dataesr/scientific-paragraphs-categorization huggingface dataset:
The primary host is the common artichoke (Cynara scolymus L. ). The pathotype strain is CFBP 4188 PT = ICMP 16775 PT , the former type strain of X. cynarae Trébaol 2000 emend. The description is the same as the species. Additionally, the Biolog GEN III and PM02A MicroPlates revealed the ability of strain CFBP 8163 PT  The primary hosts are tomato (Solanum lycopersicon L. ) and pepper (Capsicum annuum L. ). The pathotype strain is CFBP 8163 PT = NCPPB 881 PT = ATCC 19865 PT. The GenBank accession numbers for the two versions its genome assembly are SMDW00000000 and GCA_000192065. 2. In order to provide taxonomic data ready to use and easily comparable, and because the original protologues may be difficult to find, we recall hereby the characteristics of the other pathovars of X. hortorum complemented with data from our study: The description is the same as the species.
The primary host is the Kazakh dandelion (Taraxacum kok-saghyz Rodin). The pathotype strain is CFBP 410 PT = LMG 870 PT = NCPPB 940 PT = ICMP 579 PT = ATCC 19318 PT. The GenBank accession number for its genome assembly is SMDY00000000. Two different nomenclatures may be displayed in order to respect validly published names and assure continuity through literature by adding the ones sometimes still used by researchers * Cancellation of CFBP 2538 as the pathotype strain of the vitians pathovar and proposal of LMG 938 as the neopathotype were submitted by letter to the Committee on the Taxonomy of Plant Pathogenic Bacteria + Representative strain CFBP 7900 of X. hortorum pv. carotae was chosen as the actual pathotype CFBP 4997 is known to be inconsistent ¥ Pathogenicity assays conducted in this study: + = pathogenic, -= non-pathogenic, w = weakly pathogenic, NA = non-tested.
The primary host is the ivy-leaved geranium (Pelargonium peltatum L'Hér. ). The pathotype strain is CFBP 2533 PT = LMG 7314 PT = NCPPB 2985 PT = ICMP 4321 PT. The GenBank accession number for its genome assembly is SMDX00000000. X. hortorum pv. carotae (Kendrick 1934) Vauterin et al. 1995 = X. campestris pv. carotae (Kendrick 1934) Dye 1978.
Acknowledgments The first author would like to thank  Laurène Mirabel  from the  Microbial Ecology lab  for her precious technical assistance,  Martial Briand  from the  IRHS lab  and  Danis Abrouk  from the iBio platform of  UCBL  for their teachings of bioinformatics. The authors are thankful to  Elise Lacroix  from the greenhouse platform of the  UCBL  for her careful management of plants, to lettuce producers of the SERAIL who guided us through their fields, and to the FNX network for the meeting opportunities it offered.
hortorum pv. vitians pv. nov. The GenBank accession number for its genome assembly is SMED00000000. X. hortorum pv. cynarae (Trébaol et al. 2000) comb. nov. = X. cynarae Trébaol et al. 2000 = X. cynarae pv. cynarae (Trébaol et al. 2000) Timilsina et al. 2019.
hortorum pv. gardneri (Jones et al. 2006) comb. nov. Timilsina et al. 2019. The GenBank accession number for its genome assembly is GCA_002939985. 1. X. = X. gardneri (ex-Sutić 1957) Jones et al. 2006 = X. cynarae pv. gardneri (Jones et al. 2006) Timilsina et al. 2019.
Moreover, it remains to be determined whether ADAM10 functions as an intimate ADAM10/ TspanC8 complex or whether TspanC8s are merely modulators of ADAM10 trafficking. This study focuses on Tspan15 as a model TspanC8. Human Protein Atlas mRNA data indicate that Tspan15 is expressed within most tissue types, but only by approximately one-third of cancer cell lines, and not by most blood cell types  (17, 18). Tspan15 is best-characterized by its capacity to promote ADAM10 cleavage of N-cadherin in cell lines and in vivo  (8, 12, 13, 16). Tspan15 is also up-regulated and is a marker of poor prognosis in certain cancers  (19 -21) , and it promotes cancer progression in a mouse model  (21). The aims of this study were 2-fold: first, to develop a novel strategy for tetraspanin mAb generation to make and characterize the first Tspan15 mAbs, and second, to use these mAbs to test four hypotheses that would support the theory that Tspan15 and ADAM10 exist together as a scissor complex: 1) that endogenous Tspan15 and ADAM10 co-localize on the cell surface; 2) that ADAM10 is the principal Tspan15-interacting protein; 3) that Tspan15 expression requires ADAM10; and 4) that covalently linking Tspan15 and ADAM10 together as a single fusion protein yields a functional scissor.
Tspan15 immunoprecipitation followed by ADAM10 Western blotting showed that each mAb effectively co-immunoprecipitated ADAM10 (Fig. 1D ). Therefore, these data validate the four new mAbs as specific mouse anti-human Tspan15 reagents capable of immunoprecipitating Tspan15/ADAM10 complexes. To determine whether our novel immunogen strategy may be useful for other tetraspanins, the same strategy was used for Tspan14, another member of the TspanC8 subgroup. This generated five mouse anti-human Tspan14 monoclonal antibodies, which were selected by flow cytometry screening of HEK-293T cells transiently overexpressing Tspan14 (Fig. S1 ). However, these mAbs did not detect overexpressed Tspan14 by Western blotting and did not detect endogenous Tspan14 by flow cytometry in several cell lines tested (data not shown); the selected antibodies may be low-affinity.
expression constructs (except for Tspan10, which was of mouse origin) or an empty vector control (Ϫ), lysed in 1% Triton X-100 lysis buffer and Western blotted with tissue culture supernatants for each of the four Tspan15 hybridomas, or a positive control FLAG antibody. Blots are representative of three independent experiments. D, human platelets were lysed in 1% digitonin lysis buffer and subjected to immunoprecipitation (i. p. ) with the four Tspan15 mAbs or a negative control mouse IgG1, followed by anti-ADAM10 and anti-Tspan15 (5D4) Western blotting (top panels). The faint additional band in the 5F4 lane corresponds to light chain from the immunoprecipitating mAb (data not shown). To quantitate the data, the amount of ADAM10 co-immunoprecipitated was normalized to the amount of immunoprecipitated Tspan15 with each antibody (bottom).
Tspan15 is an essential subunit of an ADAM10 scissor complex ϳ50%, and a titration effect was observed with lower concentrations (Fig. 3 , Bi and Bii). In contrast, mAbs 5D4 and 5F4 had no effect (Fig. 3 , Biii and Biv). The reason for the different effects of the mAbs is not known, but it could be related to subtle differences in epitope, given that 1C12 and 4A4 more efficiently detected mouse Tspan15 by flow cytometry (Fig. S2 ). Nevertheless, these data show that certain Tspan15 mAbs can inhibit ADAM10/Tspan15 activity.
Tspan15 and ADAM10 co-localize on the cell surface Epitope-tagged Tspan15 is known to co-localize with ADAM10 in transfected cells  (6, 8) , but this has yet to be confirmed for endogenous proteins. To address this, endogenous Tspan15 and ADAM10 were visualized on the surface of A549 cells by total internal reflection fluorescence (TIRF) microscopy. Tspan15 showed substantial co-localization with ADAM10, in contrast to the non-TspanC8 tetraspanin CD9, which was used as a control (Fig. 4Ai ). Quantitation of the imaging data using Manders' coefficient showed that significantly more of the Tspan15/ADAM10 overlapping signal was present within total ADAM10 signal compared to the proportion of CD9/ADAM10 overlapping signal within total ADAM10 signal (M1) (Fig. 4Aii ). Consistent with this, significantly more of the Tspan15/ADAM10 signal was present within total Tspan15 signal than CD9/ADAM10 was within total CD9 signal (M2) (Fig.
6C ). Importantly, the loss of Tspan15 protein was not a consequence of reduced Tspan15 mRNA expression in the absence of ADAM10, as this was unaffected in ADAM10knockout cell lines as measured by quantitative RT-PCR (qRT-PCR) (Fig. 6D ). To investigate the mechanism underlying the requirement of ADAM10 for Tspan15 expression, A549 cells were treated with the lysosomal inhibitor ammonium chloride. This significantly increased Tspan15 protein expression in ADAM10-knockout cells (Fig. 6E ), whereas the proteasome inhibitor MG132 had no effect (data not shown). Interestingly, the molecular weight of Tspan15 was increased in ADAM10knockout cells following lysosomal inhibition (Fig. 6Ei ). This increase was due to aberrant glycosylation, because all Tspan15 bands on the blot were reduced to the same molecular weight following deglycosylation with peptide:N-glycosidase F (data not shown), indicating that ADAM10 affects Tspan15 glycosylation as has previously been reported for Tspan5  (15).
Tspan15 is an essential subunit of an ADAM10 scissor complex ding to a level comparable with that of ADAM10 and Tspan15 transfected as individual constructs, in terms of both basal shedding and shedding induced by the ADAM10 activator NEM (Fig. 9Ei ). Betacellulin shedding was partially dependent on Tspan15, because ADAM10 transfection alone was not sufficient to fully restore shedding (Fig. 9Ei ). To confirm expression of the constructs used in these experiments, ADAM10 flow cytometry was used; the fusion protein was expressed at ϳ2-fold greater levels than ADAM10 individually with Tspan15 (Fig. 9Eii ). These fusion protein data provide further evidence that ADAM10/Tspan15 exists as a functional scissor complex, because expression and function of the fusion protein are similar to when ADAM10 and Tspan15 are individually co-expressed.
Blots are representative of three independent experiments. D, human platelets were lysed in 1% digitonin lysis buffer and subjected to immunoprecipitation (i. p. ) with the four Tspan15 mAbs or a negative control mouse IgG1, followed by anti-ADAM10 and anti-Tspan15 (5D4) Western blotting (top panels). The faint additional band in the 5F4 lane corresponds to light chain from the immunoprecipitating mAb (data not shown). To quantitate the data, the amount of ADAM10 co-immunoprecipitated was normalized to the amount of immunoprecipitated Tspan15 with each antibody (bottom). Error bars, S. E. from three independent experiments.
Relevant P-values are highlighted directly in the figure (*< 0. 05; **< 0. 01, ***< 0. 001), and all P-values can be found in Table  EV8. B Genetic interactions of nlpI with EPase genes. Strains were arrayed using a Rotor HDA replicator on Lennox LB agar plates and incubated for 12 h at 37°C. Each plate contained 384 colonies, 96 from the wild type, single mutants and double mutants. An example of a 384-well plate is shown. Double mutants were made twice, swapping the resistance markers to the two single mutants. Colony integral opacity was quantified as a fitness readout, using the image analysis software Iris  (Kritikos et al, 2017). Bar plots show the averaged values of 2 biological experiments, each having 96 technical replicates (i = 2, n = 192). The error bars represent the 95% confidence interval.
5% (wt/vol) blocking reagents (Boehringer, Mannheim, Germany) in PBS) was used, and the samples were incubated for 30 min at 37°C. For immunolocalization, cells were immobilized on 1% agarose in water slabs coated object glasses as described  (Koppelman et al, 2004)  and photographed with an Orca Flash 4. 0 (Hamamatsu) CCD camera mounted on an Olympus BX-60 fluorescence microscope through a 100×/N. A. 1. 35 oil objective. Images were taken using the program ImageJ with MicroManager (https:// www. micro-manager. org). SIM images were obtained with a Nikon Ti Eclipse microscope and captured using a Hamamatsu Orca-Flash 4. 0 LT camera. Phasecontrast images were acquired with a Plan APO 100×/1. 45 Ph3 oil objective. SIM images were obtained with a SR APO TIRF 100×/1. 49 oil objective, using 3D-SIM illumination with a 488 nm laser, and were reconstructed with Nikon-SIM software using the values 0.
Fixed ligand concentration MST assays for trimeric complexes For fixed ligand concentration MST assays, labelled proteins were titrated against a fixed concentration of unlabelled proteins, respectively. In fixed concentration assays with labelled MepS or LpoA, unlabelled PBP4-NlpI or PBP7-NlpI complexes were preformed by incubating NlpI (3 lM) with excess PBP4 or PBP7 (30 lM), on ice for 10 min. In fixed concentration assays with labelled PBP1A, unlabelled PBP4-NlpI complex was pre-formed by incubating PBP4 (0. 5 lM) with NlpI (1 lM), on ice for 10 min. Thermophoresis or fluorescence of labelled protein in the presence of unlabelled ligands was determined using NT Analysis 1. 5. 41 and MO Affinity Analysis (×64) software.
Analytical ultracentrifugation Purified NlpI was dialysed O/N against 25 mM HEPES/NaOH, 150 mM NaCl, pH 7. 5, in preparation for AUC. AUC sedimentation velocity (SV) experiments were carried out in a Beckman Coulter (Palo Alto, CA, USA) ProteomeLab XL-I analytical ultracentrifuge using absorbance at 280 nm and interference optics. All AUC runs were carried out at a rotation speed of 45,000 rpm at 20°C using an 8-hole AnTi50 rotor and double-sector aluminium-Epon centrepieces. The sample volume was 400 ll and the sample concentrations ranged between 0. 3 and 1. 2 mg/ml. The partial specific volumes ( v) for the proteins were calculated from the amino acid sequence of NlpI, using the program SEDNTERP  (Laue et al, 1992). Sedimentation velocity profiles were treated using the size-distribution c(s) model implemented in the program SEDFIT14.
1  (Schuck, 2000). The experimental values of the sedimentation coefficient were corrected for the viscosity and density of the solvent, relative to that of H 2 O at 20°C (s 20,w ). The atomic coordinates from the published crystal structure of  (Wilson et al, 2005)  were used to calculate the sedimentation coefficient values for the monomer and dimer of NlpI using the program SoMo  (Brookes et al, 2010). In vitro PG digestion assays PG digestion assays and subsequent muropeptide composition analysis were carried out as previously described  (Glauner, 1988). 10% (v/v) substrate isolated from E. coli strain MC1061 was utilized in digestion reactions as follows: MepM (2 lM) AE NlpI (4 lM) incubated against intact sacculi for 4 h, MepS (5 lM) AE NlpI (10 lM) incubated against muropeptides O/N, PBP4 (2 lM) AE NlpI (4 lM) incubated against sacculi for 4 h, PBP7 (2 lM) AE NlpI (4 lM) incubated against muropeptides for 4 h.
A lock-mass correction with a background ion (mass/ charge ratio, 445. 12003) was applied. The raw mass spectrometry data were processed with MaxQuant (v1. 5. 2. 8;  Cox & Mann, 2008)  and searched against an Uniprot E. coli K12 proteome database. The search parameters were as following: carbamidomethyl (C) (fixed), acetyl (N-term) and oxidation (M) (variable) were used as modifications. For the full-scan MS spectra (MS1), the mass error tolerance was set to 20 ppm and for the MS/MS spectra (MS2) to 0. 5 Da. Trypsin was selected as protease with a maximum of two missed cleavages. For protein identification, a minimum of one unique peptide with a peptide length of at least seven amino acids and a false discovery rate below 0. 01 were required on the peptide and protein level. The match between runs function was enabled, and a time window of one minute was set.
Label-free quantification was selected using iBAQ (calculated as the sum of the intensities of the identified peptides and divided by the number of observable peptides of a protein)  (Schwanhausser et al, 2011) , with the log fit function enabled. The proteinGroups. txt file, an output of MaxQuant, was loaded into R (ISBN 3-900051-07-0) for further analysis. The iBAQ values of the MaxQuant output were first batch-corrected using the limma package  (Ritchie et al, 2015)  and then normalized with the vsn package  (Huber et al, 2002). Individual normalization coefficients were estimated for each biological condition separately. Limma was used again to test the normalized data for differential expression. Proteins were classified as a "hit" with a log 2 fold change higher than 4 and a "candidate" with a log 2 fold change higher than 2.
Colony integral opacity as fitness readout was quantified using the image analysis software Iris  (Kritikos et al, 2017). Doublemutant genetic interaction scores were calculated as previously described. Briefly, fitness ratios are calculated for all mutants by dividing their fitness values by the respective WT fitness value. The product of single mutant fitness ratios (expected) is compared to the double mutant fitness ratio (observed) across replicates. The probability that the two means (expected and observed) are equal across replicates is obtained by a Student's two-sample t-test.
Microscopy, cell width measurements For phase imaging and cell shape measurements, cells were grown and collected at steady state at 30°C at OD 600 %0. 1. Cells were concentrated 20 times, and 0. 4 ll was transferred to a 1% agarose pad (UltraPure Agarose; Invitrogen) prepared with LB and preheated at 30°C. The pad was supplemented with Carb 100 lg/ml and L-arabinose 0. 2% or glucose 0. 2% if specified. Phase images were obtained with an inverted epi-fluorescence Eclipse Ti microscope (Nikon), equipped with a 100× phase contrast objective (CFI PlanApo LambdaDM100X 1. 4NA, Nikon). Images were acquired using a sCMOS camera (Orca Flash 4. 0, Hamamatsu, Japan) with an effective pixel size of 65 nm. Cell boundaries were detected from phase-contrast microscopy images using the MATLAB-based cell segmentation tool Morphometrics (SimTK)  (Ursell et al, 2017).
Acknowledgements We thank  Manjula Reddy  for fruitful discussions and providing reagents. This work was supported by the  Sofja Kovalevskaja Award of the Alexander von Humboldt Foundation  and EMBL core funding to A. T. , the  Wellcome Trust  ( 101824/Z/13/Z ) and  Medical Research Council  ( MR/N002679/1 ) to V. W. M. B. is funded by the  Royal Society  ( RGS\R1\191041 ). A. M. is supported by a fellowship from the  EMBL Interdisciplinary Postdoc  ( EI3POD ) programme under  Marie Skłodowska-Curie Actions COFUND  (grant number  664726 ). M. W. was supported by a Humboldt postdoctoral fellowship. S. v. T received support from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  [Grant Agreement No. (679980)], the  French Government 's  Investissement d'Avenir program Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases"  ( ANR-10-LABX-62-IBEID ), the  Mairie de Paris "Emergence(s) " programme and the  Volkswagen Foundation.
This attenuated light was then compared to exo-atmospheric values that were recorded when the light source was sufficiently high above the atmosphere. This technique allows for high-precision measurements on the order of 5 %, as reported in the level 2 data product, for Published by Copernicus Publications on behalf of the European Geosciences Union. SAGE aerosol extinction in the main aerosol layer. In general, stratospheric aerosol extinction measurements are challenging due to the paucity of aerosols under background conditions and the ephemeral nature of ash and particulates injected directly from volcanic eruptions. However, occultation observations have the benefit of long path lengths (on the order of 100-1000 km, dependent on altitude). Further, due to the self-calibrating nature of this method, SAGE measurements are inherently stable (i.
Ground lidar Ground lidar data from three stations were used within this study. To allow intercomparison with both SAGE II and SAGE III, candidate ground stations with a long-duration data record were preferred. Further, data quality is likewise important. The Network for Detection of Atmospheric Composition Change (NDACC, https://www. ndacc. org, last access: 7 August 2020) was founded to observe long-term stratospheric trends by making long-term, high-quality atmospheric measurements. Therefore, stations within this network were selected for comparison. We identified three stations that satisfied the requirements of this analysis: Table  Mountain  Facility, Mauna Loa Observatory, and Observatoire de Haute-Provence. A brief description of the instruments and their algorithms is provided below.
Mauna Loa Observatory The NOAA Mauna Loa Observatory (MLO; 19. 5 • N, 155. 6 • W; alt. 3. 4 km) is located on the Big Island of Hawai'i. The dataset used here comes from the elastic and inelastic (Raman) backscatter channels of the JPL ozone DIAL that began measurements in 1993  (McDermid et al. , 1995; Mc-Dermid, 1995). Just like the JPL-TMF system, the lidar used the third harmonic of an Nd:YAG laser to record the elastic backscatter at 355 nm, followed by correction for ozone and NO 2 absorption, as well as Rayleigh extinction. The corrected backscatter was then used to calculate the aerosol backscatter coefficient from the backscatter ratio using the 387 nm channel as the purely molecular component in the BSR as described in  Chouza et al. (2020). The BSR was normalized to 1 at a constant altitude of 35 km where it was assumed that the aerosol backscatter contribution was negligible.
Methodology Extinction and backscatter observations cannot be directly compared. In order to evaluate the agreement between backscatter measurements and extinction coefficient measurements, the data types must be converted to a common parameter, thereby requiring a conversion algorithm. As previously mentioned, this is usually done by converting backscatter to extinction coefficients using conversion factors from sources independent of either instrument (e. g. , constant lidar ratio). Herein, we derive a process to infer this relationship based on the spectral dependence of SAGE II/III aerosol extinction coefficient measurements and only make basic assumptions on the character of the underlying aerosol. Indeed, this EBC method is proposed to act as a bridge between aerosol extinction and backscatter observations.
2. Though this figure only shows data for one combination of extinction and backscatter wavelengths, similar figures were generated for each combination (not shown), with the 520/1020 combination providing the best combination of linearity, atmospheric penetration depth, and wavelength overlap between SAGE II and SAGE III. This figure elucidates the relationship between the inverted lidar ratio (β/k, hereafter referred to as S -1 ), extinction ratio, and distribution width. Indeed, this figure provided the nexus between extinction and backscatter observations and between theory and observation since SAGEobserved extinctions were imported into this model to derive β 355. To do this, SAGE extinction ratios (k 520 /k 1020 ) were used to define the abscissa value, followed by identifying the ordinate value (S -1 ) according to the line drawn in Fig.
78-1. 02) and mean R 2 (0. 87-0. 98) had broad ranges, as did the corresponding standard deviations. However, when the dataset was limited to 15-31 km (values in parentheses) the range of mean slopes (0. 94-0. 99) and mean R 2 (0. 95-0. 98) decreased significantly, as did the corresponding standard deviations. It was observed that when the filtering criteria were in place the standard deviation significantly narrowed, in some cases by more than an order of magnitude. By considering only the mean slope and mean R 2 values the impact of the filtering criteria is partially masked. The influence of these criteria is better observed by considering the minimum and maximum values for both slope and R 2 and by considering its impact on the 95th percentile (P 95 ). Here, P 95 was calculated using a nontraditional method.