dataesr/scientific-paragraphs-categorization huggingface dataset:
Dengue virus quantification Dengue virus was quantified via RT-qPCR using the LightCycler 480 (Roche). We used the TaqMan Fast Virus 1-Step Master Mix (Thermo Fisher Scientific) in a total reaction volume of 10 μl, following the manufacturer's instructions  (Terradas et al. 2017). The list of primers and probes is given in Supplementary Table  1. The temperature profile used was: 50 °C for 10 min; 95 °C for 20 s; 35 cycles of 95 °C for 3 s; 60 °C for 30 s; 72 °C for 1 s; and 40 °C for 10 s. Data were analysed using absolute quantification where the dengue virus copy number per sample was calculated from a reference curve. This reference curve was made up from known quantities of the genomic region of the virus that the primers amplify. This genomic region had previously been cloned into the pGEM-T plasmid (Promega) and transformed into Escherichia coli  (Ye et al.
2016). We estimated a permutation-based P value threshold that corresponded to a genomewide FDR of 5% by re-running our genome scan on all possible permutations of our pairwise contrasts between high and low, high and random and low and random populations. In each case, there were nine possible unique permutations excluding the observed arrangement of the six replicate populations. For each permuted dataset, we refitted our linear model to all SNPs and estimated the number of significant SNPs. We performed a Singular Enrichment Analysis (SEA) on the AgriGO v2 website using the 61 A. aegypti genes associated with Wolbachia-mediated dengue blocking listed in the Supplementary File 1. We used the AaegL3. 3 reference genome and performed a Fisher test, correcting for multiple comparisons using the Hochberg (FDR) method.
Growth curve were performed in 96 multi-well plates at 25 • C during 30 h in a microplate spectrophotometer Infinite R M200 NanoQuant (TECAN). Optical density (OD 600 nm ) was determined each 30 min. All curves were performed in biological triplicates. DH5α were used as the control reactions. The sequences of the effector genes of a selected strain (Psa 743) were deposited in GenBank (NCBI), and the accession numbers are listed in Supplementary Table  S2.
, 2012). The nucleotide sequences of the gapA, gltA, gyr, and rpoD genes of Chilean Psa strains were added to GenBank (NCBI) and are listed in Supplementary Table  S3. The sequences of other Psa biovars available in GenBank (NCBI) were included in the analysis and are listed in Supplementary Table  S4. In addition, sequences of P. syringae pv. tomato strain DC3000 were included: gapA (AE016853. 1:1415258-1416259), cts (AE016853. 1:2414332-2415621), gyrB (AE016853. 1:4147-6564), and rpoD (AE016853. 1:588846-590696) (Buell et al. , 2003). The sequences of each locus were aligned using the CLUSTALW included in the MEGA7 software  (Kumar et al. , 2016). A dendrogram from four-locus concatenated sequences was generated using neighbor-joining (UPGMA) and 1,000 bootstrap iterations.
The PCR conditions were as follows: 5 min at 95 • C, followed by 35 cycles of 30 s at 95 • C, 30 s at the annealing temperature (Supplementary Table  S1 ), 2 min at 72 • C, and a final elongation step of 5 min at 72 •. Sanger automated sequencing of the amplicons from Psa 743, Psa 598, and Psa 889 was performed by Macrogen, Inc. (South Korea). The sequences were compared with those in the NCBI database using BLASTN and BLASTX for gene identification. The sequences obtained were deposited in GenBank (NCBI), and the accession numbers are listed in Supplementary Table  S2.
Phenotypic Characterization of the Psa Isolates Different features implicated in the fitness and virulence of Psa were evaluated in the 18 Chilean isolates. None of the strains showed differences in their growth parameters (data not shown). However, their biochemical profile determined using the Biolog GEN III MicroPlate revealed differences in 22% of the different tests in at least one of the 18 strains (Supplementary Table  S6 ). All of the strains were able to use different carbon sources such as D-glucose, D-mannose, D-galactose, glycerol, D-mannitol, Larginine, L-serine, acetic acid, and citric acid. However, they varied in their ability to use sucrose, D-fructose, inosine, L-glutamic acid, and formic acid. Alternatively, all of the strains were resistant to antibiotics such as rifamycin SV, lincomycin, and vancomycin, while they were sensitive to minocycline and troleandomycin and showed variable sensitivity to aztreonam, nalidixic acid, and fusidic acid.
Despite these differences, all of the strains were identified as P. syringae pathovars according to the Biolog GEN III database  (version 2. 8). Interestingly, all of the isolates were susceptible to copper (MIC 75 µg/mL Cu 2+ ) and streptomycin (MIC 3. 9 µg/mL), suggesting that no resistance has developed in these strains despite the use of copper compounds as antimicrobials in the Chilean kiwifruit industry. Biofilm production has been proposed to be an important virulence factor in P. syringae  (Ghods et al. , 2015; Ueda and Saneoka, 2015). Therefore, the ability to produce biofilm was evaluated in the different Chilean Psa isolates. The results showed that none were able to produce biofilm over an abiotic surface. However, they do produce a thin layer of biofilm (pellicle) in the air-liquid interface.
syringae, this amino acid is the precursor of IAA synthesis in Psa. IAA production was also confirmed in the Chilean Psa strain 743 using LC-ESI-MS/MS analysis, showing a strong signal for IAA in the supernatant of the Psa 743 cell-free cultures (Supplementary Figure  S4 ). The iaaM and iaaH genes were not detected in the Chilean Psa isolates using PCR and specific primers, suggesting an alternative route of synthesis exists in these strains. Recently, a novel IAA synthesis pathway was reported in P. syringae pv. tomato DC3000 (Pst), which involves the participation of an indole-3-acetaldehyde dehydrogenase encoded by the gene aldA and its homolog, aldB  (McClerklin et al. , 2018). Comparative analysis by BLASTN showed 95 and 97% identity between the aldA and aldB genes, and an aldehyde dehydrogenase sequence (GenBank accession number: CP011972.
2: 149109-150602) and a carnitine dehydratase/3-oxoadipate enol-lactonase sequences (GenBank accession number: CP011972. 2: 3182732-3184213) were encoded in the Biovar 3 Psa strain ICMP 18884. PCR with specific primers revealed that the aldA and aldB genes were also detected in all of the Chilean Psa strains, suggesting that they are likely to be responsible for the synthetic route of IAA. The identity of genes aldA and aldB was confirmed in strains Psa 889, Psa 743, and Psa 598 using Sanger sequencing (Supplementary Table  S2 ). It has also been reported that IAA can be conjugated to the amino acid lysine to produce IAA-Lys by the enzymatic activity of the iaaL gene product  (Glickmann et al. , 1998; Castillo-Lizardo et al. , 2015; Cerboneschi et al. , 2016). Our analysis detected the presence of the genes iaaL and matE in all of the Chilean Psa isolates (Figure  4B ), which are in tandem in the Hrp regulon and are associated with IAA-Lys production.
Bioinformatic Analysis Raw reads were first processed with Trimmomatic  (Bolger et al. , 2014)  to remove low-quality reads using a sliding window of 5 bp length with an average phred score ≥ 20. Sequences shorter than 100 bases were discarded. The 16S rRNA sequences were analysed using the Mothur software package version 1. 35. 1  (Schloss et al. , 2009). The paired-end reads were assembled and aligned to the SILVA 16S rRNA sequences database  (Pruesse et al. , 2007). Sequences were de-noised to remove sequencing error with the command "pre. cluster" and chimeric sequences were removed using the Uchime algorithm  (Edgar et al. , 2011)  implemented in Mothur. Sequences were clustered into OTUs at 96% sequence identity using the nearest neighbour clustering methods. The sequences were classified using the references Ribosomal Database Project database (RDP) provided in Mothur.
OTUs that were singletons and doubletons were removed. The samples were normalised to 6,886 sequences each (the size of the smallest sample) to ensure that the analysis was not influenced by differential sequencing depths. The bacterial 16S rRNA gene Illumina sequencing data are deposited in the NCBI BioProject library (Accession: PRJNA472855, ID: 472855). The bacterial taxonomic table (with bacterial relative abundance data) are given in Supplementary Table  S1.
Meta-Analysis of Bacterial Association The correlation among natural epiphytic populations of Psa and other bacteria (P. syringae pv. syringae, P. viridiflava, P. fluorescens, Pantoea agglomerans/vagans, and Lactobacillus spp. ) was evaluated based on data obtained between 2012 and 2016, relating to A. deliciosa cv. Hayward samples collected in the same area and season as the samplings for metagenomic analysis. Each sample was singularly washed in 10 ml MgSO 4 10 mM sterile solution. Bacterial quantification was performed on the wash by qPCR as described above.
FUNDING The work was funded by the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 613678 (Dropsa -Strategies to develop effective, innovative and practical approaches to protect major European fruit crops from pests and pathogens). Yakhin, O. I. , Lubyanov, A. A. , Yakhin, I. A. , and Brown, P. H. (2017). Biostimulants in plant science: a global perspective. Front. Plant Sci. 7:2049. doi: 10. 3389/fpls. 2016. 02049 Yang, T. , Stoopen, G. , Yalpani, N. , Vervoort, J. , de Vos, R. , Voster, A. , et al. (2011). Metabolic engineering of geranic acid in maize to achieve fungal resistance is compromised by novel glycosylation patterns. Metab. Eng. 13, 414-425. doi: 10. 1016 /j. ymben. 2011. 01. 011 Yashiro, E. , and McManus, P.
To investigate the evolutionary processes that led to the emergence of these epidemic lineages, we sequenced the genomes of six P. syringae strains that were isolated from cucurbits grown in the United States, Europe, and China over a period of more than a decade, as well as eight strains that were isolated from watermelon and squash grown in six different Florida counties during the 2013 and 2014 seasons. These data were subjected to comparative analyses along with 42 previously sequenced genomes of P. syringae stains collected from diverse plant species and environments available from GenBank. Maximum likelihood reconstruction of the P. syringae core genome revealed the presence of a hybrid phylogenetic group, comprised of cucurbit strains collected in Florida, Italy, Serbia, and France, which emerged through genome-wide homologous recombination between phylogroups 2a and 2b.
syringae pv. syringae. Here, we investigated the evolutionary processes that led to the emergence of these similar, yet distinct P. syringae lineages as successful pathogens of watermelon, cantaloupe, and squash, as well as the genetic factors that distinguish them from other members of this environmentally ubiquitous bacterial population. We obtained high-quality draft genomes for 11 P. syringae strains collected from bacterial leaf spot epidemics in the United States, as well as for three strains isolated from symptomatic squash grown in Italy, Serbia, and China over various years. In order to investigate these strains in the context of the larger diversity of P. syringae, we analyzed these data together with the genomes of 42 additional P. syringae strains collected from diverse plant species and environments available from public sequence databases.
The raw sequence data were subjected to adapter and quality trimming with Scythe 1 and SolexaQA, respectively  (Cox et al. , 2010). The quality-trimmed reads were then de novo assembled into contigs using the SPAdes Genome assembler (v3. 5. 0) with the "careful" option to reduce mismatches in the assembly  (Bankevich et al. , 2012). The draft genome assemblies were submitted to the Prokaryotic Genomes Automatic Annotation Pipeline (PGAAP) 1 https://github. com/vsbuffalo/scythe pipeline and the Joint Genome Institute (IMG-JGI) server for annotation  (Markowitz et al. , 2012; Tatusova et al. , 2016). The sequencing, assembly statistics, and collection information are presented in Table  1.
Pan-Genome Association Analysis The strains sequenced in this study were investigated in context of P. syringae by including 42 additional genomes that were publicly available from the National Center for Biotechnology Information (NCBI) GenBank for analysis (Table  2 ). These genomes were selected to represent the diversity of phytopathogenic bacteria previously described within the species and are distributed among phylogroups 2a, 2b, and 2d  (Berge et al. , 2014; Bull and Koike, 2015). Representatives of phylogroup 2c, otherwise known as P. congelans, were not included in this analysis as they are not known to be phytopathogenic  (Mohr et al. , 2008). The genome assemblies were re-annotated with Prokka to generate GFF3 files  (Seemann, 2014) , which were then used as input for Roary pan-genome pipeline  (v.
The program detects "recent" recombination events between lineages using a HMM and the origin of the recombinant sequence is assigned to the lineage with the highest probability at that position. Similarly, "ancestral" recombination events that are shared by all strains which comprise a lineage are identified; however, the origin of these recombination events cannot be 2 https://github. com/widdowquinn/pyani 3 http://tree. bio. ed. ac. uk/software/figtree/ inferred due to their conserved nature  (Mostowy et al. , 2017). The statistical significance of recombination predictions was tested using a Bayes factor (BF) > 1 for recent recombination events and BF > 10 for ancestral recombination events. This analysis was conducted with two alternative genome alignments using completed reference genomes of P.
Functional Analysis of Recent Recombination Events To characterize the functional impact of the recombinant genes leading to the emergence of phylogroup 2b-a, BLASTn (Evalue ≤ 1e -50 ) was used to map the recent recombination events predicted by fastGEAR back to the genome assemblies of three strains (13-140A, ZUM3584, HS191), representative of the different recombination profiles in the dataset. The Clusters of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology IDs corresponding to recombinant and non-recombinant genes were subsequently extracted from the IMG annotations and a linear regression analysis was conducted to compare the composition of recombinant vs. non-recombinant core genes across the COG functional categories. Additionally, the KEGG orthology IDs were used to compare the distribution of recombinant genes across the KEGG BRITE functional annotations among the three different recombination profiles.
Identification of Plasmids and Genomic Islands The presence of plasmids was predicted for the strains sequenced in this study using plasmidSPAdes  (Antipov et al. , 2016). Assembled contigs were screened using Microbial Genome BLAST against the complete plasmid database to identify putative plasmid sequences. These contigs were subsequently screened for T3SEs and other virulence factors as described above. Genomic islands and other signatures of horizontal gene transfer (HGT) were detected using the Island Viewer 4 server  (Bertelli and Brinkman, 2018). Genomic islands (GIs) were predicted using the reference strains P. fluorescens SBW25, P. protegens Pf-5, P. aeruginosa PAO1, and P. syringae pv. syringae B728a. The predicted GIs were analyzed for gene content and extracted from the genome assemblies to construct multiple sequence alignments using the Mauve software package  (Darling et al.
Functional categorization of recombinant core genes utilizing the KEGG BRITE database supported these observations. Approximately 25% of the classifiable genes impacted by recombination were ATP-dependent transporters associated with numerous metabolic pathways, followed by bacterial motility proteins and secretions systems, which each comprised approximately 7-8% of the recombinant genes in each strain (Figure  3B ). Examination of the specific secretion systems impacted by recombination indicated that many of the genes associated with the biosynthesis of type III secretion system (i. e. , hrp/hrc gene cluster) were recombinant among strains 13-140A and ZUM3584, whereas no signals of recombination were detected in the hrp/hrc cluster of strain HS191. Phylogenetic analyses showed that 17 hrp/hrc genes clustered the cucurbit strains isolated in Florida, France, and Serbia into a monophyletic group with other members of phylogroup 2a and were therefore considered recombinant, while strain ZUM3584 carried 11 recombinant alleles (data not shown).
1). This plasmid carried the effectors hopC1 and hopH1, which marked the second copy of hopH1 for these two strains, in addition to the disrupted allele present in the ICE. A putative virulence plasmid of 16. 51 Kb in size was assembled in strains 13-429 and 13-139B which harbored four accessory effector genes including hopAU1, hopAW1, hopAF1, and avrPto. The top hit for this contig in the NCBI complete plasmid database was plasmid PP3 (NZ_LT963405. 1) of P. syringae pv. avii strain CFBP3846 and displayed only distant homology (95% nucleotide identity and 39% query coverage). Strains BS2121 and ZUM3984 also carried two putative plasmids, for which the top BLAST hits included the complete plasmids pCC1557 (NZ_CP007015. 1) and pB13-200A (NZ_CP019872. 1). However, no apparent virulence factors were identified in these contigs.
syringae phylogroups may inhabit overlapping environmental niches and are consistent with that of an epidemic population structure. The link between macro-scale recombination events and the emergence of hybrid, epidemic-clones has been well documented among human and animal bacterial pathogens  (Spoor et al. , 2015). As such, genome-wide recombination events are associated with niche adaptation and remodeling of the host-pathogen interaction. Functional analysis of the recent recombination events that led to the emergence of phylogroup 2b-a painted a similar picture. Although a strong linear relationship between the COG category compositions suggested an overall proportional change among the general functional groups (Figure  3A ), analysis utilizing the KEGG BRITE database revealed that pathways involved in the ATP-dependent transport of amino acids and other organic compounds, bacterial motility, and secretion systems were enriched for recombinant genes (Figure  3B ).
Pan-Genome Size For evaluation of the pan-genome of the 58 X. perforans strains, all genes were extracted from the 58 X. perforans strains using 1 https://github. com/drpowell/utils/blob/master/filter-spades. py roary  (Page et al. , 2015)  following gene annotation from prokka  (Seemann, 2014). The method yielded a total of 7,245 genes. The pan-genome matrix of gene presence/absence in each genome was used as input for a rarefaction analysis to calculate the average number of genes added with each additional genome  (Méric et al. , 2014). The calculation was randomized by resampling 100 times. The Heaps law function was fitted to the data using the micropan package in R to the rarefaction curve  (Tettelin et al. , 2008; Snipen and Liliand, 2015). The Heaps law model estimates the parameter alpha.
Sequence Typing and Gene Mapping Individual core genes were sequence typed based on nucleotide sequence identity using a python script. Genes with identical sequences were assigned the same number, representing the sequence type. The process was repeated in a loop for all core genes and an output sequence type matrix was generated. This allowed quick comparison of core genes based on allelic variation. Invariable genes were stripped from the matrix to generate a heat map of allelic profiles using the ggplot2 package  (Wickham, 2010)  in R (R Core Team, 2013). The heat map was color coded to illustrate the allelic patterns for variable core genes, thus providing a genetic fingerprint. The relative positions of the core genes were mapped based on the complete genome of X. perforans Xp91-118 (NCBI accession number: GCA_000192045.
Identifying Recombination Sources and Recombination Mechanisms We used two methods to determine if PgD genes may have been horizontally transferred. The sequences of the PgD genes were compared to the NCBI sequence database to determine if alleles were shared with other closely related Xanthomonas species. We also calculated the relative impact of recombination to mutation on nucleotide substitution using ClonalFrameML. Clusters of genes identified as variable or PgD, particularly those with high recombination values, were identified and their gene neighborhoods and flanking regions were examined. Gene neighborhood regions from representatives of each phylogenetic group were aligned and examined for the presence of genes suggestive of prior transfer events, including features of plasmids, phages, and transposable elements  (Chiu and Thomas, 2004).
This situation should be rectified in order to facilitate more comprehensive analyses of the role of T3SEs in the outcomes of host-pathogen interactions, particularly in light of the growing database of P. syringae genomics resources. Here, we present an expanded catalog of T3SEs in P. syringae and an updated phylogenetic analysis of the diversity within each T3SE family. We identified a total of 14,613 T3SEs from 494 P. syringae whole-genomes that include strains from 11 of the 13 P. syringae species complex phylogroups. These strains allowed us to redefine evolutionarily distinct family barriers for T3SEs, examine the distribution of each family across the P. syringae species complex, quantify the diversity within each T3SE family, and explore how T3SEs are inherited. By expanding and diversifying the database of confirmed and predicted P.
Genome Sequencing, Assembly, and Gene Identification Four hundred and ninety-four P. syringae species complex strains were analyzed (Supplementary Dataset S1), of which 102 assemblies were obtained from public sequence databases, including NCBI/GenBank, JGI/IMG-ER, and PATRIC  (Markowitz et al. , 2012; Wattam et al. , 2014; NCBI Resource Coordinators, 2018) , and 392 strains were sequenced in house by the University of Toronto Center for the Analysis of Genome Evolution and Function (CAGEF). Two hundred and sixty-eight of these sequenced strains were provided by the International Collection of Microorganisms from Plants (ICMP). For the strains sequenced by CAGEF, DNA was isolated using the Gentra Puregene Yeast and Bacteria Kit (Qiagen, MD, United States), and purified DNA was then suspended in TE buffer and quantified with the Qubit dsDNA BR Assay Kit (ThermoFisher Scientific, NY, United States).
Identifying, Annotating, and Delimitation of Type III Secreted Effector Families To characterize the effector repertoire of each of the 494 P. syringae strains used in this study, we first downloaded all available P. syringae effector, helper, and chaperone sequences from three public databases: NCBI 2  (18,120), Bean 2. 0 (225)  (Dong et al. , 2015) , and the P. syringae Genome Resources Homepage 3  (843). Additional type III associated proteins were recovered from NCBI by querying the NCBI protein database with "type III effector, " "type III helper, " and "type III chaperone" along with "P. Syringae. " These were combined with all available type III secretion associated genes from the Bean 2. 0 database and the P. syringae Genome Resources database, which were downloaded directly. Using this database of 19,188 T3SE associated sequences in P.
However, this only occurred in one case, which resulted in all HopF and HopBB sequences being assigned to the HopF/HopBB family. In sum, our final seed database of P. syringae T3SEs contained a total of 7,974 effector alleles from 66 independent families, 1,585 discontinued effector alleles from 6 independent families, 2,230 helper alleles from 23 independent families, and 1,569 chaperones alleles from 10 independent families. Any sequences that were not able to be assigned to an appropriate T3SE family were discarded because of the possibility that these are not true T3SE associated genes.