and are listed in Additional file 8: Table  S3. Melting curve analysis was used to verify the specific single-product amplification. The gene expression levels were normalized relative to the expression levels of the cpxR housekeeping gene and relative quantifications were determined with CFX Manager software (Bio-Rad) by the E(-Delta Delta C(T)). The amplification efficiency (E) of each primer pair used for the quantification was calculated from a standard amplification curve obtained by four dilution series of genomic DNA. All assays were performed in technical triplicates with three independently isolated RNA samples.
The clearest representation for each condition of the dataset was obtained with K = 10 for CDS clustering and K = 5 for ncRNA genes clustering. To highlight groups of CDS highly overexpressed or under-expressed in a specific condition, the mean of the Z-scores in each cluster was calculated for each condition, and the Z-score groups presenting a mean value > 1 or < -1 were named overexpressed boxes and under-expressed boxes, respectively. The most relevant signature genes in the dataset were extracted using two fold-change thresholds, the Identity Threshold Fold-Change and the Differential Threshold Fold-Change. These thresholds were modulated as described in Figure  S4  (Additional file 7) to obtain the most stringent signature genes for each condition. analysis and GEO submission. We thank Sylvie Miquel for helpful discussion and critical reading of the manuscript.
Statistical analysis Continuous variables are described as median (interquartile range) and categorical variables in percent (%). Comparisons between groups were made using the Mann-Whitney or the Kruskal-Wallis test for continuous data, and the χ 2 test for categorical variables. Statistical analyses were done with the use of Prism 6. 05 Software (GraphPad Software Inc, La Jolla, CA). P-values 0. 05 were considered significant. The inter-observation variability for histological analysis was assessed by calculating the weighted kappa coefficient between two blind readings. Microarray data analyses were performed blind to clinical data using R software version 3. 0. 1. Raw data were quantile normalized via the Limma package:  [12]  first background subtraction, then log2 transformation and quantile normalization were applied.
A gene was considered as differentially expressed 1) when a comparison between two groups yielded a P-value 0. 05 in the student parametric test and 2) a variation of at least 1. 3-fold was observed. Fold-change was raised to 1. 5 for the comparison between Rejection and Control groups in order to restrict the number of probes differentially expressed. Hierarchical clustering was performed on scaled gene expression based on the Euclidean distance and the Ward's linkage method. Canonical pathways and biological functions associated with differentially expressed genes were identified using Ingenuity Pathway Analysis software (IPA 1 , Qiagen, Redwood City, www. qiagen. com/ingenuity). Linear Discriminant Analysis (LDA) was further performed using the 'MASS' package with the intention of predicting EMB histological features from their individual gene expression levels.
White arrows with solid outlines indicate unknown function, and white arrows with broken outlines indicate other functions (these genes of A. vinosum and S. thiotaurini do not have a homologue in the C. orbicularis symbiont's nif cluster). Sequence similarities are symbolized by red hues for direct comparisons and blue hues for reversed comparisons. Darker colours correspond to higher identities. For protein functions see Supplementary Table  3. *Identified as a protein in this study. Sequence data and the BLAST comparison files were drawn with the R package genoPlotR (ref. 57) and edited in Inkscape. The production of ethylene as a consequence of acetylene reduction by the nitrogenase enzyme complex was measured in gill tissue samples from freshly collected C. orbicularis specimens, in purified gill symbionts, in symbiont-free foot tissue, in the water column and in T.
'Ca. T. endolucinida' COS (this study) is shown in bold. Orange dots denote known diazotrophic sulfur oxidizers. (Note that no information regarding potential thiotrophy is available for the uncultured seagrass bed isolates. Some of these clones might be sulfur oxidizers, although they are not marked with orange dots. ) Accession numbers or locus tags in parentheses refer to the International Nucleotide Sequence Database Collaboration (INSDC). The sequence marked with an asterisk was only available as a nucleotide sequence and was translated for this analysis (frame 3). The NifH sequences of Anabaena variabilis ATCC 29413 (AAA93020) and Frankia alni ArI3 (AAA96262) were used as outgroup (shown in Supplementary Figure  4d ). thiotrophic lucinid symbionts and seagrass sediment bacteria has been suggested previously  23, 43.
Gene cluster comparison. All genes in the nif gene cluster of 'Ca. T. endolucinida' COS (CODIS_20190-20650, Fig. 1 ) were compared to the genomes of Allochromatium vinosum DSM 180 (NC_013851) and Sedimenticola thiotaurini SIP-G1 (NZ_CP011412) using Bl2seq (BLASTn, E-value 1e-5). Sequence data and the BLAST comparison files were drawn with the R package genoPlotR version 0. 8. 4  (ref. 57) and edited in Inkscape version 0. 91. Blast results were automatically edited, so that short hits contained in longer hits were removed. They were further curated manually, so that each of the 'Ca. T. endolucinida' genes matched only one gene in its relatives. Proteomic analyses. Mass spectrometry (MS) analyses of C. orbicularis symbiont proteins were performed in two parallel approaches: (1) in an identification-centred (that is, qualitative), gel-based approach and (2) in a quantitative gel-free approach (see section 'Gel-free protein quantification').
Peptides were eluted from the gel pieces in a sonication bath and purified using ZipTips (Millipore) according to the manufacturer's recommendations. As described previously  60  , peptide mixes were subjected to separation using reversed-phase C18 column chromatography on a nanoACQUITY-UPLC system (Waters). Mass spectrometry (MS)-and tandem mass spectrometry (MS/MS) data were acquired using an online-coupled LTQ-Orbitrap mass spectrometer (Thermo Fisher Scientific). MS spectra were searched against a target-decoy protein sequence database including all sequences from the C. orbicularis symbiont database (see 'Genome sequencing and genomic analysis' section) and common laboratory contaminants using the SEQUEST Sorcerer platform (Sage-N). Scaffold (version 4. 2, Proteome Software) was used to validate MS/MS-based peptide and protein identifications using the XCorr-based filter settings described previously  61.
Samples were stored at -80 °C until MS analysis. Peptide mixtures were analysed using the nanoACQUITY-UPLC system (Waters), coupled to a Synapt G2 mass spectrometer (Waters), equipped with a NanoLockSpray source in positive mode. The analyser was set to resolution mode and operated with ion mobility separation as described by Huja and co-authors  63. The ProteinLynx Global Server (PLGS) 2. 5. 3 was used for processing raw data and carrying out the database searches against the randomized C. orbicularis symbiont database with added common laboratory contaminants and the bovine haemoglobin sequence  63. Proteins were considered identified if they were detected in one of the respective technical or biological replicates with a minimum of two peptides at a maximum FDR of 5% on the protein level.
Some of these NifH sequences  71  were only available as nucleotide sequences and were therefore translated using EMBOSS Transeq  73  and the correct reading frame was selected manually. Four additional NifH protein sequences from known thiotrophs and two sequences from the outgroup taxa Anabaena variabilis ATCC 29413 (NifH: AAA93020) and Frankia alni ArI3 (NifH: AAA96262) complemented the data set, giving a total of 1,114 sequences for the NifH-based phylogenetic analysis. Sequence entries from the PDB and PRF databases as well as sequences containing stop codons or ambiguous amino acids (X) were removed, leaving 1,073 sequences that were clustered at 100% identity with CD-HIT (refs 74,75) to remove redundancies. All 834 representative non-redundant sequences (93 full length, 741 partial length) were automatically aligned with MAFFT version 7.
221 (2014/04/16)  76  using the L-INS-i algorithm and the 'leave gappy region' option. The alignment was imported into ARB version 5. 5 (ref. 77) using a custom filter, and a protein database was created. A total of 55 full-length amino-acid sequences were selected and exported. ProtTest version 3 (refs 78,79) was employed to select the best-fit model of aminoacid replacement from 120 models (15 matrices: +G, +I or + G+I; +F) with a starting topology based on maximum likelihood. As the Bayesian information criterion (BIC; also known as the Schwarz criterion, or SC)  80  , the corrected Akaike information criterion (AICc)  81, 82  and the decision theory framework (DT)  83  favoured LG+I+G, the phylogeny was then inferred using RAxML version 8. 2. 4 (ref. 84) with the LG amino acid matrix  85  , a gamma model of rate heterogeneity and an estimate of proportion of invariable sites.
The best tree was chosen from 1,000 independent inferences that were executed on the original alignment (169 alignment patterns) using 1,000 distinct randomized maximum parsimony (MP) trees and was imported into ARB version 6. 0. 3. All 741 partial length NifH sequences were added by ARB's interactive parsimony. Sequences that could not be unambiguously inserted at a specific position in the tree were removed. To identify the partial length NifH sequences with the highest identity to the full-length sequences, a BLAST+ (ref. 86)  protein database of all partial sequences was created and the full-length sequences that had partial sequences assigned by parsimony were searched against this database using BlastP version 2. 2. 31+. For each full-length sequence, only the best matching partial sequence (that is, the one with highest identity) was kept in the tree, and only if sequence identity between both was 95% or higher.
Note that the uncultured clones from seagrass and mangrove sediments (dotted branches in the NifH tree) are not included in the NifD and NifK trees, because no NifD or NifK sequence information was available for these isolates. 16S rRNA phylogeny. The 16S rRNA-coding region of the 'Ca. T. endolucinida' genome was identified using barrnap version 0. 6 (available from https://github. com/ tseemann/barrnap) and automatically aligned against the SILVA SSU Ref NR 99 Release 123 database (available from http://www. arb-silva. de)  87 using the SILVA Incremental Aligner (SINA) version 1. 2. 11 (ref. 88). The SINA-aligned sequence was imported into the ARB software package version 5. 5 (ref. 77). Besides the C. orbicularis symbiont's 16S ribosomal RNA nucleotide sequence and its closest homologues (by NCBI blastn), the data set contained additional 16S rRNA sequences of bivalve and gastropod symbionts, free-living sulfur oxidizers and some diazotrophic bacteria, whose NifH sequences were also included in the NifH tree.
orbicularis symbiont 'Candidatus Thiodiazotropha endolucinida' COS see Supplementary Table5. 'Ca. T. endolucinida' COS (this study) is shown in bold. Orange dots denote known diazotrophic sulfur oxidizers. (Note that no information regarding potential thiotrophy is available for the uncultured seagrass bed isolates. Some of these clones might be sulfur oxidizers, although they are not marked with orange dots. ) Accession numbers or locus tags in parentheses refer to the International Nucleotide Sequence Database Collaboration (INSDC). The sequence marked with an asterisk was only available as a nucleotide sequence and was translated for this analysis (frame 3). The NifH sequences of Anabaena variabilis ATCC 29413 (AAA93020) and Frankia alni ArI3 (AAA96262) were used as outgroup (shown in Supplementary Figure4d).
model Fer4_NifH (PF00142, available from http://pfam. xfam. org/family/PF00142/hmm) against all annotated proteins of the C. orbicularis symbiont's draft genome with hmmsearch (Expect value 1e-10) from HMMER version 3. 1b2 (ref. 67). Its sequence was subsequently searched with HMMER's phmmer (Expect value 1e-10) against a local version of NCBI's nr database.