dataesr/scientific-paragraphs-categorization huggingface dataset:
Phylogenetic analyses We considered three distinct genomic components for phylogenetic analyses mitochondrial DNA, W chromosome and autosomes. Due to the haploid (female) or diploid (male) status of the Z chromosome in our dataset, it was discarded in the phylogenetic analyses. Sequence alignments were created by projecting SNPs on the G. gallus reference genome (galGal5 assembly) and include both variant and invariant sites. For the autosomal compartment, we removed G. sonneratii sequences detected as introgressed from G. gallus (see Introgressed Regions) and replaced them with N prior to inference. Since the W chromosome and the mitochondrial are transmitted as a single block, we conserved them in introgressed samples.
Briefly, the population level data of autosomal chromosomes were obtained from the vcf file using the vcf2smc utility of smc++. To avoid spurious runs of homozygosity caused by large uncalled regions, we masked all regions where the median coverage was lower than 7x using the -m option. We then ran smc++ with default parameters and a per generation mutation rate of μ = 1. 91 × 10 -9  (Nam et al. , 2010) , like in the psmc analysis. Finally, we used smc++ in split mode to estimate divergence times between G. sonneratii, G. lafayettii and G. gallus. G. varius was left out of splitanalyses as there are only two samples including the one with lowest coverage and highest fraction of missing data.
Distance-based method The neighbor joining tree obtained from the autosomal data (Fig. 2a ) revealed a first separation of G. varius from the other species and a second separation that divided the G. sonneratii and G. lafayettii from the G. gallus. All nodes were well supported with bootstrap values (BP) of 100% and each Gallus species formed a monophyletic clade. The three G. sonneratii samples issued from zoological parks clustered with the wild ones. The phylogenetic trees of the W chromosome (Fig. 2b ) and of the whole mitochondrial genome (Fig. 2c ) both differed from the autosomal tree with the G. varius branching with the G. gallus cluster (100% BP). The trees revealed also that in our dataset the three G. sonneratii samples collected in zoological parks were clustered with the G. gallus, while the wild G.
In fact, high bootstrap values become irrelevant as the sheer size of the dataset means that systematic errors dominate stochastic and sampling errors  (Young and Gillung, 2020). There are some modeling differences between our approach and  Lawal et al. (2020). First,  Lawal et al. (2020)  reconstruct a neighbor joining tree on whole-genome data after doing SNP thinning (at most 1 SNP/kb). Note that we find the same topology when using the same method without SNP thinning (Fig. 2a ). Second their ML tree is reconstructed using the GTR model on exon SNPs whereas we use GTR + CAT on full gene sequences. The CAT variant of GTR models rate heterogeneity across sites (RAS) and downweights rapidly evolving sites. With a parameter α estimated equal to 0. 02, the sites evolve at markedly different rates.
Acknowledgements This work was supported by the  French research agency (ANR)  [grant name Domestichick, grant number  ANR-12-BSV6-0018 ]. We are grateful to the  INRAE MIGALE bioinformatics platform  (http://migale. inrae. fr)for providing computational resources and  Jean-Claude Fotsa  for providing the sample of a village chicken from  Cameroun. Marie Suez  was also partially supported by the  CRB-Anim infrastructure  project,  ANR-11-INBS-0003 , funded by the  French National Research Agency  in the frame of the ' Investing for the Future' program.
Data Calculations and Statistical Analyses Empty body weight (EBW) was calculated by subtracting the weight of the gut content from the slaughter weight. The carcass yield was the weight of cold carcass related to EBW. The FA were summed by families according to their structure: even straight-chain saturated FA (ESFA) = C10:0 + C12:0 + C14:0 + C16:0 + C18:0 + C20:0 + C22:0 + C24:0; oddnumbered straight-chain FA (odd FA) = C13:0 + C15:0 + C17:0 + C17:1n-8 + C19:0 + C21:0; methyl-branched chain FA of the iso and anteiso forms, (isoFA and anteisoFA) = isoC14:0 + isoC15:0 + anteisoC15:0 + isoC16:0 + isoC17:0 + anteisoC17:0; straight-chain monounsaturated FA (MUFA) = C14:1 + C16:1 (n-9 and n-7) + C18:1 (n-7, n-9, trans-10) + C17:1n-8 + C20:1 + C22:1 + C24:1; n-3 FA = C18:3n-3 + C20:3n-3 + C20:5n-3 + C22:5n-3 + C22:6n-3; n-6 FA= C18:2n-6 + C18:3n-6 + C20:2n-6 + C20:3n-6 + C20:4n-6 + C22:4n-6; and polyunsaturated FA (PUFA) = n-3 FA + n-6 FA.
Data were analyzed using PROC GLM (Version 9, SAS Inst. , Inc. , Cary, NC, 1999) with diet, age at slaughter, and interaction diet * age as the main effects in the model. The statistical unit was the animal. Initial LW and slaughter weight were used as co-variables for ADG and carcass traits. Co-variables were kept in the model when significant. Carcass quality scores and cut weights were studied with carcass weight used as a co-variable, which was only kept in the model when significant.
Thus, the improvement of the nutritional level remains necessary to increase animal performances. The present experiment was designed to measure the effect of supplementation in a forage feeding system on Creole buck performances. We evaluated the influence of age at slaughter since forage finishing result in lower growth rate and consequently longer fattening periods. As expected, the inclusion of 50% concentrate in the diet was responsible for ∼80% of the increase of the ADG and slaughter performances (i. e. , 75-80% of increases for the weights of the carcasses, prime cuts, and muscles and 50% for conformation score), but the range of variations observed were relatively large compared to data reported for other tropical breeds  (5, (25) (26) (27). It is largely admitted that for tissue partitioning and consequently their effects on quality, the maximum growth rate is reached firstly by bone, secondly by muscle, and lastly by fatty tissue  (28).
Fatty acid profile of hemp seed OBs The fatty acid profile was determined by a gas chromatography (GC) procedure after methylation with cold methanolic solution of potassium hydroxide. The fatty acid methyl esters (FAME) were analyzed by GC (Focus GC, Thermo Electron Corporation, Massachusetts, USA) equipped with a split injector (ratio of 1/20), a CPCil 88 Varian capillary column (50 m × 0. 25 mm with a 0. 2-μm thick film; Chrompack, Middelburg, The Netherlands) and 1 mL/min of helium as carrier gas. FAME were analyzed using a flame ionization detector and ChromCard Data System (version 2005; Thermo Electron Corporation, Massachusetts, USA). The FAME were identified using a mixture of methyl esters as external standard (Mixture ME 100, Larodan, Sweden). The GC analysis was performed in triplicate for each Folch extract of total lipids from hemp seed OBs.
Acknowledgements Christelle Lopez thanks all the  UR BIA 's members involved in the "hemp project" for stimulating discussions. The authors warmly thank  Alain Riaublanc  and  Adeline Boire  ( INRAE, BIA, ISD, Nantes, France ) for interesting discussions about hemp seed proteins and protein bodies. Valérie Beaumal  and  Elisabeth David-Briand  ( INRAE, BIA, ISD, Nantes, France ) are acknowledged for help in particle size and zeta potential measurements. Yann Gohon  ( Institut Jean-Pierre Bourgin, Versailles, France ) is acknowledged for interesting discussions about the partitioning of TAGs and steryl esters within the core of oil bodies. Iterg ( Canejan, France ) is acknowledged for pertinent discussions about lipid analyses.
To further elucidate the sessile, nonmotile properties of certain evolved isolates, in vitro biofilm formation was assayed under different scenarios. Pellicle biofilm formed at the air-liquid interface generally requires motility as a pivotal factor during formation  (57). As expected, pellicle formation in LBGM (58, 59) (LB with glycerol and MnSO 4 ) medium was greatly reduced in the evolved lineages E and F, providing additional evidence for pellicle formation being heavily dependent on swimming motility (Fig. S4A ). Pellicles in evolved lineage A showed partial impairment, potentially indicating that pellicle formation could also be linked to other altered traits. Next, the isolates were tested for submerged biofilm development at the plastic surface under slight shaking conditions. Both imaging and quantitative data demonstrated a significantly lower degree of submerged biofilm formation in lineages E and F, compared to the ancestor and other EE lineages (Fig.
Genomic analysis reveals key mutations related to evolutionary adaptation. To identify whether evolved isolates harbored mutations responsible for the observed evolved phenotypic properties, whole-genome sequencing (WGS) analysis was carried out on three isolates from each evolved lineage and the ancestor. The analysis revealed a total of 58 mutations on the chromosome, most of which are nonsynonymous and assigned to specific genes. Most mutations that were identified in all three isolates of a certain lineage were related to metabolic processes such as peptidoglycan and amino acid metabolism (see Data Set S1 in the supplemental material). Specifically, mutations in evolved lineages A, C, and D were present in genes related to peptidoglycan/cell wall metabolism. In contrast, lineages E and F harbored mutations in genes related to transcription and translation, which led to the hypothesis that certain genes (e.
After incubation at 37°C for 24 h, the mortality of each group was recorded. The LD 50 of each strain was evaluated based on mortality data and calculated by the probit regression analysis employing IBM SPSS Statistics 20. Microscopy. For bright-field images of pellicles and colonies, Axio Zoom V16 stereomicroscope (Carl Zeiss) was used, equipped with a Zeiss CL 9000 LED light source, a PlanApo Z 0. 5Â objective, and AxioCam MRm monochrome camera (Carl Zeiss). Confocal laser scanning microscopy imaging was performed as described previously  (50). For rootattached biofilms, colonized plants were washed twice with sterilized double-distilled water (ddH 2 O) and placed onto glass slides. Images were obtained using a 63Â/1. 4 oil objective. Fluorescent reporter excitation was performed with the argon laser at 488 nm, and the emitted fluorescence was recorded at 484 to 536 nm and 567 to 654 nm for GFP and mKate, respectively.
Z-stack series were performed with 1-mm steps, and stacks were merged using ImageJ software. For cryo-electron microscopy imaging, bacteria were grown overnight at 30°C, OD 600 was adjusted to 1 using NaCl buffer (0. 9%), 1-ml portions of the adjusted cultures were centrifuged washed three times using NaCl buffer (0. 9%), and the resulting cell pellets were subjected to cryo-SEM analysis. Cryofixation was performed via high-pressure freezing (HPF) before cryo-SEM. The HPF was performed by the HPF instrument HPM100 (Leica Microsystems) in standard conditions. After freezing, the sample was mounted into a cryo-sample holder in liquid nitrogen attached to a Leica VCT100 cryo transfer arm (Leica Microsystems) and transferred into a Leica MED020 freeze fracture and coating system. After the freeze fracturing in the MED20 cryo-preparation chamber (Leica Microsystems), the biofilm freezing samples were sublimated at 290°C for about 90 s and coated with 6 nm of a C/Pt alloy.
Primary data analysis (base calling) was carried out with "bcl2fastq" software (v2. 17. 1. 14; Illumina). All further analysis steps were done in CLC Genomics Workbench Tool 9. 5. 1. Reads were quality trimmed using an error probability of 0. 05 (Q13) as the threshold. In addition, the first 10 bases of each read were removed. Reads that displayed $80% similarity to the reference over $80% of their read lengths were used in the mapping. Nonspecific reads were randomly placed to one of their possible genomic locations. Quality-based single nucleotide polymorphism (SNP) and small in/del variant calling was carried out requiring $8Â read coverage with $25% variant frequency. Only variants supported by good-quality bases (Q $ 20) were considered and only when they were supported by evidence from both DNA strands in comparison to the B.
thuringiensis Bt407 genome (GenBank accession number CP003889. 1). Identified mutations in each strain are listed in Data Set S1 in the supplemental material. Raw sequencing data have been deposited to the NCBI Sequence Read Archive (SRA) database under BioProject accession number PRJNA673616. RNA extraction and transcriptome analysis. Overnight-grown strains were diluted to an OD 600 of 1. 0 in LB medium and grown to late-log phase, and cultures were collected by centrifugation and flash frozen in liquid nitrogen. Total RNA was extracted by combining phenol-chloroform-isopropanol treatment using the High Pure RNA isolation kit (Roche, Germany)  (102). The concentration and quality of extracted RNA were examined by Nanodrop and Agilent RNA 6000 Nano Chips. Ribo-off rRNA Depletion kit (Bacteria) (Vazyme Biotech) was used to deplete rRNA.
Read pairs for which both mates passed the quality control (QC) checks were recovered using cmpfastq. pl (https:// toolshed. g2. bx. psu. edu/repos/amol/cmpfastq), were generated, followed by differential gene expression analyses using Trinity 2. 10. 0 with RSEM 1. 3. 3 to estimate gene/transcript abundances and DESeq2 v1. 22. 2 run in R 3. 5. 3 (http://www. R-project. org/) for statistical testing  (104). In RSEM, the bowtie2 (105) v2. 4. 1 aligner was employed to map (with a maximum insert size of 1,000; "-max_ins_size 1000") the read pairs onto the annotated protein-coding (coding DNA sequence [CDS]) transcript sequences of Bt407 (GenBank: GCF_000306745. 1, file "cds_from_genomic. fna"). Genes that have P values adjusted for multiple testing (adjusted P value [P adj ]; corresponding to the false discovery rate [FDR]) # 5% were considered DEGs and included for further analysis (Data Set S2).
A heatmap with hierarchical tree clustering of genes and replicate samples according to gene expression profiles was computed using the "ana-lyze_diff_expr. pl" utility script in Trinity. For that, gene/transcript abundances were converted (with the "run_TMM_normalization_write_FPKM_matrix. pl" utility) to TMM-normalized (trimmed mean of M values) FPKM (fragment per kilobase per million mapped reads) expression values. The Pearson correlation coefficient was chosen as the distance metric, and average linkage was chosen as the clustering method (options "-sample_dist sample_cor -sample_cor pearson -sample_clust average"). A log 2 cutoff of 0 and a P value cutoff of 0. 05 were set ("-C 0 P 0. 05") to select DEGs (other options included "-min_rowSums 10 -min_colSums 0"). Functional analysis of DEGs was carried out using the Genome2D webserver (106) and GSEA-Pro v3.
0 webserver (http://gseapro. molgenrug. nl/), combining FACoP (http://facop. molgenrug. nl/) and database (UniProt and SubtiWiki) information (Data Set S3). Raw sequencing data have been deposited to the NCBI Sequence Read Archive (SRA) database under BioProject accession number PRJNA673582. Statistical analysis. Unless indicated otherwise, all experiments were performed with at least three biological replicates. Statistical analysis of bacterial trait comparison between evolved isolates and the ancestor (e. g. , root colonization assays) was analyzed and illustrated using GraphPad Prism 8. Specifically, the statistical differences were calculated using Student's t test with Welch's correction (assuming unequal standard deviations [SD]). For comparison across multiple groups (e. g. , comparison among the ancestor, evolved strain E, and constructed rho mutant), ordinary one-way analysis of variance (ANOVA) analysis and Tukey tests were employed.
ACKNOWLEDGMENTS Y. L. was supported by a  Chinese Scholarship Council fellowship. G. M. was supported by the  Lendület-Program  of the  Hungarian Academy of Sciences  ( LP2020-5/2020 ). All authors contributed to, and approved, the final version of the paper. Y. L. and Á. T. K. conceived the project. Y. L. performed the experiments and analyzed the data. M. A. and J. K. Y. P. constructed the rho mutant. M. E. -R. performed SEM. Y. L. and N. T. performed the RNA-Seq analysis. O. A. Ø. and G. M. provided resources and analysis methods. Á. T. K. supervised the project. Y. L. and Á. T. K. wrote the manuscript with input from all authors.
Data availability. Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Ákos T. Kovács (atkovacs@dtu. dk). Identified mutations, normalized transcriptome data are available in Data Sets S1 to S3, while raw sequencing reads have been submitted to NCBI Sequence Read Archive (SRA) database under BioProject accession numbers PRJNA673616 and PRJNA673582 (see above).
ESBL Resistance Gene Screening Extended-spectrum beta-lactamase-encoding genes were screened by polymerase chain reaction (PCR). On the basis of previous epidemiological evidence for ECC in the community, PCR was performed only for bla CTX-M group 1  (Dallenne et al. , 2010; Guyomard-Rabenirina, 2016). Amplicons were sequenced at Eurofins (Eurofins Genomic SAS, Les Ullis, France). Resistance genes were identified from the ResFinder database  (Zankari et al. , 2012).
ECC hsp60 Typing As ECC members cannot be differentiated reliably with classic identification methods, we conducted sequence analysis of the partial hsp60 gene, as described previously on 313 local strains  (Hoffmann and Roggenkamp, 2003). PCR products were sequenced at Eurofins, and DNA sequences and chromatograms were analyzed with ApE software 2. Maximum likelihood phylogenetic reconstruction was performed with RAxML in 100 replications  (Stamatakis, 2014). The tree was drawn with iTOL  (Letunic and Bork, 2019)  and rooted with Klebsiella aerogenes hsp60 partial sequence (AB008141. 1; Hoffmann and Roggenkamp, 2003). Accession numbers for previously identified hps60 cluster sequences are listed in Supplementary Figure  1. To complete the analysis, hsp60 partial sequences were extracted from the assembled genomes of ECC ST873 strains, characterized, and added as a new ECC cluster (C-XIV -Clade S;  Beyrouthy et al.
Core-Genome Phylogenetic Analyses To better describe possible circulation of ECC lineages collected from animals, fresh food, raw water, and humans and to gain understanding of the emergence of 3GC-R ECC from nonhuman samples, WGS was conducted on randomly selected strains in the two most prevalent hsp60 clusters: C-VI (n = 45) and C-VIII (n = 86). Their origins were: 47 from Anolis, 5 from domestic animals, 14 from fresh produce, 10 from raw water samples, and 55 from human isolates. WGS was performed at the "Plateforme de microbiologie mutualisée" of the Pasteur International Bioresources network (Institut Pasteur, Paris, France). The method and software used for sequencing, quality checking and core-genome extraction were described previously  (Guyomard-Rabenirina et al. , 2020). Raw reads were trimmed and filtered with AlienTrimmer  (Criscuolo and Brisse, 2014).
Genomes were assembled with SPAdes software  (Bankevich et al. , 2012) , and final quality was appreciated with QUAST and BUSCO score  (Gurevich et al. , 2013; Simão et al. , 2015). Total core single nucleotide polymorphisms (SNPs) were detected with Snippy software version 4. 4. 5, with GENC200 strain as reference for C-VI isolates and GENC071 strain for C-VIII 3. Recombination elements were removed from the global core genome alignment with ClonalFrameML software  (Didelot and Wilson, 2015) , The two maximum likelihood phylogenetic reconstructions were performed with RAxML software in the GTR-CAT model and 1000 bootstrap replicates, and the trees were drawn with iTOL. Multilocus sequence typing was performed in silico with mlst software 4  against the PubMLST database  (Jolley et al. , 2018) , and virulence gene factors were identified with Abricate software 5  associated with the Virulence Factor Database with a threshold of 95% coverage and 75% nucleotide identity  (Chen et al.
Focus on Cephalosporinase Genes and Mutations In the ECC collection, 11 wild-type (WT)/CoP pairs from the same sample were analyzed for mutations. Each strain pair differed by fewer than 45 SNPs (Supplementary Table  4 ). Nine pairs belonging to ECC C-VIII and two to C-VI were selected. Most of the strains (14/22) were isolated from reptiles. Mutation analyses were performed with Snippy software, and the corresponding GenBank flat file format for each gene was retrieved from the NCBI website 6   (Benson et al. , 2018). The accession numbers of the sequences used as references were: NZ_CP012165. 1 (E. hormaechei subsp. oharae strain 34978, complete genome) and NC_014121. 1 (E. cloacae subsp. cloacae ATCC 13047 chromosome, complete genome). All genes which could be involved in CoP and 3GC-R phenotype were analyzed and listed in Supplementary Table  4  (see Reference.
ACKNOWLEDGMENTS We are grateful to all the technicians and students for their participation in this project at the  ARS (Agence Régionale de Santé) , the  University Hospital , the  Pasteur Institute of Guadeloupe and the "Plateforme de microbiologie mutualisée. "We thank the curator team of the E. cloacae typing PubMLST database for their co-operation. We extend special thanks to  E. Heseltine  for editorial assistance. We also express our gratitude to the employees of the slaughterhouse in  Le Moule  and all the farmers and fruit and vegetable merchants for their collaboration.
Plant Material Corsican wild hops were found in different Corsican riverbeds and planted in an experimental field in Patrimonio (Corsica, France). Leaves sample were collected for the DNA analysis. Rizhomes of Cascade, Tettnanger and Smaragd cultivars were obtained from German grower (Locher-Hopfen-Tettnang, Missenhard, Germany), and planted in the experimental field. The hop cones of all the studied hops were picked two times: three months after planting and the following picking year. To have the evidence of the varieties and to be sure to compare the same varieties, leaves samples of the German hops cultivated in Patrimonio and in Tettnang region were genetically analyzed. The climatic conditions of the Tettnang valley and the four studied Corsican areas have been gathered from the open database "climate-data.
org" for which the results shown are averaged from 1999 to 2019, and from the database "meteoblue" for which the data are averaged from 2010 to 2020. The "Patrimonio" data can be considered common to "Oletta" due to the geographical proximity. During the growth period of hop from May to September, the Tettnang valley is characterized by its very high rain content (90-130 mm/month; av: 114 mm/month), low temperatures (13-18 In the first part of this study, wild hops (Table  1 ), located in Ajaccio, Corte, Patrimonio and Oletta, were characterized by a morphological, genetic and chemical approach. In the second part of the study were compared three hops cultivars: Cascade, Smaragd and Tettnanger. In this case, the hops have been identified with the commercial name of the cultivar followed by the geographical origin, for example, Cascade Tettnang, Cascade Corsica, etc.
Data Analysis The nuclear DNA fragments, resulted by the DNA amplification with the SSR markers, were sized by using a conservative binning approach  [36]  through the statistical R software (R Development Core Team 2005), which takes into account the type of replicate and compensates for the limits of the fragment resolution. The differences among the examined hops were evaluated through the genetic similarity matrix using Euclidean distance  [25, 37, 38]. The cluster analysis and construction of the dendrogram relative to genetic distances were obtained by using the unweighted pair-group method with arithmetic mean (UPGMA) algorithm, with Genetix  [39]  and XLSTAT 2009 software (AddinsoftTM 1995-2009). The univariate clustering analysis was performed using XLSTAT 2009 software (AddinsoftTM 1995-2009) to discriminate the genotypes.