dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements. Adrien Vu Van  acknowledges funding from  SPACIA SA  through an  ANRT CIFRE doctoral grant. IASI is a joint mission of  EUMETSAT  and the  Centre National d' Etudes Spatiales (CNES, France). The IASI Level 1C data are distributed in nearreal time by  EUMETSAT  through the EUMETCast system distribution. The authors acknowledge the AERIS data infrastructure (https://www. aeris-data. fr, last access: 19 April 2023), for providing access to the IASI Level 1 radiance and Level 2 concentration data used in this study. Financial support. This research has been supported by the  French Association Nationale de la Recherche et de la Technologie  (grant no. 2019/0196 ). Review statement. This paper was edited by  Diego Loyola  and reviewed by  Santtu Mikkonen  and one anonymous referee.
Data availability. IASI L2 SO 2 , NH 3 , and CO data are available at https://doi. org/10. 25326/42 (Clarisse, 2019), https://doi. org/10. 25326/11 (Clarisse et al. , 2018), and https://doi. org/10. 25326/64  (Clerbaux et al. , 2020) , respectively. The volatile organic carbon (VOC) retrievals are processed by Franco Bruno (bruno. franco@ulb. be) and Lieven Clarisse (lieven. clarisse@ulb. be) at ULB and are available upon request.
The SEC columns (Shodex KW803 or KW804, 7 lm, 8 mm ID Â 300 mm, void volume $ 6 mL, total volume $ 12. 5 mL or Agilent BioSEC5-500 A, 4. 6 mm ID Â 300 mm, void volume $ 2 mL, total volume $ 5 mL) were equilibrated either with PBS (pH 7. 4, Gibco, Thermo Fisher Scientific) or HNGT buffer (5 mM TCEP). The flow rate ranged from 0. 2 to 0. 5 mL/ min. Data were processed with OmniSEC software (v5. 12, Malvern Panalytical) using RALS/ LALS detectors. The refractometer was used to determine the protein concentration and the refractive index increment value (dn/dc) used to determine the molecular weight (MW) was 0. 185 mL/g. Hydrodynamic radii were estimated with SEC protein standards (BEH200, Waters).
Nuclear magnetic resonance (NMR) 13 C/  15  N and 2 H/ 13 C/  15  N samples of DPCD were prepared as described above, except those bacteria were grown in aqueous or deuterated minimal M9 media supplemented with  15  NH 4 Cl and  13  C-d6-Glucose as sole nutrient source. The recombinant proteins were purified as described above, the final buffer being 10 mM NaPi, pH 6. 5, 300 mM NaCl, 5 mM DTT deuterated. 1 H-15 N TROSY-HSQC, 1 H-15 N NOESY-HSQC and triple resonance HNCA/trHNCA, HNCO, HNCACB/ trHNCACB and CBCACONH/trCBCACONH spectra were recorded at 298 K on 600 MHz and 950 MHz spectrometers equipped with cryoprobes. Data were processed with TopSpin-3. 0 (Bruker) and analyzed with CARA. 36 Assigned HN, N, CO, Ca and Cb chemical shifts were derived into secondary structures using TALOS-N. 37.
Isothermal titration calorimetry (ITC) Protein/protein interactions were characterized at 30 °C using a microcalorimeter (MicroCal iTC200, Malvern Panalytical) in HNGT buffer. DPCD was placed into the syringe at a concentration of 203 mM and 6 mM of R1/R2 hexamers were injected into the cell. Nineteen successive 2 mL injections were performed, except for the first injection which was only 0. 5 mL to prime the syringe. The rotation of the blade was set to 300 rpm. Data were processed with NITPIC  38  (v1. 2. 7) and NanoAnalyze (v3. 10. 0, TA instruments) software to determine the dissociation constant (K d ), the stoichiometry (n), and the thermodynamic parameters: enthalpy (DH), entropy (DS) and free energy (DG).
The trapping gas pressure was set to 7 a. u. (corresponding to an ultra-high vacuum of 1. 10 -9 mbar). To improve the transmission of the high MW species, the voltages on the injection-, inter-, and bent-flatapoles were set to 2 V. Acquisitions were performed in the m/z range 1,000-20,000 with a 3 s scan time and a resolution of 8,750 at 200 m/z with an automatic gain control (AGC) target set to 1. 10 6 and a maximum injection time set to 100 ms. External calibration was performed using singly charged ions produced by a 2 g/L solution of cesium iodide in 2-propanol/water (50/50 v/v). Orbitrap MS data were interpreted using BioPharmaFinder v3. 2 (Thermo Fisher Scientific, Bremen, Germany). Native IM-MS experiments were performed on a hybrid quadrupole/travelling wave ion mobility spectrometry (TWIMS)/time-of-flight mass spectrometer (Synapt G2 HDMS, Waters, Wilmslow, UK).
R1/ R2 and R1R2D were tested at a concentration of 1 mg/mL. Small-angle X-ray scattering (SAXS) experiments and de novo protein prediction SAXS data were obtained using SEC-SAXS on the SWING beam line at the French SOLEIL synchrotron (Saint-Aubin, France). Data were collected using an Eiger 4 M detector at a sampledetector distance of 2 m and at a wavelength of k = 1. 033 A (I(Q) vs Q, where Q = 4psinh/k, and 2h is the scattering angle), covering a Q-range of 0. 005-0. 5 A À1. SEC-SAXS was performed at 15 °C with a Bio SEC5-500 A HPLC column (4. 6 mm ID Â 300 mm, void volume $ 2 mL, total volume $ 5 mL, Agilent) equilibrated in HNGT buffer (5 mM TCEP) at 0. 3 mL/min. Fifty microliters of samples at 5-12 mg/mL were injected into the column. The data were collected through the SEC peak of the protein as a series of 1-s exposures.
Data reduction to absolute unit, frame averaging, and subtraction were performed with FOXTROT. Curves displaying a constant Rg, in a Rg versus frame number plot, were averaged and used for further characterization. Data were analyzed with the ATSAS suite  43  following the man-ufacturer's guidelines unless indicated otherwise. The MW was determined using the volume of correlation method. 44 Ten ab initio models were generated with GASBOR software, the models were aligned and averaged with DAMAVER software. The models shown are those with the lowest v 2 value. For DPCD, Tr-Rosetta  45  was used to predict de novo models. RoseTTAFold  46  and AlphaFold2 47 were also employed. The generated models were compared to SAXS data with CRYSOL. The model with the lowest v 2 value was selected for further processing and was subjected to normal mode analysis using SREFLEX  48  through the ATSAS online interface (www.
51. 3347 (Waters). Raw data collected were processed and converted into. mgf format. The MS/MS data were analyzed using MeroX software v2. 0. 1. 4 (Go ¨tze et al. , 2015). Mass tolerances of 5 ppm for precursor ions and of 10 ppm for product ions were applied. A 5% FDR cut-off and a signal-to-noise ! 2 were applied. Lys and Arg residues were considered as protease sites with a maximum of three missed cleavages. Carbamidomethylation of cysteine was set as static modification and oxidation of methionine as variable modification (max. mod. 2). Primary amino groups (Lys side chains and N-termini) as well as primary hydroxyl groups (Ser, Thr and Tyr side chains) were considered as cross-linking sites. The cRap database was used in combination with the reporter ion scan event (RISEUP) mode with a maximum missing ion of 1.
Nevertheless, around 75% of the H N , N, C O , C a and C b nuclei in the protein were successfully assigned. Even if it was not possible to transform these partial NMR data into an accurate 3D structure, the values of the chemical shifts obtained for some of the residues were derived into secondary structures using the TALOS-N software (Figure  S2(A) ). 37 The predicted (PSIPRED, upper) and experimental (NMR, lower) patterns of secondary structures are in good agreement, confirming the global folded structure of the protein. Respectively, 13%, 37% and 50% of the assigned residues were folded in a helix, sheet, and coil, in agreement with the CD data. Interestingly, the NMR data support the presence of a CS domain ranging from residue K99 to residue K172 (Figure  S2(C) ). Note that the long unstructured regions in DPCD may impair protein crystallization.
The theoretical SAXS curves of 4 of the models fit the experimental data remarkably well with equivalent v 2 (5. 5-6. 5) whereas the fifth, which differs in the position of an unstructured loop, did not fit the data properly (v 2 $ 12. 5). Derived R g values of $ 20 A are in good agreement with the value of 22 A determined experimentally. Of note, newly   S1. (C-F) LUMIER-IP analysis of interactions. Graph plotting the % of co-IP efficiency for the interaction between co-expressed 3xFLAG-FL-R2TP subunits and RL-DPCD (C), 3xFLAG-FL-R2TP subunits or DPCD and RL-WDR92 (D), 3xFLAG-FL-DPCD and RL-R1 or R2 WT or mutant (E), 3xFLAG-FL-DPCD and RL-R1 or R2 with or without CB6644 treatment (F). The percentage of co-IP was calculated from the co-precipitated RL fusion protein (IP/Input ratios of RL activity), normalized with the IP/Input ratio of FL activity obtained in the anti-FLAG IP.
Topological investigation of the interaction between R1R2 and DPCD First, SEC-SAXS experiments were performed on the R1R2D complex (Figures  4(A-D ) and Tables  S2  and S3 ). Remarkably, the R1R2D complex harbored a constant R g in a R g versus a frame number plot, attesting to the homogeneity and the stability of the complex even after several dilution/concentration steps (Figure  4(A) ). The scattering curve of the R1R2D complex is shown in Figure  4(B). The R g value determined for R1R2D was 54 A (Table  S3 ). In comparison, a R g value of $ 52 A was determined for a pure R2 hexamer. 20 The same theoretical R g value of $ 52 A was obtained for R1R2 hexamers both having DII up conformation (DII ext stretched upward in the direction of the solvent, PDB: 7OLE). On the other hand, a theoretical R g value of $ 45 A was determined for hexameric R1R2 with DII down conformation (DII ext stretched downward), in the context of INO80 (PDB: 5OAF).
To evaluate the reliability of our XL-MS experiments, we first compared R1R2 inter-and intra-cross-links on available R1R2 cryo-EM structures either in DII up (PDB: 7OLE) or DII down conformation (PDB: 5OAF). Considering a constraint distance cut-off of 6 to 30 A, more cross-linked peptides (both intra and inter) were validated for the DII down stretched structure (23/32 XL peptides, 72% for 5OAF compared to 20/31, 65% for 7OLE), suggesting that DPCD rather binds to R1R2 in its DII down conformation. Concerning the R1R2D complex, 13 inter-cross-links (8 involving DPCD N-ter) were identified between DPCD and R1, while 14 cross-links (4 involving DPCD N-ter) were identified with R2. Interestingly, the inter-R1R2-DPCD cross-links identified included three different DPCD regions (Figure  4(E) ): one at the N-terminus, another at the C-terminus parts corresponding to predicted a-helices located close together, the last region in the putative predicted CS domain.
Acknowledgments The authors would like to thank  S. Balor  and  V. Soldan  ( METI platform, Toulouse ), for technical support in electron microscopy. The negative stain EM image analysis was performed using High Performance Computing resources from  CALMIP  (grant  2020-P1406 ). We thank the  Biophysics and Structural Biology  ( B2S ) platform of IBSLor ( UMS 2008/US 40 ) for access to the  NMR, ITC, CD , and SLS core facilities (https://umsibslor. univ-lorraine. fr/en/facility/biophysics-structural-biology-b2s). We also thank the  Functional Proteomic Platform of Montpellier (FFP). Financial support from the  IR-RMN-THC   FR3050   CNRS  for conducting the research is gratefully acknowledged. We also thank  Javiez Perez  and  Aurelien Thureau  for assistance with the SWING beamline. SOLEIL Synchrotron is acknowledged for providing beamtime and synchrotron radiation facilities.
This work was supported by the  French Centre National de la Recherche Scientifique (CNRS) ,  Universitede Lorraine (UL), Universitede Strasbourg (Unistra) , the  Agence Nationale de la Recherche  [ ANR-16-CE11-0032-04 ], the  Ligue Nationale Contre le Cancer  ('equipe labellisee'),  Institut national du Cancer [INCa PLBio   2016-161 ], and the  French Proteomics Infrastructure  ( ProFI ;  ANR-10-INBS-08-03 ). The authors would like to thank  GIS IBiSA and Region Alsace  for financial support in purchasing a Synapt G2 HDMS and Orbitrap Exactive Plus EMR instrument, respectively. E. D. acknowledges the  French Ministry for Education and Research  for funding of her PhD fellowship. M. L was granted by the  ANR  and S. H. by  UCB. R. D. S. M. received young researcher funding from the region Grand-Est.
Genome sequencing, assembly and automatic annotation The nuclear genome was deposited in the MycoCosm platform  (Grigoriev et al. 2014 ) and automatically annotated, as previously described  (Kuo et al. 2014 ) using the JGI Annotation Pipeline. The mitochondrial genome annotation pipeline combined ab initio predictions, homology-based predictions with a curated mitochondrial protein set, and HMM-based predictions, as described in  (Haridas et al. 2018 ). The KOG classification scheme was used to evaluate the number of genes associated with predicted processes with detailed gene ID available at https://mycocosm. jgi. doe. gov/cgi-bin/kogBrowser?type=KOG&db=Diohu1). The KEGG pathway database was used to identify metabolic pathway genes (https://mycocosm. jgi. doe. gov/cgibin/metapathways?db=Diohu1).
Detected putative TEs were classified into Orders and Superfamilies, as previously described  (Wicker et al. 2007). Unique candidate TEs for each family, with typical TE domains (e. g. transposase, reverse transcriptase, RNase H, integrase, aspartic protease, gag domains) were then used to build a putative TE library (File S1) to screen the genome sequence of D. hungarica PDD-24b-2 using RepeatMasker v4. 1. 2-p1 and estimate putative TE copy number, including full-length and truncated copies. The RepeatMasker. out file was parsed with the tool "One code to find them all" (Bailly-Bechet et al. 2014) to assemble detected TE fragments. More information on the TE-mining process can be found in the following GitHub repository: https://github. com/JarrigeD/Dioszegia_hungarica_sequencing.
Geographical distribution A total of 2,068 whole genome shotgun (WGS) raw read metagenomic datasets were hand-picked to maximize geographic and environmental variety, and retrieved from the Sequence Read Archive (SRA) using sra-tools. The presence of D. hungarica sequences was tested using sra-tools blastn_vdb megablast, with strain PDD-24-filtered to target members of the genus Dioszegia (≥ 45 nt with ≥ 99% identity to the PDD-24b-2 5. 8S rRNA gene sequence) and of the species D. hungarica (≥ 15 nt to ITS1 or ITS2 sequences, E-value ≤ 10e -10 ). These thresholds were defined using alignments of ITS regions of D. hungarica PDD-24b-2 to those of fungal type strains in the NCBI ITS_RefSeq_Fungi database.
One contig was circular, as evidenced by more than 500 Illumina reads bridging its ends (data not shown), and corresponded to the mitochondrial genome. Its size of 27,226 bp was in close agreement with that estimated for the D. hungarica strain CBS 4214 T from average contour-length on electron micrographs twenty years ago (27. 3 kbp,  Gácser et al. 2002). After assembly, the beginning 5' third and the remaining 3' parts of the 18S rRNA gene were located at the termini of two nuclear contigs, i. e. the smallest contig of 2 kbp (contig20) and the contig of 1. 11 Mbp (contig11, which also contained the remainder of the rRNA-encoding region). To confirm the linkage between contig20 and contig11, PCR amplification of the 18S rRNA gene was performed using primers targeting contig20 and contig11.
aurantiaca and D. crocea. A detailed comparative assembly assessment of the 4 genomes using BUSCO v5. 2. 2  (Manni et al. 2021 ) was performed using the tremellomycetes_odb10 database. The estimated occurrence of complete genes was similar for the 4 compared Dioszegia genomes, yet at about 89. 5% instead of the expected 100%. This suggests a lineage specific bias for the Dioszegia genus of the reference tremellomycetes_odb10 database. A notable difference between Dioszegia genomes is the high percentage of duplicated genes reported for D. cryoxerica (53. 4%), possibly reflecting unresolved haplotypes in the diploid assembly of its genome (https://mycocosm. jgi. doe. gov/Diocr1). This would also be consistent with the twice larger length of its assembly (39. 5 Mpb) compared to the 3 other reported genomes including D.
Identified genes for carotenoid biosynthesis (36 putative genes, KEGG annotations, JGI Annotation Pipeline) are in line with previous reports of carotenoids in Dioszegia strains  (Madhour et al. 2005; Amaretti et al. 2014; Villarreal et al. 2016) , and also with the bright orange color culture observed for D. hungarica PDD-24b-2 (Figure  1 ). Carotenoids prevent oxidative stress  (Madhour et al. 2005 ) and act as photo-protectants  (Moliné et al. 2009 ) and cryo-protectants  (Dieser et al. 2010) , and may thus favor survival under the harsh conditions of clouds  (Šantl-Temkiv et al. 2022). In this context, strain PDD-24b-2 also encodes a putative antifreeze protein (protein ID: 32937, with a predicted ice-binding protein domain (InterPro entry: IPR021884) and a predicted secretion signal. Secreted antifreeze proteins impair ice crystal formation and protect cell integrity under cold conditions  (Hashim et al.
D. hungarica was detected at diverse latitudes around the world (Figure  4B ), and mostly in aerial biomes. In contrast, representatives of the Dioszegia genus were found to be more diversely distributed (Figure  4C ). Strikingly, ITS sequences specific of D. hungarica were not detected in marine samples in our dataset of selected metagenomes, nor in the Mar and TARA Ocean Gene Atlas databases (no fungal hits with over 97% identity were found). This suggests that D. hungarica is scarce in open sea environments. On the other hand, D. hungarica sequences were not detected in soil metagenomes either (Figure  4C ). This was surprising since the Dioszegia hungarica type strain was isolated from soil  (Takashima et al. 2001). However, when using the GlobalFungi database, which is a terrestrial soil-focused database, ITS sequences of D hungarica were detected in soil samples.
Considering the significant differences in types of sequences between metagenomes (WGS, short raw reads) and the GlobalFungi database (targeted amplification of longer ITS sequences), the stringency of search parameters used in our analysis may contribute to explain this discrepancy, especially in environments with low abundance of D. hungarica communities. Nevertheless, the low occurrence of D. hungarica in oceans is somewhat paradoxical considering that strain PDD-24b-2 was isolated from a cloud of oceanic origin (Figure  S1 ). We thus hypothesize that D. hungarica was picked up during air mass travel across France through the puy de Dôme sampling site. As such, the detection of D. hungarica in cloud water could serve as an indicator of air mass contact with terrestrial surfaces in future studies where detailed characterization of investigated cloud microbiomes is of interest.
Acknowledgements We thank  Léa Eck  for her help with DNA extraction and  Amandine Moreno  for physiological tests and microscopy photographs,  Dr. Laurie B Connell  for giving access to the D. cryoxerica  ANT 03-071  T genome prior to publication,  Dr. Joseph Schacherer  for discussion of sequencing strategy and  Prof. Hubert Becker  for his help with tRNA analysis. This article is dedicated to  Dr. Anne-Marie Delort , pioneer of investigations on the role of microorganisms in atmospheric chemistry, on the occasion of her retirement. FB initiated the study. FB and DJ wrote the manuscript. FB, DJ and SV revised the manuscript. MJ and MS cultivated the strain under supervision of PA. FB performed wet lab experiments. SH performed genome annotation on the MycoCosm platform under supervision of IG.
Funding This study and the postdoctoral grant to DJ were funded by the  French National Agency , grant  ANR-19-CE01-0004-02 , project  METACLOUD. Genome annotation was performed by the  U. S. Department of Energy Joint Genome Institute , a  DOE Office of Science User Facility , supported by the  Office of Science of the U. S. Department of Energy  under contract no. DE-AC02-05CH11231.
Data availability The Dioszegia hungarica PDD-24b-2 Whole Genome Shotgun project was deposited at DDBJ/ENA/GenBank under accession number JAKWFO000000000. The genome version used in this report is JAKWFO010000000. The raw Illumina and PacBio reads were deposited at the Sequence Read Archive under accessions numbers SRR18177991 and SRR18177990 respectively. Details on genome assembly and gene model properties are provided on the MycoCosm genome portal (https://mycocosm. jgi. doe. gov/Diohu1). Strain Dioszegia hungarica PDD-24b-2 is available upon request to Dr. Pierre Amato or Dr. Françoise Bringel. Representative sequences of putative D. hungarica PDD-24b-2 TE families are in File S1. Putative TEs detected in D. hungarica PDD-24b-2 are in Table  S1. ITS sequences used to construct the phylogenetic tree of the Dioszegia genus are in Table  S2.
Environmental samples in which D. hungarica and Dioszegia species were searched are provided in Table  S3. The air mass trajectory of the cloud from which D. hungarica strain PDD-24b-2 was isolated is shown in Figure S1. A close-up of the Illumina read depth coverage of D. hungarica PDD-24b-2 rRNA gene region is provided in Figure S2. The homolog search scripts, environmental metagenome dataset, as well as more information on biogeographic analyses and TE mining are available at https://github. com/JarrigeD/Dioszegia_hungarica_sequencing.
Maps of WGS datasets with D. hungarica or Dioszegia sp. hits were plotted in Python v3. 10. 2 using Matplotlib v3. 5. 1 and GeoPandas v0. 10. 2. Details of metadata and dataset accessions, homolog search scripts, filtering parameters and mapping processes are available at https://github. com/JarrigeD/Dioszegia_hungarica_sequencing. The GlobalFungi database (accessible at https://globalfungi. com/) (17,000 ITS amplicons environmental samples) (Větrovský et al. 2020), the MarDB database (accessible at https://mmp. sfb. uit. no/blast/) (14,600 (Salazar et al. 2019)8;Priyam et al. 2019) 2018;Priyam et al. 2019)and TARA Ocean Gene Atlas databases(Villar et al. 2018) (accessible at https://tara-oceans. mio. osupytheas. fr/ocean-gene-atlas)EUK_SMAGs(713eukaryoticplanktonMetagenomeAssembledGenomes:MAGs)(Delmontet al.
Genome assembly and predicted annotation data of D. hungarica PDD-24b-2 compared to the three other genome-sequenced Dioszegia sp. Content D. hungarica PDD-24b-2 D. aurantiaca JCM 2956 T D. crocea JCM 2961 T D. cryoxerica ANT 03-071 T BioProject accession n° PRJNA809585 PRJDB3721 PRJDB3718 PRJNA196046 Reference this study Takashima et al. , 2019 Takashima et al. , 2019 (Connell L. B. personal communication) Sequencing and assembly a statistics Sequencing read coverage depth 97x (PacBio Sequel) + 112x (Illumina HiSeq 176x (Illumina HiSeq 98. 5x (Illumina HiSeq (technology) 101x (Illumina MiSeq) 2500) 2500) 2500) Assembly size (Mbp) 20. 96 19. 34 20. 60 39. 52 Scaffolds/contigs 18/18 52/139 26/86 865/1,318 Longest scaffold (Mbp) 5. 56 4. 12 3. 59 0. 43 L50 scaffold value 4 5 10 96 N50 scaffold length (Mbp) 2.
• Lactobacillus cellobiosus was first reclassified to as Lactobacillus fermentum, more recently renamed Limosilactobacillus fermentum. • The qualification 'QPS only applies when the species is used for production purposes with absence of viable cells in the product' has been harmonised among the different TUs concerned. • Synonyms of yeast species were added and the qualification 'absence of resistance to antimycotics' has been deleted for those yeast TUs for which the QPS status only qualifies for production purposes. • The warning for the probiotic use of Saccharomyces cerevisiae has been deleted because this is out of the scope of the QPS assessment. The third ToR requires a (re)assessment of new TUs notified to EFSA, for their suitability for inclusion in the updated QPS list at the Knowledge Junction in Zenodo (https://doi.