dataesr/scientific-paragraphs-categorization huggingface dataset:
Two complementary databases were used to identify these proteins and found that two proteins were redundant, i. e. , A0A2K9YND8_9APHY and the protein deduced from contig_4953, which shared 100% identity. No significant statistical differences were found between conditions with or without levofloxacin, meaning that the identified proteins may be involved in the levofloxacin modification process but that none of them were overproduced when the antibiotic was added to the culture medium. Among the 14 identified proteins, 6 proteins (from contigs Contig_9130, 12183, 1852, 1851, 18606, and 19718) were very poorly represented in the secretomes, and so were very unlikely to be involved in the levofloxacin modification process. Three other proteins were moderately produced (dye-decolorizing peroxidase/contig_16816, chloroperoxidaselike protein/contig_3046, and manganese-dependent peroxidase/contig_1800) and could be enzymes targeted for the levofloxacin modification as they were not strongly represented in the secretomes but their catalytic efficiency could be high.
Data Availability Statement: All data are available in the main text or the Supplementary Materials. The mass-spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD035019 and 10. 6019/PXD035019. ITS sequence of Coriolopsis gallica strain CLBE55 data were deposited in NCBI under accession number ON340792.
NMR Analysis Nuclear magnetic resonance (NMR) spectra were recorded on MAE fractions 10 and 11, and the NaBH 4 reduction product of MAE fraction 10. NMR experiments were acquired in CDCl 3 (EuroIsotop, Saint Aubin, France), at 300 K using a Bruker Avance DRX 500 NMR spectrometer (Karlsruhe, Germany) operating at 500. 13 MHz for 1 H and 125. 77 MHz for 13 C Larmor frequency with a double resonance broadband fluorine observe (BBFO) 5 mm probe head. 13 C-NMR experiments were recorded using a one-pulse excitation pulse sequence (90 • excitation pulse) with 1 H decoupling during signal acquisition (performed with WALTZ-16); the relaxation delay has been set at 2 s. For each analyzed sample, depending on the compound concentration, 3 up to 5 k free induction decay (FID) 64 k complex data points were collected using a spectral width of 30,000 Hz (240 ppm).
Statistical analysis The original data involved 1,050 E. coli strains on which 68 genetic variables were measured (i. e. , phylogroup, serotype and 66 virulence markers). Our aim was to predict the virulence status (i. e. , virulent/non-virulent) of the strains; therefore, statistical analyses were applied to a subset of 373 E. coli strains (i. e. , 170 presumed non-virulent strains from no-colibacillosis farm environments (controls), and 203 presumed virulent strains obtained from colibacillosis lesions from actual colibacillosis cases on chicken farms). The 203 presumed virulent strains had been isolated during early colibacillosis cases (138 isolates) or late colibacillosis cases (65 isolates). The prediction (response) variable is Boolean, designed to predict the virulence status (i. e.
Title: SNP4OrphanSpecies Design description: The method to isolate single-copy genes for orphan species is based on an automated de novo genome assembly without the step of manual curation, using sequence data generated by paired-end Illumina sequencing technology. The assembly quality is checked by looking at some summary statistics (i. e. genome size, degree of assembly fragmentation, completeness of the genome). For isolating hundreds of SNPs, we focused on the single-copy genes conserved in genomes at a given taxonomic level (i. e. genus, family or order). The focus on these conserved genes allows us: 1) to control for the taxonomic assignment of the analysed genomic regions, 2) to remove duplicated genes in the genome which can produce possible false positive SNPs, 3) to isolate several SNPs generally present in the introns of these genes and 4) to yield several pools of pairs of primers for amplification of around 400 bp sequences which can be amplified together in one multiplex (100 sequences per pool).
2019 ). This step starts with a quality analysis of the raw data using FastQC v. 0. 11. 9 (https://www. bioinformatics. babraham. ac. uk/projects/fastqc/). Reads are trimmed by using a sliding window and filtered using a minimum length with the software trimmomatic v. 0. 39  (Bolger et al. 2014). The parameters for trimming are defined in the parameter file of the pipeline (Snakemake_Config_SNP4OrphanSpecies. yaml). Then a de novo assembly is performed using IDBA-UD v. 1. 1. 3 (Peng et al. 2010). A basic statistics report is then generated on the final assembly using Quast v. 5. 0. 2  (Gurevich et al. 2013). For fungi, bacteria and viruses only, detection for DNA contamination can be performed by an automatic assignation of the assembled contigs, using  Kaiju v. 1. 7. 4 (Menzel et al. 2016).
Optionally, a taxonomic assignment of the selected genes can be done using Kaiju. Genes assigned to taxon other than the taxon set in the configuration file are removed from the final selection. This verification step requires large disc spaces (ideally 125 GB for the nr_euk database) and is possible only for fungi, bacteria and viruses. The last step of the pipeline is the isolation of amplicons to be amplified in pools. For this step, the amplicons are chosen to encompass at least one intron in the sequence. For each amplicon, a pair of primers is designed using a home-made Perl script integrating the programme Primer3 (v. 2. 5 Koressaar and Remm 2007), with stringent parameters favouring the possibility to be amplified jointly in a single multiplex PCR. All the designed primers are subjected to  BLASTn (v.
Implements specification Keeping in mind biologist users, we implemented this pipeline with Snakemake (Köster and Rahmann 2012) and Singularity  (Kurtzer et al. 2017). These softwares allow us to organise the whole bioinformatics workflow within a container, with all software and libraries needed and the automatic achievement of each step of the analysis from the initial input data. This pipeline is easy to install, easy to use and can be run on all Linux machines, including highperformance clusters. The pipeline, its associated notice and parameter files can be downloaded from the Portail Data INRAE (https://doi. org/10. 15454/GWKRKY). For running the pipeline, users only must: 1) produce a paired-end Illumina whole-genome sequencing of the species of interest and 2) set parameters (i. e.
These genome assemblies were strongly fragmented with small L50 and large N50 values (Table  1 ). As expected for contaminated DNA extraction  (Dutech et al. 2020) , the E. alphitoides genome assembly was one of the most fragmented genomes together with T. pityocampa. It confirmed the originally published surprisingly large estimate of the genome size for a powdery mildew species (317 Mb vs. less than 110 Mb for other published powdery mildew genome assemblies; Frantzeskakis et al. 2019). For fungal species, identifying the ITS1 sequences using the Kaiju nr_euk database confirmed that at least a part of the genome assembly may be assigned to the expected genus for each sequenced species (Suppl. material 1). The software ITSx used for this identification detected several ITS1 haplotypes in the E.
alphitoides genome, which is congruent with the detection of several contigs of the genome assigned to different phyla or fungal families (Suppl. material 2). Between 98. 6% (D. sapinea) and 42% (T. pityocampa) of conserved singlecopy genes listed in the Busco database were isolated from the genome assemblies (Table  2 ). For the analysed fungal species and using Kaiju, a variable proportion of genes was actually identified as different from the targeted genus, leading to the removal of between 70% (E. alphitoides) and 0. 6% (A. ostoyae) of the initial list of single-copy genes. In the last steps of the analysis, the pipeline defined in each species between 20,991 (A. ostoyae) and 1,829 (E. alphitoides) short 400 bp sequences (i. e. amplicons), encompassing at least one intron region. The design of the primer pairs for DNA amplification for each amplicon (only one per gene) and the control for their potential duplication in the genomes yielded a final set of between 614 (E.
Perspectives for evolutionary genetic studies of non-model invasive and emergent insect and pathogen species The analysis of genomes from different phyla suggested that the method can be used for a large number of invasive or emergent insect and pathogen species for which genetic markers are searched. Some limitations may occur for large genomes (i. e. several hundreds Mb), since the assembly, even without any curation steps, requires a minimum of computation resources. For example, the analysis of the T. pityocampa genome for which the size was estimated to be more than 500 Mb, generated 268 GB (only 134 GB for the trimmed fastaQ files) and took more than 18 hrs on a Linux cluster using 20 CPUs. For such a large genome, it could be interesting to assess the method with a reduced wholegenome sequencing (i.
Using the Kaiju nr_euk database to assign the identified genes is then useful to detect this DNA contamination and discard the sequences with the incorrect taxonomic assignment. For the identification of conserved single-copy genes, a taxonomic determination is a sensitive parameter. An incorrect taxonomic identification at the genus level or higher of the emergent species may lead us to discard several BUSCO genes present in the genome assembly, but too different from the chosen reference genome. Conversely, if BUSCO genes are searched at a taxonomical level that includes the emergent species and a contaminating related species, some BUSCO genes non-specific to the emergent species may be selected despite the control performed by Kaiju. To avoid the selection of these unspecific genes, the isolated BUSCO genes can be evaluated again before the step of primers design.
This evaluation can be done using the fasta files of the isolated genes (available in the outputs of the pipeline) and a phylogenetic reconstruction for each gene by extracting BUSCO genes of the taxonomical group studied from a database (for example, Mycocosm; Grigoriev et al. 2013) and the use of one of the numerous published phylogenetic software (see, for example,  Dereeper et al. 2008). Two strategies can then be developed after the isolation of these amplicons. The first one would be sequencing hundreds of samples using one of the designed pools and nextgeneration sequencers. The combination of SNPs identified in each amplicon can be treated as microhaplotypes (i. e. multi-SNP loci), potentially giving more power for population genetic analyses than analysing independent bi-allelic SNP loci  (Baetscher et al.
Acknowledgements We thank  Pedro Crous  ( Westerdijk Fungal Biodiversity Institute, The Netherlands ) for providing us with the Diplodia sapinea isolate and  G. Sypos  and  C. Simang  ( University of Sopron, Hungary ) for having sent us the raw sequencing data of the C17 Armillaria isolate genome. We also thank  O. Lepais  and the two reviewers for their comments on the previous versions of this manuscript that have greatly improved the quality of this manuscript. The genome sequencing of the Diplodia isolate was performed in collaboration with the  GeT core facility, Toulouse, France  (http://get. genotoul. fr). GeT was supported by  France Génomique National  infrastructure, funded as part of " Investissement d'avenir " programme managed by  Agence Nationale pour la Recherche  (contract  ANR-10-INBS-09 ).
Preliminary tests were performed at the  Genome Transcriptome Facility of Bordeaux  (grants from the  Conseil Regional d'Aquitaine n°20030304002FA  and  20040305003FA , the  European Union ,  FEDER  n°2003227 and Investissements d'avenir,  N°ANR-10-EQPX-16-01 ). Parts of the computational resources and infrastructure used in the present publication were provided by the  Bordeaux Bioinformatics Center (CbiB). This research has benefitted from the  European HOMED project  and received funding from the  European Union 's  Horizon 2020 Research and Innovation Programme  under grant agreement  N°771271.
3. Figures  3c  and 3d  present the comparison between experimental data and model results performed with n o = 0. 3 for tracers that were installed in the first layer below the surface, but were then found on the surface (Figure  3c ) and buried in the deposit (Figure  3d ) after 15 min. The excel files with the experimental data and the comparisons between experimental and model results are stored with the model and the documentation at https://github. com/vipenrica/tracer-stone-modeling. The 10 estimates of n o are plotted as a function of the Shields number τ* in Figure  4 , where the black line represents a linear fit of the data with equation  = -28. 67 * + 3. 15 (18) The points in Figure  4  show that as the bedload transport rate, and thus the Shields number, increases, the maximum probability of entrainment seems to migrate downward in the bed deposit.
(2007)  experiments is representative of a condition in which particles are in transport. This, however, creates two important issues of ambiguity. First, the average bed height may be calculated using position data of moving particles measured as they pass beneath the sensor. Thus, the measured bed elevation value may be higher than the actual bed. Second, the position of the static bed (and thus of the recovered tracers) at the beginning and at the end of a tracer experiment is likely to be somewhat higher than the position of the mobile bed because the particles in transport drop to the bed when the water no longer flows. In other words, the experimental particle entrainment location data are based on incremental numbers of particle diameters relative to the static surface. If the static bed height is higher than the mobile bed height, the entrained tracer particles are higher in the mobile bed than documented.
Data Availability Statement Python scripts with the version of the model for applications in the laboratory and in the field, the data by  Wong et al. (2007)  and  Brousse et al. (2019)  and the excel files with the model validation at laboratory scale are available through the repository of the Community Surface Dynamics Modeling System (CSDMS; https://csdms. colorado. edu/wiki/Model:Tracer_dispersion_calculator). Halfmoon Creek data (Bradley, 2017a)  are available as Supporting Information and downloadable at https://doi. org/10. 1002/2017GL075045.
Acknowledgments The authors thank Miguel Wong who provided the data many years ago, Guillaume Brousse and Guillaume Fantino for providing the raw data of the RFID tags he introduced into the Buëch in 2018 as part of his thesis work, Nate Bradley for providing information on the variability of bed elevations and a picture of the Halfmoon Creek field site, G. Parker and two anonymous reviewers for comments and suggestions that helped to improve the manuscript. This work was partially supported by an Exxon Mobil grant. Amanda Balkus was supported with a REU supplement to the NSF Grant CBET 1751926.
Cadmium seaweed contamination data The dataset included data from French Annual Monitoring and Control Plan (FAMCP database), the Centre for Study and Promotion of Algae (CEVA) in France and the scientific literature. One hundred and thirty-one samples of seaweed (macroalgae, microalgae e. g spirulina, and halophytes e. g glasswort) were collected through the French Annual Monitoring and Control Plan between 2009 and 2017 (FAMCP database), including seaweed harvested in France and imported seaweed often of unknown origin. Samples were composed by seaweeds used as such (fresh, dried or roasted), as a food ingredient (agar-agar, beverages) and as a food supplement The Centre for Study and Promotion of Algae (CEVA) also measured the cadmium levels in one-hundred and seventy-two samples of seaweed collected in France.
These samples were analysed in dried form between 1996 and 2016 by the ICP-MS method (contamination data provided by CEVA to ANSES; unreferenced). In addition, an optimized and validated ICP-MS method was employed by Rodenas de la  Rocha et al. (2009)  and thus cadmium contamination data from eight seaweeds in this study were also retained. Results came from analysis of samples of seaweeds from France, Spain, Korea, and Japan. From these three sources of information, we were able to produce a dataset including a total of three hundred and eleven contamination data of cadmium in seaweeds. Contaminations originally expressed as wet weight were converted in dry matter using a conversion factor defined from the literature (Arne  Jensen 1993; Stévant et al. 2017; Qing Chen et al. 2018; Roleda et al.
French seaweed consumption data Our study covered several types of edible seaweeds, such as (i) intended for direct human consumption as food (condiment or vegetable); (ii) used as an ingredient in foodstuffs; and (iii) used in food supplements. Data on the consumption of edible seaweeds and seaweed-based ingredients, as well as on food supplements containing seaweed, were obtained from the third French Individual and National Study on Food Consumption (INCA 3) (ANSES 2017). Information on the food consumption of individuals was collected over three non-consecutive days (2 weekdays and 1 weekend day) spread over around three weeks, using the 24-h recall method for individuals aged from 15 to 79 years, and the 24-h record method for individuals aged from 0 to 14 years. For the three selected days, the individuals were asked to describe their food consumption by identifying all the foods and beverages consumed during the previous day and night.
Of the 5855 individuals (2698 children from birth to age 17 and 3157 adults between the ages of 18 and 79) participating in the study, 4114 (1993 children and 2121 adults) validated the consumption part by taking part in at least two food interviews. The data on food supplement consumption collected in the INCA 3 study included drugs that can provide nutrients, and plant extracts. Data on food supplement consumption was collected for the 5855 participants in the INCA 3 study. For each product mentioned, the name, brand, form of presentation, place of purchase, frequency of consumption and quantity consumed were documented. Concerning the data on food supplement composition, the packaging of the food supplements consumed was collected by the investigators when possible. Foods labelled "seaweed" and "glasswort" in the INCA 3 study were selected as edible seaweed.
Estimation of cadmium dietary exposure for French edible seaweed consumers Dietary cadmium exposure for seaweed consumers were obtained using the combination of the consumption and individual weight data from INCA 3 (ANSES 2017) with seaweeds cadmium contamination data  (CEVA (1996 (CEVA ( -2016)) , Rodenas de la  Rocha et al. (2009 ), French Annual Monitoring and Control Plan -FAMCP database (2009 -2017). Dietary exposure to cadmium in seaweed consumers was estimated on the basis of the following four consumption scenarios, considering: (i) Seaweed consumed directly as a food as such without processing (vegetable or condiment), (ii) Seaweed consumed as an ingredient in foodstuffs (maki, California roll), (iii) Seaweed consumed as a food supplement ingredient and (iv) Seaweed consumed in all its forms (food, ingredient, food supplement).
Estimation of maximum cadmium level in seaweed intended for human consumption taking into account the total diet exposure of French consumers The maximum cadmium concentration in edible seaweed was calculated so as not to increase the initial dietary cadmium exposure of seaweed consumers compared to the oral health-based guidance value (HBGV) for cadmium. ANSES (2019) has established a tolerable daily intake (TDI) of 0. 35 µg Cd kg bw -1 d -1 resulting in a urinary cadmium concentration of 0. 5 μg g -1 creatinine, in a 60-year-old adult, assuming that ingestion is the sole source of cadmium exposure  (Leconte et al. 2021). Data from TDS2 (ANSES 2011a) provided a distribution of cadmium exposure of the French general population. These data reflected the baseline exposure of the population, also known as "background exposure", i.
Description of the cadmium levels in seaweed Out of 131 samples analysed from FAMCP database, the levels measured in 26 samples were less than the quantification/LOQ (n = 17) or detection limit/LOD (n = 9) (the LOD/LOQ were between 0. 001 and 0. 090 mg kg -1 of dry matter (DM)). Out of these 131 analysed samples, 39 analytical results concerned macroalgae (brown, red, green) used as such, while 11 and 3 analytical results concerned microalgae (spirulina only) and halophytes (glasswort only) respectively. The seaweed genus was unspecified or unknown for 20 of the analysed samples. Fifty-three analytical results were linked to food supplements containing seaweed. Two samples of seaweed mixtures, one sample of seaweed powder, one sample of agar-agar and one sample of seaweed-based beverage analysed for cadmium were present in the FAMCP database.
The groups of seaweed, or food containing seaweed, analysed, in increasing order of percentage, were as follows: food supplements (FS) (40. 5%) > unknown seaweed (15. 3%) > brown macroalgae (13%) = red macroalgae (13%) > microalgae (spirulina) (8. 4%) > green macroalgae (3. 8%) > halophytes (glasswort) (2. 3%; n = 3) > seaweed mixtures (1. 5%; n = 2) > powder, agar-agar and beverages (0. 8% each (n = 1 each)). The mean and median cadmium contamination levels of all seaweed combined from FAMCP database, excluding food supplements, agar-agar, beverages and seaweed powder, were 1. 07 and 0. 23 mg kg -1 DM, respectively (min-max 0. 001-9. 4 mg Cd kg -1 DM). Red, brown macroalgae and unknown seaweed were the most contaminated with cadmium, with mean values above 1. 14 mg kg -1 DM. A maximum cadmium level of 9.
Estimated cadmium dietary exposure of French edible seaweed consumers Data used to estimate dietary cadmium exposure for French edible seaweed consumers according to several scenarios are presented in For adults consumers, the consumption occasions of seaweed as a food, as an ingredient and as a food supplement were considered for estimating the associated cadmium exposures whereas for children, due to the lack of consumption data, only there eating occasions of seaweed as an ingredient were taking into account. Probability distribution of cadmium dietary exposure to seaweed consumers for each scenario are generated with probability distributions defined in For French adult seaweed consumers, exposure to cadmium by seaweed consumed as a food (condiment or vegetable) represented on average about 16% of the TDI.
Limitation of the overexposure of French consumers to cadmium due to the emergence of seaweed consumption To limit the high exposure of the general population to cadmium, establishing or strengthening management measures is necessary. The case of cadmium and emerging seaweed consumption in the French population due to fashion and possibly to sustainability claims raises the issue of risk management. In our study, almost a quarter of our dataset of 255 cadmium contamination data in unprocessed seaweed (26%) exceeded 0. 5 mg Cd kg -1 DM as recommended by CSHPF in France (68 samples including 29 samples of seaweed from FAMCP database). Higher cadmium levels were found for brown and red macroalgae (Table  A1  and A2 in appendices). Cadmium levels higher than 0. 5 mg Cd kg -1 DM are also highlighted in the literature linked to the strong Otherwise, the levels of cadmium contamination measured in the food supplements samples (n=53) did not exceed the regulatory maximum cadmium levels of 3.