dataesr/scientific-paragraphs-categorization huggingface dataset:
Identifying and Classifying Individual Type III Secreted Effectors We identified all putative T3SE protein sequences from the 494 P. syringae genomes by querying each predicted protein against the T3SE seed database using BLASTP if it passed a significance threshold of E < 1e-24. This resulted in the annotation of 14,613 T3SEs across the 494 P. syringae strains. Family names were initially assigned to these T3SEs based on the name that had been assigned to the hit in the seed database, and then later refined based on more rigorous criterion. First, we blasted each T3SE amino acid sequence against a database of all 14,613 T3SEs and retained only hits with an E-value of less than 1e-24 and a length that covered at least 60% of the shorter sequence. Sequences that had multiple non-contiguous hits (i.
However, for cases where there were multiple family names assigned to sequences within a single cluster, both Hop designations (i. e. , HopD/HopAO) were assigned to all sequences in the cluster, with the lower designation being considered the short-form for the family. Conversely, for cases where T3SEs that had initially been assigned the same family designation formed two separate clusters, T3SEs from the larger cluster were assigned the initial family name, and T3SEs from the smaller cluster(s) were assigned a novel family name, starting with HopBO, which is the first available Hop designation. In these cases, the initial family designation of the T3SEs in the family were also kept following a forward-slash ("/") so that the source of the family was known (i. e. , HopBO/HopX). Ultimately, this method allowed us to effectively delimit all T3SEs in this dataset into separate families with consistent definitions and performed considerably better at partitioning established T3SE families than standard orthology delimitation software like PorthoMCL  (Tabari and Su, 2017)  (Supplementary Dataset S2), likely because of the widespread presence of chimeric T3SEs in the P.
Phylogenetic Analyses We generated three separate phylogenetic trees in this study to ask whether core-genome diversity, pan-genome content, or effector content could effectively sort P. syringae strains based on their host of isolation. For the core genome tree, we clustered all protein sequences from the 494 P. syringae genomes used in this study into ortholog families using PorthoMCL v3 with default settings  (Tabari and Su, 2017). All ortholog families that were identified in at least 95% of the P. syringae strains in our dataset were considered part of the soft-core genome and each of these families was independently aligned using MUSCLE v3. 8. 31 with default settings  (Edgar, 2004). These alignments were then concatenated end-to-end using a custom python script and a maximum likelihood phylogenetic tree was constructed based on the concatenated alignment using FastTree v2.
RESULTS In this study, we analyzed the collective type III effector repertoire of the P. syringae species complex using whole-genome assemblies from 494 strains representing 11 of the 13 established phylogroups and 72 distinct pathovars (Supplementary Dataset S1). These strains were isolated from 28 countries between 1935 and 2016, and include 62 P. syringae type and pathotype strains  (Thakur et al. , 2016). Although the majority of the strains were isolated from a diverse collection of more than 100 infected host species, we also included strains isolated from environmental reservoirs, which have been dramatically under-sampled in P. syringae studies  (Morris et al. , 2007 (Morris et al. , , 2013;; Mohr et al. , 2008; Clarke et al. , 2010; Demba Diallo et al. , 2012; Monteil et al. , 2013 Monteil et al.
g. , soil or water). All of the P. syringae genome assemblies used in this study were downloaded directly from NCBI or generated in-house by the University of Toronto Centre for the Analysis of Genome Evolution & Function using paired-end data from the Illumina GAIIx or the Illumina MiSeq platform. There was some variation in the genome sizes, contig numbers, and N50s among strains due to the fact that the majority of the genomes are de novo assemblies in draft format (Supplementary Figure  S1 ); however, the number of coding sequences identified in each strain were largely consistent with the six finished (closed and complete) genome assemblies in our dataset. Given the large size of the P. syringae pan-genome, the fact that some strains have acquired large plasmids, and the relatively high frequency of horizontal gene transfer in the P.
Distribution of Type III Secreted Effectors in the P. syringae Species Complex To explore the distribution of T3SEs across the P. syringae species complex, we first identified all putative T3SEs present in each of our 494 genome assemblies using a BLASTP analysis  (Altschul et al. , 1997) , where all protein sequences from each P. syringae genome were queried against a database of known P. syringae T3SEs obtained from the P. syringae Genome Resource Database 4  , the Bean 2. 0 T3SE Database 5  , and the NCBI Protein Database 6. In sum, we identified a total of 14,613 confirmed and putative T3SEs (Supplementary Datasets S2-S4), 4,636 of which were unique at the amino acid level, and 5,127 of which were unique at the nucleotide level. We consider these T3SEs to be putative because their presence within a genome does not necessarily mean that they are expressed and translocated into the host cytoplasm.
Individual P. syringae strains in the dataset harbored between one and 53 putative T3SEs, with a mean of 29. 58 ± 10. 13 (SEM), highlighting considerable variation in both the composition and size of each strain's suite of T3SEs (Figure  1 ). As expected, primary phylogroup strains tended to harbor substantially more T3SEs than secondary phylogroups strains (30. 55 ± 8. 97 vs. 3. 89 ± 1. 64, respectively), which frequently do not contain a canonical T3SS  (Dillon et al. , 2019). However, a subset of strains from phylogroups 2 and 3, and all strains from phylogroup 10 harbored fewer than 10 T3SEs, more closely mirroring secondary phylogroup strains in their T3SE content. The extensive T3SE repertoires found in most primary phylogroup strains supports the idea that these effectors play an important role in the ecological interactions of the majority of strains in this species complex.
syringae strains (Supplementary Figure  S3 ). Following family and strain T3SE classification, we also performed hierarchical clustering using the T3SE content of each strain to determine if T3SE profiles are a good predictor of host specificity. We previously reported that in P. syringae, neither the core genome or gene content phylogenetic trees correlate well with the hosts from which the strains were isolated  (Dillon et al. , 2019). This remains true in this study, where we've updated the core and pan-genome analyses with an expanded set of strains (Supplementary Figures  S4, S5 ). The T3SE content tree is not as well resolved due to the smaller number of phylogenetically informative signals in the T3SE dataset. However, we were able to largely recapitulate the established P. syringae phylogroups with this analysis, suggesting that more closely related strains do tend to have more similar T3SE repertoires (Supplementary Figure  S6 ).
While the average copy number of individual T3SEs per strain across all families is 1. 30 and some families are present in copy numbers as high as six, it is important to recognize that in many cases these multi-copy effectors are not full-length T3SEs. Rather, they are partial copies derived from the same fulllength allele that have been split due to the introduction of a premature stop codon (Supplementary Dataset S2). Therefore, at least in these cases, we think it is unlikely that both copies retain function. Nevertheless, the fact that both of these two coding sequences retain enough protein similarity to be linked to other T3SEs in the same family suggests that these disruption events either occur very commonly, or that these regions are FIGURE 2 | Interfamily blast hits (E < 1e-10) that did not pass our e-value and/or length cut-offs for combining T3SEs into families.
syringae T3SEs and gain insight into their role in host specificity, we cataloged the T3SE repertoires of a large and diverse collection of 494 P. syringae isolates. These phylogenetically diverse strains allowed us to generate an expanded database of more than 14,000 putative T3SE alleles and investigate the evolutionary mechanisms through which these important molecules have enabled P. syringae to become one of the most globally important bacterial plant pathogens  (Mansfield et al. , 2012). for each effector family with the average core genome non-synonymous and synonymous substitution rates of the corresponding P. syringae strains. Pairwise substitution rates for all sequences within a family were estimated by reverse translating the effector family and concatenated core genome amino acid alignments, then calculating pairwise substitution rates in MEGA7 with the Nei-Gojobori Method.
Expanded Database of Type III Secreted Effectors in P. syringae This study increases the number of confirmed and putative T3SE alleles available in the P. syringae Genome Resources Database by 20-fold, resulting in a final database of 14,613 T3SE alleles from the P. syringae species complex, 5,127 of which are unique at the nucleotide level. Although these new, putative T3SEs all share an ancestral sequence with known T3SE families, we did not confirm expression or translocation of any of these T3SEs, so some of these coding regions may represent recently pseudogenized effectors. However, the extensive diversification that has occurred within many of these families clearly indicates that some level of functional diversification has occurred. Consistent with our earlier analysis, we find that primary phylogroup strains harbor considerably larger repertoires of T3SEs than secondary phylogroup strains  (Baltrus et al.
, 2014). The T3SEs from this dataset were also highlighted by this study as undergoing considerably higher rates of gene gain and loss within the P. syringae species complex. Specifically, all of these T3SEs were demonstrated to have undergone at least ten gene gain events and many were among the most dynamic T3SEs in our dataset. Other studies have shown that many T3SEs are present on mobile genetic elements and that T3SEs from the same family are often found at different genomic locations  (Kim and Alfano, 2002; Charity et al. , 2003; Lovell et al. , 2009 Lovell et al. , , 2011;; Godfrey et al. , 2011; Neale et al. , 2016) , which may both promote and be a consequence of the high rates of gene gain and loss for particular T3SE families. From a selective perspective, it is also likely that host immune recognition can drive selection for gene gain or loss  (Vinatzer et al.
A typical variable number of tandem repeats (VNTR) locus shows large range of copy numbers even among highly related bacterial strains  (Jackson, 2010). MLVA has been used as a typing tool in outbreaks of numerous human and animal pathogens, but also in food microbiology such as the winemaking process  (Claisse and Lonvaud-Funel, 2012). For human pathogens of medical interest, it has been regarded as a powerful tool for outbreak detection and source tracing in several European countries  (Lindstedt et al. , 2013). Resources for discovery of polymorphic loci such as VNTR databases are available for free access  (Chang et al. , 2007). For plant associated bacteria, several MLVA schemes have been described for important pathogens including several species and pathovars of Xanthomonas spp. such as X.
Sequences obtained from forward and reverse primers were assembled and edited using GENEIOUS  Pro 4. 8. 5 (Biomatters, New Zealand). Consensus sequences were generated, and codonbased multiple alignments were obtained using CLUSTALW  (Thompson et al. , 1994)  application in BioEDIT  (Hall, 1999)  with default parameters. Initial phylogenetic analyses were performed on individual rpoD and gyrB sequences for comparisons with sequences from Xanthomonas (type and pathotype strains) from the CFBP/PhyloSearch tool database 1 using the Neighbor Joining (NJ) method available in MEGA 5. 05  (Tamura et al. , 2007). As the concatenated data sets were identical for all 27 strains tested, we selected the sequences from the pathotype strain (CFBP 7660) for comparisons with DNA sequences of 131 strains of X.
Nucleotide Sequence Accession Numbers The GenBank accession numbers for the partial sequences of the grapevine strain CFBP 7764 and the Amaranthus strain Am-1, used in this study are, respectively: for atpD MH171285 and MH171286; for dnaK MH171287 and MH171288; for efp MH171289 and MH171290; for fyuA MH171291 and MH171292; for glnA MH171293 and MH171294; for gyrB MH171295 and MH171296; and for rpoD MH171297 and MH171298.
These CDSs were distributed in several clusters, corresponding to almost 15 whole contigs of various sizes (between 64. 4 and 0. 8 Kb). Around 100 of these 233 CDSs had no orthologs in NCBI nr database. Most of the remaining CDSs had orthologs in plasmid sequences, such as plasmid pB07007 of X. hortorum strain B07-007, plasmid C of X. citri pv. fuscans strain 4834R, plasmid pICMP7383. 2 of X. gardneri, and plasmid pLH3. 1 of X. euvesicatoria pv. perforans strain LH3. Apart from numerous CDSs encoding proteins involved in conjugation, these putative plasmids carried CDSs encoding functions such as toxin-antitoxin, restriction and anti-restriction proteins, multidrug efflux systems and copper resistance genes (Supplementary Table  S3 ). A copLAB gene cluster has hence been evidenced in CFBP 7764.
Genome Sequencing and Assembly Long read, SMRT sequencing (PacBio, Menlo Park, CA, United States) data were generated for five Xol strains and for the Xo strain X11-5A, to be used as an outgroup. DNA for SMRT sequencing was isolated by culturing strains on nutrient agar for 48 h then using the Genomic DNA buffer set and Genomic-tips according manufacturer instructions (Qiagen, Valencia, CA, United States). SMRT sequence was assembled using HGAP v4 (PacBio, Menlo Park, CA, United States). Genomes were circularized using circulator  (Hunt et al. , 2015). Assemblies and raw data have been deposited in NCBI (BioProject IDs PRJNA522807 and PRJNA522811; BioSample accessions SAMN03862116, SAMN02469650, SAMN10956066-68, SAMN10956070; raw sequencing files SRX5417793-98; Assembly accessions CP036251-56).
Xo produced water-soaked spots at the point of infiltration that did not expand on southern cutgrass (Figure  1 ). After clip inoculations, lesions caused by Xol did not expand on rice or southern cutgrass, unlike those caused by the vascular pathogen Xoo (Supplementary Figure  S1 ). When infiltrated into leaves, populations of Xol were equivalent to Xoc BLS256 and Xo X11-5A on rice cvs. Nipponbare or Azucena after 72 hpi (Figure  2 ). On southern cutgrass, their native host, Xol grew to a significantly higher population than Xo X11-5A. Xol did not cause disease on wheat or barley (Supplementary Figure  S2 ). Phenotyping Nicotiana species can serve as a screen for the ability 3 https://github. com/alperezq/experimenTAL of microbes, particularly Xanthomonas spp. , to elicit a non-host resistance response  (Gonzalez et al.
By examining pairwise genetic distances between the repeat regions of TALEs, we saw that TALEs from Xol are on average more similar to each other than TALEs within other X. oryzae groups, indicating that they are possibly less diversified and/or more redundant (Figure  5C ). Xol TALE Targets in Cutgrass and Rice Are Different From Xoc and Xoo Targets Talvez  (Pérez-Quintero et al. , 2013)  was used to predict host targets for each TALE in our dataset in the promoters of annotated genes in the L. perrieri (v1. 4) and O. sativa (vMSU7) genomes. We identified ortholog pairs between both genomes using reciprocal BLAST. Comparisons of the predictions between both genomes for Xol TALEs revealed very few cases where an ortholog pair was predicted to be a target in both genomes (Supplementary Figure  S7 ), and highlighted that the promoters (and thus the targeted genes) in these two hosts are very different.
perrieri genome for each pair of strains, and the upper right shows shared targets in the O. sativa genome. Trees at the top and left show hierarchical clustering based on stared targets in each genome. Accession numbers for genomes used in this analysis are available in Supplementary Table  S2. strain. As a result, we saw that each X. oryzae group has a distinct group of predicted targets with relatively little overlap with other groups. In the case of Xol, the highest overlap was found with predictions for Xoc TALEs (10-11% shared predicted targets) (Figure  6 ). Given the differences in the genomes of their hosts and that Xol TALEs have unique repeat sequences, we expect their targets to be likewise unique. Additionally, we looked for orthologs of known susceptibility (S) genes targeted by Xoc or Xoo TALEs (e.
, 2002). Subsequently, based on a PFPs sequencing project that included strains that harbored different variants of copper-resistance determinants  (Gutiérrez-Barranquero et al. , 2017a) , it was shown that the presence of a novel genetic structure in Pss UMAF0081 strain isolated from mango increased copper-resistance phenotypes. This novel genetic structure encoded the cusCBA genes (detoxifying monovalent cations of silver and copper) and copG, a putative metal-transporting P-type ATPase, both inserted within the copABCD operon (Gutiérrez-  Barranquero et al. , 2013b). Furthermore, the novel genetic structure was found in another strain of Pss analyzed in this study (Pss 6-9 strain isolated from sweet cherry), and was also present in another two strains from the database that belonged to different pathovars (ATCC1128 pv.
Interestingly, group III (the group that lacked the mbo operon) diverged before the separation of groups I and II. These results suggested that the mbo operon was acquired by groups I and II in only one or two acquisition events after their separation from group III. Thus, this work strongly suggested that the mbo operon was horizontally acquired only once during the evolution of the P. syringae complex shown to be specifically distributed within the P. syringae Genomospecies 1  (Carrión et al. , 2013). In the last few years, the databases have suffered a veritable explosion regarding the number of P. syringae genome sequences available  (Baltrus et al. , 2011; Thakur et al. , 2016) , which also contributed to a novel classification of the P. syringae complex in 13 different phylogroups  (Berge et al.
Supplementary Table  S1  provides the phylogenetic groups, the host of isolation and the accession numbers of the DNA sequences used for each strain represented in this phylogenetic analysis. genome sequencing project performed on the Pss model strain isolated from mango trees, UMAF0158, revealed the presence of two different T3SSs  (Martínez-García et al. , 2015). The first T3SS (T3SS-1) is similar to the Hrp-1 T3SS family  (Egan et al. , 2014)  found in different pathovars of P. syringae  (Lindeberg et al. , 2012)  and represents the canonical T3SS widely distributed in pathogenic P. syringae strains  (Block and Alfano, 2011; Lindeberg et al. , 2012). Pss strains isolated from mango trees were able to induce a hypersensitivity response (HR) in tobacco plants  (Cazorla et al. , 1998). The capability of P.
, 2009; Green et al. , 2010; Baltrus et al. , 2011; McCann et al. , 2013; Thakur et al. , 2016; Hulin et al. , 2018). Currently, the complete genome sequences of 29 P. syringae strains, along with more than 400 draft genome sequences, are included in the NCBI database 2,3. To date, there is only one complete genome sequenced of Pss strains isolated from mango trees (chromosome + 62-kb PFP plasmid), which was performed in the model strain Pss UMAF0158  (Martínez-García et al. , 2015). This work revealed a high degree of conservation with other Pseudomonas from the P. syringae complex; however, different genetic factors were identified for their potential involvement in the epiphytic or pathogenic lifestyle, and these factors have been described in depth in this review. Among these factors, the most important were the presence of the mbo operon (mangotoxin biosynthetic operon), the presence of the wss operon (operon involved in cellulose biosynthesis), the additional type III-like rhizobial secretion system, the additional type VI secretion system, and a particular T3E repertoire.
Genome Selection For the purposes of phylogenomic analyses, we searched for genomes in NCBI/GenBank using "Xanthomonas citri" as a keyword, then looked at the automatic dendrogram generated by genomic distances on the NCBI website 3 , which reveals all genomes within this group, including all subspecies/lineages/varieties available as reference sequences (RefSeq). After downloading this tree, we searched for all different lineages, and then downloaded up to three genomes from each such lineage, if available, and preferentially (if possible) drawing from separate clades where the lineage appears in NCBI's dendrogram, to avoid pseudoreplication (i. e. , avoiding picking two closely related genomes). This led to a final dataset of 31 genomes.
We observed that the genomes of XauB strains do not have any of these genes. However, the loss of a single gene of hemolysin in XauC strains would have a small effect, since this loss could be compensated by paralogous genes in their genomes. Concerning the cluster of membrane proteins, three of the ABC transporters are associated with resistance to acriflavin (XAC3994-95 and XAC3850) and two have the hlyD domain (PF00529), involved with secretion of toxins. Some of the genes in this network were not found in the genomes of strains XauC 1609 and XauC 535.
citri pv. mangiferaindicae), and cotton (X. citri pv. glycines). Curiously, X. citri pv. anacardii (infecting cashew) apparently evolved within a citrus-associated clade, suggesting a possible host jump. We have made an extensive analysis of the presence and absence of effectors in the 31 genomes we sampled to reconstruct FIGURE 2 | Network of putative interactions between genes/proteins using as query the hlyB gene from strain A306, a key gene in the Type 1 Secretion System. The nodes represent the genes/proteins present in the A306 genome. The color codes on the lines is: red -fusion evidence; green -neighborhood evidence; blueco-occurrence evidence; purple -experimental evidence; yellow -text mining evidence; light blue -database evidence; black -co-expression evidence. The network part of the figure was generated by the program STRING  (Snel et al.
EN, ME, JJ, EG, and MP conceived the project. MP, CB, NZ, EN, and AO provided P. syringae strains. EN conducted the pathogenicity assays. ME prepared the genomic DNA. ME, ST, and JJ oversaw the sequencing experiments. ST and NP assembled the draft genomes. ME conducted the toxin analysis and EN performed all other computational analyses with support from JH-T and NP. ME submitted the genome sequences to NCBI-GenBank and JGI-IMG. EN wrote the manuscript and all authors provided a critical review of the paper. FUNDINGThis research was supported in part by the Southern IPM Center, Florida Watermelon Association, the National Watermelon Association, and USDA-NIFA. NZ and AO were supported by the national project III46008. NP and EN were supported by funding from NIFA-Hatch and Alabama Agriculture Experiment Station.
ACKNOWLEDGMENTS We would like to thank  Karine Durand ,  Jacky Guillaumes , and  Geraldine Taghouti  for their technical assistance. We would also like to thank  Muriel Bahut  and the ANAN platform from  SFR Quasav  for VNTR sequencings, and CIRM-CFBP (https://www6. inra. fr/cirm_eng/ CFBP-Plant-Associated-Bacteria )for strain preservation and supply.