dataesr/scientific-paragraphs-categorization huggingface dataset:
When necessary, datasets were first subsetted to exclude disease samples. All datasets were processed using the Seurat analysis pipeline described above with one modification. In place of running PCA analysis, mutual nearest neighbors (mnn) correction was performed using the FastMNN function from the SeuratWrappers package to perform batch correction of each unique patient sample within the respective dataset. Subsequently, the UMAP and sNN were calculated using the mnn reduction based on 30 dimensions. For datasets where uploaded metadata did not include cell type annotations, the melanocyte cluster was identified by expression of MITF, PMEL, DCT, TYR and MLANA. For each dataset the melanocyte cluster was subsetted and the relevant metadata names and levels were made consistent across datasets.
Acknowledgements We thank the  UC Davis Biological Electron Microscopy Core Facility  for their technical support and sample preparations. We acknowledge the  SF Chan Zuckerberg Biohub  Sequencing platform with special thanks to  Norma Neff , as well as the  UCSF Center for Advanced Technology  for next generation sequencing. We thank the  Laboratory Animal Resource Center (LARC) at UCSF. The work was generously supported by grants from  UCSF Program for Breakthrough Biomedical Research and Sandler Foundation , the  NIH   Director's New Innovator Award  ( DP2NS116769 ) and the  National Institute of Diabetes and Digestive and Kidney Diseases  ( R01DK121169 ) to F. F. The study was supported in part by  UCSF Laboratory  for Cell Analysis shared resource facility through the  NIH  grant  P30CA082103  and by grants to H.
Scale bar represents 100um. H. Doubling time analysis of T1 and T2 melanocytes. Points represent technical replicates from n=3. **** is p<0. 0001 and error bars represent standard deviation. I. UMAP embedding of merged T1 and T2 melanocyte datasets. J. Violin plots showing the expression of selected T1 and T2 melanocyte specific transcription factors. K. Violin plots showing the expression of selected T1 and T2 melanocyte specific secreted ligands. L. Violin plots showing the expression of selected T1 and T2 melanocyte specific receptors. M. Violin plots showing the expression of selected T1 and T2 melanocyte specific surface markers.
Error bars represent standard deviation. F. Projection of stage 5 Schwann subclusters and cell types into the SWNE embeddings of the "low passage" Schwann induction dataset published in Majd et al. Cells (points) with similar SWNE coordinates are transcriptionally similar to one another. Abbreviations: SCs = Schwann Cells, SCPs = Schwann Cell Precursors, SCPDs = Schwann Cell Precursor Derivatives. G. Expression (top) and predicted activity (bottom) of canonical mesenchymal transcription factors in stage 1-5 NCC and Schwann subclusters. Asterisks represent TF activity predicted from lower confidence motif annotations. H. Expression (top) and predicted activity (bottom) of canonical sensory and autonomic neural transcription factors in stage 1-5 NCC and Schwann subclusters. Asterisks represent TF activity predicted from lower confidence motif annotations.
I. Feature plots of normalized expression for hub markers SOX8 (top), ITGA4 (middle) and SERPINE2 (bottom) in stage 2-5 NCC and Schwann subclusters. J. Feature plot Kastriti et al. dataset colored by module score for S4 NCC2 top 100 marker genes. Dotted line outlines the cells annotated as "Hub" by the original authors. UMAP inlay colored by author annotations for the Hub and SC cells. K. SOX10 (white), MITF (red) and cKIT (green) expression in stage 2-4 crestospheres and stage 5 SCP induction. Scale bar represents 100um. L. Flow cytometry-based quantification of SOX10 positive and SOX10/MITF double positive populations in stage 1-5 crestospheres and stage 5 SCP induction. Error bars represent standard deviation.
**** is p<0. 0001 and error bars represent standard deviation. D. UMAP embeddings of individually analyzed T1 (top) and T2 (bottom) melanocyte datasets. E. Scatter plot of average expression of all detected genes in T1 and T2 melanocytes. Genes are colored by differential expression where genes in blue are significantly (p < 0. 05) more highly expressed in T1 melanocytes by > 0. 25 fold change while genes in pink are significantly (p < 0. 05) more highly expressed in T2 melanocytes by > 0. 25 fold change. Genes represented by black outlines are not significantly differentially expressed.
Results A T7SSb locus specific to Sgg. In order to identify the specific pathogenic trait(s) of Sgg, comparative genomics was performed on newly sequenced 13 Sgp and 38 Sgg clinical isolates obtained from the National Reference Center of Streptococci in France. Phylogenetic analysis of these newly sequenced genomes, together with the complete genomes of Sgg and Sgp publicly available on NCBI GenBank assigned Sgg and Sgp into two distinct clades, confirming their correct classification (Figure  S1 ). BLASTnbased comparative genomic analysis of the reference genome UCN34 together with the representative Sgg and Sgp genomes uncovered a genomic island unique to Sgg (Figure  1A ). This genomic island contains the six genes  (esxA, essA, esaB, essB, essC and esaA)  encoding the core components of the Type VIIb Secretion System (T7SSb) machinery (Figure  1A  and 1B ).
coli from TelE intoxication (Figure  5A , 5B), and our data showed that only TipE is able to block TelE activity through direct interaction and sequestration. Notably, TipE is a DUF5085 family protein predicted related to T7SS in the Pfam database. Based on our data, we propose herein that DUF5085 family proteins could serve as immunity proteins to T7SSb toxins. Interestingly, a diverse pool of TelE variants (TelE to TelE7) exist in the genomes of Sgg isolates, all harboring the conserved C-terminal glycine zipper motif essential for TelE activity. Glycine zipper motif is a common feature in membrane proteins displaying pore-forming activity. In addition to the aforementioned CdzC/D and Tse4, glycine zipper motif is also found in the vacuolating toxin VacA from Helicobacter pylori, the prion protein (PrP) and the amyloid beta peptide (A)  (Kim et al.
Phylogenetic analysis A core genome-based alignment was performed on Parsnp version 1. 2 integrated in the Harvest suite  (Treangen et al. , 2014) , with Sgg UCN34 (GenBank accession no. FN597254) served as the reference genome. The other S. gallolyticus complete closed genomes available on NCBI, i. e. Sgg ATCC43143 (GenBank accession no. NC_017576), ATCC BAA_2069 (GenBank accession no. NC_015215) and DSM 16831 (GenBank accession no. NZ_CP018822); Sgp ATCC43144 (GenBank accession no. NC_015600), NCTC13784 (GenBank accession no. NZ_LS483462) and WUSP067 (GenBank accession no. NZ_CP039457); and two additional draft genomes -Sgm ACA-DC-206 (unpublished genome) and the Sgg TX20005 (NCBI Assembly ID GCA_000146525) -were also included in the analysis for a clear distinction of these closely related strains.
, 1994)  to the protein sequences on protein databases. All databases include a reversed version of all the sequences and the data was filtered to between a one and two percent peptide false discovery rate. Downstream data analysis was performed in R studio using the Differential Enrichment analysis of Proteomics Data 1. 10. 0 package  (Zhang et al. , 2018). Proteins that were not detected across all the three replicates of either the UCN34 WT or the ∆essC mutant were excluded from the analysis. Next, the total peptide count of the remaining proteins (n = 162) was scaled and variance stabilized  (Huber et al. , 2002)  before the missing values (i. e. peptide count = 0) were imputed with the assumption that the missing values are missing not at random (MNAR), using the Deterministic Minimum Imputation (MinDet) strategy (10 -4 quantile)  (Lazar et al.
The isolates sequenced in this study were labeled in black font, whereas the reference strains Sgp (NCTC13784, ATCC43144 and WUSP067) and Sgg (DSM16831, ATCC43143, BAA2069 and UCN34) with complete genomes available on NCBI GenBank, and a draft genome of Sgm (strain ACA-DC-206) were labeled in blue font. Genomes used for comparative genomics analysis as shown in Figure  1A  were highlighted with darker color shades. Bootstrap value for all the major branches ranges from 0. 97 to 1. Genomes labelled with asterisk contain a different T7SSb gene locus arrangement than the UCN34 reference strain.
Acknowledgement We are very grateful to  Alexandra Doloy  and  Nicolas Dmytruk  for providing us with the collection of S. gallolyticus clinical isolates. We thank  Ross Tomaino  from  Taplin Mass Spectrometry Facility  for the mass-spectrometry analysis. We thank  Tarek Msadek  for critical reading of the manuscript. This work was supported by the  National Research Foundation and Ministry of Education Singapore  under its  Research Centre of Excellence Program (SCELSE). S. Dramsi  would like to acknowledge the support of the  Institut National contre le Cancer (INCA , grant  PLBIO16-025 ) and from the  French Government 's  Investissement d'Avenir program ,  Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases  (grant no. ANR-10-LABX-62-IBEID ).
Transcriptomic analysis reveals cholesterol biosynthesis as a pathway modulated by shear stress In order to explore the molecular changes occurring upon shear stress, we performed a transcriptomic study by RNA sequencing and compared static and shear conditions (48 h). First, we performed an analysis of the principal components (PCA) to have an overview of our dataset and check its consistency. As shown in Figure  4A , we first observed that the triplicates of each condition are grouped together, confirming their homogeneity. Then, the principal component PC1, differentiating shear (on the left) and static (on the right) conditions, is of 40%, while the second principal component, PC2 of 17%, explains the differences between KD_N1 on one side (bottom) and KD_N4 and control cells (CTRL) on the other side (top).
This PCA shows that, overall, our samples are first distinguishable by the culture conditions, and second by the genotype. Of note, it reveals also that KD_N4 and control samples have a closer transcriptomic signature than with KD_ N1 samples which is also visible on the heatmap (Figure  4A' ). In control cells, 48 h of shear stress induced a drastic change of gene expression compare to static condition, with the deregulation of a total of 4,302 genes, of which 2,236 were upregulated and 2,066 downregulated (fold change of 1. 2) (Figure  4A ", Supplementary Table  S1 ). Of note, Nphp1 expression is slightly modulated by shear stress (fold change of 1. 44), while Nphp4 is not (fold change of 1. 08). To understand which signaling pathways were the most altered upon shear stress, we performed a pathway enrichment analysis using Ingenuity software (Qiagen) (Figure  4B , Supplementary Table  S2 ).
For filipin staining, cells were washed in PBS three times and incubated in the filipin solution at a concentration of 50 μg/mL (Sigma Aldrich, F-9765) for 30 min at room temperature. Coverslips and microslides were mounted in Mowiol media. Image acquisition was performed with a Yokogama CSU-X1 spinning disk microscope (63×, NA 1. 4) (filipin staining) or a Leica SP8 laser scanning confocal microscope (63×, NA 1. 4). Fiji software (http://fiji. sc/) was used for all quantifications, with the JACoP plugin for Pearson correlation coefficient analysis. Measurements of cilium length was done with Imaris software (Oxford Instruments).
Calcium measurements Cells were seeded at a density of 200,000 cells/microslide with a growth area of 2. 5 cm 2 and grown for 1 day prior to transfection. Cells were then transfected with 500 ng of R-GECO calcium biosensor plasmid (Addgene plasmid # 45494) using Lipofectamine 2000  (Thermo Fisher Scientific, 11668-019)  for 48 h and cultured with phenol red-free medium. Images were acquired on a Nikon Ti-E inverted microscope equipped with a temperature chamber set at 37 °C, at the ×40 objective (NA 1. 4). The shear stress of 1 dyn/cm 2 was applied after 1 min of acquisition over a total period of 5 min. R-GECO signal intensity was normalized to background (ΔF/F0), where F0 is the average intensity over the first 30 s, were measured for each cell over time using ImageJ software. The response time following shear stress initiation (Δt) was evaluated for all analyzed cells.
Funding acquisition, Resources, Writing-review and editing. MD: Funding acquisition, Project administration, Resources, Supervision, Funding This work was supported by  INSERM , the  Ministère de l'Education Nationale de la Recherche et de la Technologie (MENRT) , and by state fundings from the  Agence Nationale de la Recherche (ANR)  ( ANR-10-IAHU-01 ,  ANR-17-RHUS-0002  (" RHU-C'IL-LICO "), and  R18176KK  to ND). FR was supported by a fellowship from the  european Innovative training  network DRIVE ( E17245KK ); GF by the  Marie Sklodowska-Curie Innovative Training Network SCilS  (# 861329 ).
Discussion In this study, we defined the structure of the major H. pylori ribonuclease RNase J and its in vitro oligomerization state as well as that of its cooperative partner, the RhpA RNA helicase. We also identify in vivo acetylation patterns of RNase J and demonstrate that the corresponding residues impact on oligomerization and activity in vitro and in vivo. Our crystal and cryo-EM structures of H. pylori RNase J revealed a tetrameric arrangement composed of a dimer-of-dimers. These experimental structures are in excellent agreement with predictions from the programs Robetta and Alphafold that are based on machine learning. The N-terminal region, corresponding to residues 1-136, is not resolved in the cryoEM maps. This region is not predicted to form a compact, globular structural module but rather to be intrinsically disordered  9.
Bacterial strains and growth conditions The bacterial strains used in this study are summarized in Supplementary Data 2. H. pylori strains were derivatives of strain B128  39, 40. Plasmids (Supplementary Data 2) were constructed and amplified using E. coli XL1-Blue (Agilent Technologies). H. pylori strains were grown on Blood agar base 2 (Oxoid) plates supplemented with 10% defibrinated horse blood and with an antibiotic-antifungal cocktail composed of 2. 5 µg/mL amphotericin B, 0. 31 µg/mL polymyxin B, 6. 25 µg/mL trimethoprim and 12. 5 µg/mL vancomycin. H. pylori mutants were selected using 20 µg/mL kanamycin, 10 µg/mL apramycin or 6 µg/mL chloramphenicol. For liquid cultures, we used Brucella broth supplemented with 10% fetal calf serum (FCS) (Eurobio), the antibiotic-antifungal cocktail and, when necessary, chloramphenicol to select for plasmid-containing bacteria.
Plasmid preparation and transformations A NucleoBond Xtra midi kit (Macherey-Nagel) and a QIAamp DNA minikit (Qiagen) were used for plasmid preparations for H. pylori transformation and genomic DNA extractions, respectively. For plasmid preparations for E. coli transformation and sequencing, a QIAprep Spin Miniprep kit (Qiagen) was used. PCR was carried out with either DreamTaq DNA polymerase (Thermofisher) or with Q5 High-Fidelity DNA polymerase (NEB) when the product required a high-fidelity polymerase. A list of the oligonucleotides that were used can be found in Supplementary data 3.
The resulting strains were then used to transform, by cassettes constructed in a similar manner, in order to delete the rnj gene and replace it by a kanamycin resistance gene [as in ref. 2]. The transformants were selected on plates containing kanamycin, chloramphenicol and 1 mM IPTG to allow the expression of the copy of rnj from the plasmid. Plasmids for BACTH were constructed from plasmids pUT18 and pKNT25  42  by inserting wild type or mutant variants of the rnj gene in the PstI and KpnI restriction sites following standard techniques using plasmids indicated in Supplementary Data 2. Deletion of the genes of interest, construction of mutants, of fusions and/or insertion of cassettes was verified by PCR and sequencing of the region of interest.
Mass photometry Mass photometry experiments were performed using Refeyn TwoMP mass photometer (Refeyn). Borosilicate microscope coverslips (24 ×50 mm 1. 5 H, Marienfeld) were cleaned using ethanol and MilliQ water (3x) and dried under nitrogen stream. Silicone gaskets (6 wells, 3 mm diameter x 1 mm depth, Refeyn) were placed onto clean coverslips. Before data acquisition, coverslip wells were loaded with 18 μL of buffer (20 mM sodium phosphate pH 7. 2, 300 mM NaCl), followed by focusing the instrument on the glass-liquid interface. Before measurements the protein concentration was adjusted to 500 nM. Typically, mass photometry experiment was initiated by jump-diluting 2 μL of a protein solution directly in the buffer-loaded well to reach a final concentration of 50 nM, followed by recording for 60 s.
CryoEM of RNase J The protein mixture of RNase J (1 µM) and RhpA (2 µM) in a buffer containing 20 mM sodium phosphate pH 7. 2, 500 mM NaCl, 0. 5 mM TCEP was used for grids preparation. Three μl of the sample was applied to Quantifoil R1. 2/1. 3 grids that had been pretreated by glow-discharge (0. 29 mbar, 25 mA, 1 min, Pelco Easiglow glow discharger), and excess sample was blotted away and frozen in liquid ethane, blot force -4 to 0, blot time 3 s, Vitrobot Mark IV (Thermo Fischer). The grids were screened on a 200 kV Talos Arctica (FEI) (Cryo-EM facility, Department of Biochemistry, University of Cambridge) and the movies were recorded on the same 200 kV Talos Arctica machine with a Falcon III (Thermo Fischer, Cryo-EM facility, Department of Biochemistry, University of Cambridge). Datasets were pre-processed with Warp  49.
Analytical ultracentrifugation Samples of His-tagged purified proteins were thawed on ice and the buffer was replaced using G-25 columns (PD MiniTrap G-25, GE Healthcare) with 25 mM Tris-HCl pH 8, 300 mM NaCl and 0. 5 mM Tris(2-carboxyethyl)phosphine (TCEP, Sigma). Appropriate amounts of the different proteins were mixed and diluted in the same buffer with a final volume of 300 µL that was charged into 2 sector AUC cells. The centrifugation was performed for 16 h on an Optima analytical XL-I ultracentrifuge (Beckman-Coulter) with an 8-hole An-50 Ti rotor, at 157,772 x g and 20 °C, measuring the optical density at 230 nm in order to determine the sedimentation profile of the protein. The data was analyzed with the Sedfit v16. 1c software (NIH) using a diffusion deconvoluted continuous sedimentation coefficient distribution c(s) with one discrete component model  53.
The model was chosen in order to take in consideration the signal due to TCEP absorption. The presented graphs correspond to a resolution of 300 points with a confidence interval of 0. 9. For the individual proteins, the sedimentation coefficient independent of the concentration (S 0 ) was calculated. The partial specific volume ( ν) of the proteins was estimated by the software Sednterp 54 based on the amino acid sequence. This software was also used for the calculation of the density and viscosity of the buffer used throughout the experiments. Calculation of sedimentation coefficients for protein structures was performed with the program Hydropro  55. For comparison, the profile of each analysis was normalized to 1 for the highest peak.
Circular dichroism The near-UV absorption spectra (195-260 nm) were measured, in the same buffer as for the AUC experiments, by circular dichroism with a Circular Dichroism Spectrometer Model 215 (Aviv instruments) using 0. 2 mm optical path cells with 5 mM of RNase J WT and K649A mutant. The proportions of the different secondary structure elements were determined with the BeStSel software  56, 57  based on the amino acid sequence.
Phase contrast microscopy Phase contrast microscopy was performed with an Axio Observer microscope (Zeiss) equipped with an Axiocam camera with X100 magnification. Image acquisition was performed with the axiovision SE64 software. Images were cropped and adjusted using FiJi-ImageJ v2. 0. 0 software. The length of wild type cells and that of cells expressing wild type or mutant versions of RNase J from a plasmid, with or without 1 mM IPTG, was measured by using the MicrobeJ plugin of ImageJ  26  with the following parameters: cell area above 0. 7 µm 2 , minimal length of 1 µm and cell width between 0. 4 and 1 µm. Pulldown and mass spectrometry H. pylori cultures of strains expressing FLAG-tagged RNase J were grown in 15 mL of Brucella medium until an OD 600 nm of 0. 6-1. 2 for exponential phase cultures.
For each sample, peptides were loaded on an in-house packed 26 cm nano-HPLC column (75 μm inner diameter) with C18 resin (1. 9 μm particles, 100 Å pore size, Reprosil-Pur Basic C18-HD resin, Dr. Maisch GmbH, Ammerbuch-Entringen, Germany) after an equilibration step in 100 % solvent A (H 2 O, 0. 1% FA). Peptides were eluted with a multi-step gradient using 2-7 % solvent B (80% ACN, 0. 1% FA) during 5 min, 7-23% during 70 min, 23-45% during 30 min and 45-95% during 5 min at a flow rate of 300 nL/min over 132 min. Column temperature was set to 60 °C. MS data were acquired using Xcalibur software using a datadependent Top 10 method with a survey scans (300-1700 m/z) at a resolution of 70,000 and a MS/MS scans (fixed first mass 100 m/z) at a resolution of 17,500. The AGC target and injection time for the survey scans and the MS/MS scans were set to 3E6, 20 ms and 1E6, 60 ms respectively.
The isolation window was set to 1. 6 m/z and normalized collision energy fixed to 28 for HCD fragmentation. We used a minimum AGC target of 1E4 for an intensity threshold of 1. 7E5. Unassigned precursor ion charge states as well as 1, 7, 8 and >8 charged states were rejected and peptide match was disable. Exclude isotopes was enabled and selected ions were dynamically excluded for 30 s. Raw data were analyzed using MaxQuant software version 1. 6. 6. 0 59 using the Andromeda search engine  60. The MS/MS spectra were searched against a UniProt Helicobacter pylori [strain B8  39, 40  ] database (download in 24/06/2019, 1719 entries) and tagged RNase J. Usual known MS contaminants and reversed sequences of all entries were included. Andromeda searches were performed choosing trypsin as specific enzyme with a maximum number of five missed cleavages.
Possible modifications included carbamidomethylation (Cys, fixed), oxidation (Met, variable), Nter acetylation (variable) and K acetylation (Lys, variable) for in-gel peptides. The mass tolerance in MS was set to 20 ppm for the first search then 4. 5 ppm for the main search and 20 ppm for the MS/MS. Maximum peptide charge was set to seven and five amino acids were required as minimum peptide length. A false discovery rate cutoff of 1% was applied at the peptide and protein levels. Raw files and MaxQuant files (msms. txt) were processed in Skyline-daily 20. 1. 9. 268  61  to generate MS1-XIC and perform peak integration for each K-acetylated peptide. Normalization across samples was performed by using the mean of the ratios from non-modified peptides (Supplementary data 1). The MS data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository  62  with the dataset identifier PXD027670.
Acknowledgements We would like to thank  Sébastien Brûlé  and  Bruno Baron  for their help with AUC and circular dichroism experiments, and  Frédéric Fischer  for bioinformatical analysis regarding protein HPB8_1270. We thank  Diane Soussan  for her help in preliminary experiments of this project,  Daniel Vinella  with help with the ß-galactosidase activity measurement and all the members of the  Unité Pathogenèse de Helicobacter. A. T. A. is part of the  Pasteur -Paris University (PPU)   International PhD Program. This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Sklodowska-Curie  grant agreement  N°665807 , and from the  Institut Carnot Pasteur Microbes & Santé  for A. T. A. M. B. L. was a master student of the  UTC (Université de Technologie de Compiègne).