dataesr/scientific-paragraphs-categorization huggingface dataset:
Creation and Curation of the COMPASS Database Complete bacterial plasmid accessions were retrieved from the NCBI nucleotide database on 17 June 2018 using advanced optimized filters in the entrez query to exclude incomplete and misannotated plasmids. More precisely, keywords such as "plasmid, " "bacteria, " and "complete" were used in the initial query to retrieve complete plasmid records. Specific terms in the title were filtered to remove plasmid "genes, cds, origin of replication or region, " and other words such as "integron, transposon, operon, and phage" were applied to get rid of mobile genetic elements other than plasmids. Fasta and GenBank files associated with all plasmid accessions were downloaded from the NCBI database. A python script was developed to extract metadata from the GenBank files and to curate the database as described below.
Duplicated records were first identified based on specific metadata. All the plasmids with the same size, topology, taxonomy, and header description were considered identical. Duplicated records were removed keeping preferentially the most recent version and RefSeq entry. Duplicated sequences sharing 100% identity and coverage were then identified using the clustering tool CD-HIT-EST  (Li and Godzik, 2006). This step allowed the identification of clusters constituted of identical plasmids. One plasmid sequence was kept (as a reference) in the database while the other records were discarded. Finally, putative chromosomal sequences mislabeled as plasmids were identified by performing in silico Ribosomal Multilocus Sequence Typing (rMLST) analysis  (Jolley et al. , 2012). rMLST is an approach which indexes variation of the 53 genes encoding the bacterial ribosome protein subunits (rps genes) to identify rapidly the phylogenetic position of any bacterial sequence.
The 53 rps genes, downloaded from PubMLST 1  (12 February 2019) were sought in the plasmid records using BLASTn and hits with at least 95% identity and 95% coverage were considered potential matches  (Jolley et al. , 2012). The scripts and database of COMPASS developed in the present study can be found in the following GitHub repository: https://github. com/itsmeludo/COMPASS.
Plasmid Typing and Predicted Mobility In silico predictions of the replication gene (replicon), mobilization protein (relaxase), mate-pair formation (MPF), and the origin of transfer (oriT) types were obtained using the MOB-typer module from the MOB-suite package 2   (Robertson and Nash, 2018). Replicon, relaxase, MPF, and oriT sequences were identified by BLAST using default parameters against reference databases that Robertson and Nash built for the MOBtyper tool. These databases contained 2481 plasmid-derived replication genes that corresponded to 1683 replicon types, 916 relaxase sequences classified into six MOB families (MOB F , MOB H , MOB Q , MOB C , MOB P , and MOB V ), 2066 MPF proteins clustered in four groups (MPF I , MPF F , MPF G , and MPF T ), and 502 oriT sequences. The plasmid mobility was predicted based on the presenceabsence of the three dissemination markers.
A plasmid was labeled as "conjugative" if it carried a relaxase plus an MPF and as "mobilizable" if it contained at least a relaxase or an oriT whereas plasmids missing both a relaxase and an oriT were classified as "non-mobilizable"  (Robertson and Nash, 2018). Replicon typing was also performed using the conventional in silico tool PlasmidFinder (version October/2019) 3  with recommended parameters  (Carattoli et al. , 2014)  and the results were compared to those obtained with MOB-typer. The replicon content of the MOB-typer database was also compared to the one of PlasmidFinder using the clustering tool CD-HIT-EST-2D (i. e. , 100% identity and 100% coverage) to identify specific alleles shared between the two typing resources.
Visualization and Statistical Analysis The plasmid size was analyzed with R scripts  (R_Core_Team, 2018)  and graphically represented with the ggplot2 library  (Wickham, 2016). A custom world map showing the distribution and the number of plasmids isolated per country was created using the online tool Gunnmap 2 4. The exploration of the taxonomical composition of the COMPASS database was performed using the web-based interactive visualization tool Krona  (Ondov et al. , 2011). The HTML link for the interactive Krona chart can be found in the COMPASS GitHub repository mentioned above. The plasmid content of our database was compared to other plasmid resources (PLSDB, pATLAS, and MOB-suite) by comparing the nucleotide databases 2 by 2 and identifying strictly identical plasmid sequence (i. e.
, 100% identity and 100% coverage) using the clustering tool CD-HIT-EST-2D. The integrative venny tool  (Bardou et al. , 2014)   5  was also used to visualize the number of plasmids shared between COMPASS and the other three databases by comparing the lists of accessions. Two co-occurrence network analyses were performed independently based on the R igraph library to highlight plasmid mobilization in different species and decipher the linkages between replication genes present in multireplicon plasmids. Sankey diagrams were built using the online tool SankeyMATIC 6  to show particular associations between typing results and taxonomy.
Construction and Curation of the COMPASS Database A total of 22,425 sequences representing complete plasmids were retrieved from the NCBI nucleotide database. Duplicate records were first identified based on metadata; records presenting identical size, topology, taxonomy, and header were considered as duplicates. These filtering steps led to the identification of 9299 duplicated records. Among these, 6329 arose from different databases (RefSeq vs GenBank, e. g. , NZ_CP018683. 2 vs CP018683), 22 were different versions of the same sequence (updated vs older version (e. g. , CP022061. 2 vs CP022061. 1), and 2948 had different accession numbers (CP004864. 1 vs CP007611. 1). The list of redundant records removed from the initial list is available in Supplementary Table  S1. The remaining 13,126 plasmids records were subjected to the stringent clustering tool CD-HIT-EST to remove strictly identical sequence (i.
One reference plasmid was kept within each 849 clusters for downstream analyses and 1040 redundant sequences were discarded (Supplementary Tables  S1, S2 ). Finally, chromosomal sequences were identified based on the number of RPS genes present. Out of the 12,086 plasmids, 108 contained less than 10 RPS genes while two records NZ_CP014062. 1 and NZ_CP022019. 1 had 55 and 54 exact matches with RPS genes of the rMLST database. The predicted taxa of these two records were Salmonella enterica and Pseudomonas putida, respectively. These two chromosomal sequences were excluded from the database that finally contains 12,084 plasmids. These two records have since been updated on the current GenBank database as "chromosome, complete genome, " which confirmed the present rMLST results.
Comparison of Plasmid Databases Our COMPASS database shared 11,374 plasmids (94%) with PLSDB  (Galata et al. , 2019) , 9873 plasmids (82%) with pATLAS  (Jesus et al. , 2019) , and 8271 plasmids (68%) with the MOB-suite database, respectively  (Robertson and Nash, 2018)  (Supplementary Figure  S2  and Supplementary Table  S3 ). Altogether, 6440 plasmids were shared between COMPASS, and the other three databases. The content of the three published databases was also compared with COMPASS to confirm the overlap between plasmid resources. MOB-suite, PLSDB, and pATLAS shared 11,610 (96%), 11,380 (83%), and 10,204 (77%) plasmids with COMPASS, respectively (Supplementary Table  S3 ). The differences observed among the number of plasmids shared between two specific databases (for example, COMPASS versus MOB-suite and MOB-suite versus COMPASS) revealed the presence of duplicates.
The presence of identical sequences within a database was indeed confirmed (by running CD-HIT-EST 100%) for MOB-suite (n = 3500), pATLAS (n = 381), and PLSDB (n = 7) but not for COMPASS. The list of duplicated records is available in Supplementary Table  S3. The differences in composition could be explained by the construction and curation steps that were specific to each database. The keywords used for the original query to download plasmid records and the inclusion/exclusion criteria in the filtering steps were diverse. Duplicated records were also removed differently; redundant sequences were identified based on pair-wise distances created by the program mash for the PLSDB database while Robertson and Nash removed Refseq accessions, which contained the accession of another records (Supplementary Methods of the MOBsuite paper).
Description of the COMPASS Database In order to generate a comprehensive database, all the metadata available from the GenBank files were extracted for each plasmid and carefully examined. The information regarding the size, the topology, and the complete lineage was available for all the plasmids whereas the other metadata were partially available. Relevant metadata describing the host range and transmission route are presented below. All the other metadata can be found in Supplementary Table  S4. Plasmids ranged in size from 744 to 2,555,069 bp, with a median at 53,206 bp. The plasmid size distribution varied among the different phyla (Figure  1A ). Large plasmids occurred more frequently in Deinococcus-Thermus, Proteobacteria, and Actinobacteria than the rest of the phyla (Figure  1A ).
The metadata "Collection date" was obtained for 5819 plasmids (48%). Plasmids sequences were obtained from isolates dating from 1884 to 2018 with an exponential increase after 2000, accounting for 85% of all plasmid present in the COMPASS database (Supplementary Figure  S3 ). The vast majority (94%) of the plasmids were circular and among the 665 plasmids that were linear, 48% were isolated from bacteria belonging to the Borreliaceae family. Our plasmid database covered 1571 distinct bacterial species, 443 genera, 189 families, 93 orders, 37 classes, and 21 phyla. Proteobacteria (63%) and Firmicutes (21%) were the most represented phyla and 32% of the bacterial species (n = 3963) belonged to the Enterobacteriaceae family (Figure  1B ). Overall, Escherichia coli (n = 1672), Klebsiella pneumoniae (n = 1053), and S.
Replicon Typing Using MOB-typer, the presence of at least one replicon was detected for 9231 plasmids (76. 4%) (Supplementary Table  S5 ). Due to biases related to the constitutions of GenBank and replicon databases, the number of plasmids encoding replicons varied regarding the taxonomy (Supplementary Figure  S4 ). For instance, 81. 8% of the plasmids associated with Firmicutes and Proteobacteria contained at least one replicon whereas only 29. 6 and 18. 2% of plasmids from Cyanobacteria and Spirochaetes matched the replicon database, respectively. These observations stressed the knowledge gap of plasmid biology associated with less represented taxa in sequence databases. The number of replicons detected within a plasmid varied from a single gene identified in 6828 plasmids to seven replicons identified in a 446 kb plasmid isolated from Raoultella ornithinolytica (Supplementary Figure  S5 ).
Interestingly, the amount of replicons within a plasmid does not correlate with the plasmid size (Pearson test: rho = -2%, p-value = 6. 8 × 10 -3 ); meaning that big plasmids do not necessarily possess several replication genes. Among the 6828 plasmids specifically typed by the presence of a single replicon, 2469 plasmids harbored a known replicon from the ColRNAI family (n = 639) or were associated with a known Inc group (n = 1830) while 4359 plasmids carried a replicon that did not belong to a recognized family or Inc group. These plasmids were associated with 1436 replicon clusters from the MOB-typer database. While 19 Inc groups were identified, plasmids belonging to Inc10 (n = 2), IncT (n = 1), and IncW (n = 4) were rare (Table  1 ). The most frequently assigned Inc groups by MOB-typer were IncI (362 records) followed by IncX (309 records), IncF (also described as F-type replicons) (269 records), IncA/C (176 records), and IncP (158 records).
The plasmids harboring a replicon from the Inc10, Inc18, IncF, IncH, IncI and IncL/M, IncR, IncT, IncU, IncW, IncX, and IncY were associated with a limited host range (less than five bacterial families) while ColRNAI, Inc11, Inc13, IncA/C, IncN, IncP, and IncQ plasmids were present in a broad host range (BHR)  (14, 8, 11, 5, 20 , and 7 bacterial families, respectively) (Figure  2 ). The IncL/M family has now been split into IncL, IncM1, and IncM2 subtypes  (Carattoli et al. , 2015). In addition, the IncA/C group have recently been shown to be compatible and are now distinguished to IncA and IncC  (Ambrose et al. , 2018). However, the MOB-typer database does not differentiate between the subtypes within these two groups and therefore our analysis did not take these new distinctions into account.
Among the 4359 plasmids that The comparison of the two replicon databases revealed that MOB-typer shared only 147 sequences with the PlasmidFinder and carry 2336 unique sequences (Supplementary Table  S7 ). The analysis of the 147 shared replicons showed that 10 MOBtyper sequences associated with Inc11, Inc13, and Inc18 were identical to PlasmidFinder sequences that were classified as different types; thus clarifying the divergence mentioned above for Inc11-13-18 plasmids. Similarly for the IncH plasmids, the allele p0111 (AP010962) in PlasmidFinder was identical to IncH (CP021336) in MOB-typer. The comparison also showed that the IncFIIA and IncFIC alleles were unique in MOB-typer and PlasmidFinder, respectively, explaining the different allelic profiles found for IncF plasmids.
MOB Typing The second classification method is based on the variation of the relaxase protein. Using the relaxase database of MOB-typer, 821 mobilization protein alleles were detected in 5791 plasmids (47. 9%) (Supplementary Table  S5 ). A strong phylum-bias was observed for the detection of relaxases sequences. Indeed, 56. 5 and 41. 3% of plasmids from Proteobacteria and Firmicutes, respectively, harbored relaxase proteins but none was identified in Cyanobacteria, Spirochaetes, or Tenericutes (Supplementary Figure  S4 ). While more than 25% of plasmids in the database contained multiple replicons (see above), a single relaxase protein was present in 90% (n = 5229) of the plasmids. Among the 5229 plasmids that could be assigned a MOB type, the most prevalent was MOB P (n = 2303) followed by MOB F (n = 1422), MOB Q (n = 717), MOB H (n = 378), MOB V (n = 269), and MOB C (n = 106).
In contrast to these known MOB, 34 relaxases did not belong to the 6 main families but matched sequences classified as "MOB_unknown" from the MOB-typer database. We found that the plasmids harboring a relaxase MOB C or MOB H had a limited host range including 9 and 14 bacterial families, respectively, and were mostly associated with Enterobacteriaceae (>80%). MOB F plasmids, found in 43 families, were also highly represented in Enterobacteriaceae (67%) whereas the relaxase MOB V were virtually absent in this family. In contrast to the other MOB groups, relaxase belonging to the MOB P and MOB Q were highly promiscuous (BHR plasmids in 80 and 47 bacterial families, respectively) (Figure  2 ). Plasmid size trended within MOB types, we observed that 95% of MOB H -associated plasmids (n = 378) were larger than 110 kb  while 91% of MOB V plasmids (n = 269) were smaller than 40 kb (Figure  3 ).
Predicted Mobility Plasmid mobility was predicted based on the presence/absence of three mobilization markers (relaxase, oriT, and MPF) (Supplementary Table  S5 )  (Robertson and Nash, 2018). Using the known oriT loci and their matching MOB group from the MOB-typer database, 2048 oriT sequences corresponding to the five MOB types present in the database (MOB C -associated oriT were missing) were detected in 1942 plasmids (16%). The vast majority of plasmids harbored a single oriT excepted for 104 plasmids carrying 2 and a single plasmid bearing 3. The most abundant oriT loci matched MOB P (n = 974) and MOB F (n = 482) groups while 96% of the associated plasmids belonged to Proteobacteria (n = 1624) and Firmicutes (n = 251). The predicted oriT-group matched their relaxase MOB-type for 72% of the plasmids, while discrepancies resulted from the absence of MOB (n = 411), a wrong match (n = 85), or the detection of an unknown type (n = 43).
Finally, 1831 MPF sequences were identified against the MOB-typer database in 4270 plasmids. In comparison to other typing components, the number of MPF per plasmid fluctuated considerably from 1 to 21 genes identified in 608 and 2 plasmids, respectively; 3662 plasmids carried more than 1 MPF and 19% of all MPF-carrying plasmids encoded more than 10 MPFs (Supplementary Figure  S7 ). Regarding the typeability, all the sequences detected within a plasmid were from the same cluster therefore all the 4270 plasmids could be assigned to an MPF type. MPF T and MPF F were the most prevalent types (2053 and 1633 plasmids, respectively) while MPF I was detected in 495 plasmids and MPF G was rare (n = 13). Most of the MPF proteins were detected in Proteobacteria (86. 2%) and Firmicutes (9. 4%) while no MPF were identified in the phyla Chlamydiae, Cyanobacteria, Spirochaetes, and Tenericutes.
DISCUSSION The Comprehensive and Complete Plasmid Database-COMPASS Plasmids are ubiquitous in bacteria and have been shown to be involved in transferring genes important for survival and fitness to their hosts, enabling rapid adaptation to various selective pressures. They have been widely associated with the global dissemination of antimicrobial resistance and represent an important threat to global health  (Chen et al. , 2014; Hardiman et al. , 2016). Despite the important contribution of plasmids to bacterial evolution, little is known about the global diversity of circulating plasmids and their host range. In order to fill this gap, we curated and compiled all the complete plasmid sequences and associated metadata that were available in the NCBI nucleotide archive to create a comprehensive database.
The initial retrieval of 22,425 plasmid records was followed by several curation steps based on their metadata and nucleotide sequences. The identification of redundant sequences using the CD-HIT-EST tool allowed us to identify clusters of identical plasmids. The analysis of these clusters showed that plasmid dissemination occurs more frequently within the same species (91. 8%) rather than transferring horizontally (8. 2%) between different species. In addition, these analyses showed that horizontal transmission is favored between species belonging to the same family. Finally, our new collection composed of 12,084 plasmids covers 1571 distinct bacterial species that were isolated worldwide (126 countries) over more than 100 years. The diversity of the plasmid host range in our database was compared to that of 197,345 bacterial genomes (belonging to 63,240 different Taxonomy IDs) available in the NCBI genome report the 14 April 2019 7.
The host range of the plasmids in our database was found representative of the bacterial genome distribution present in NCBI (i. e. , absence of significant differences based on the Kolmogorov-Smirnov test, p-value = 0. 99). This result partially explained that for many complete plasmid sequences, a complete chromosome sequence from the same isolate may well have been deposited. Among the different bacterial families present in the COMPASS database, we observed an over-representation of plasmids isolated from Enterobacteriaceae (n = 3963), a family of particular interest for studying antimicrobial resistance as its members have become increasingly resistant to the antibiotics commonly used to treat bacterial infection  (Carattoli, 2009; Iredell et al. , 2016). The comparison of COMPASS with previously existing databases showed a similar composition with PLSDB (94%) and pATLAS (82%) in comparison to MOB-suite that only shared 68% with our database.
Plasmid Sizes and Bacterial Hosts Are Related Plasmids covered a wide size range and both intra-and interphyla variations were observed. Indeed, the smallest (644 bp) and largest (2. 5 Mb) plasmids were identified in Proteobacteria (Candidatus Tremblaya and Paraburkholderia caribensis, respectively). This phylum, especially the Alphaproteobacteria, harbored 94% of the megaplasmid (>1 Mb). In addition of carrying a large chromosome of several megabases, the presence of megaplasmids is another feature that characterizes Alphaproteobacteria  (Ettema and Andersson, 2009). In contrast, the smallest plasmids were detected in bacteria belonging to the Tenericutes and Chlamydia phyla, which also happened to bear the smallest chromosomes  (Vetrovsky and Baldrian, 2013; Li and Du, 2014). In our database, almost all chlamydial plasmids (92%) corresponded to an non-conjugative 7.
Limitations of Current Plasmid Typing Methods The large number of plasmids in our collection required a thorough classification to decipher plasmid diversity. Here, the in silico typing of all the plasmids in our database was performed using the recent reference-based tool MOB-typer  (Robertson and Nash, 2018)  and the conventional tool PlasmidFinder. MOB-typer provides replicon typing similar to PlasmidFinder but with the inclusion of transferability predictions based on the presence of relaxase, oriT, and MPF. Even though several studies investigated the diversity of plasmid mobilization proteins  (Garcillán-Barcia et al. , 2009 , 2011; Fernandez-Lopez et al. , 2017) , MOB-typer was (at the time of the manuscript writing) the only tool providing in silico predictions of the plasmid mobilization system but a novel tool, MOBscan developed by  Garcillan-Barcia et al.
(2019)  recently became available online. The proportion of plasmids that can be assigned a replicon type is influenced by the dataset and the bioinformatics methods used. Orlek et al. (2017b)  found that 85% of the curated Enterobacteriaceae plasmids (n = 2097) could be replicontyped  (Orlek et al. , 2017b). In contrast, only 39. 5% of the extensive PLSDB dataset (n = 13,789) were typed  (Galata et al. , 2019). These results both obtained by PlasmidFinder highlight the fact that the performance of the replicon typing is constrained by the bacterial host and most suitable for Enterobacteriaceae and Gram-positive species. The percentage of plasmids typed with PlasmidFinder in our study is very similar (40. 8%) to the one obtained by  Galata et al. (2019). In contrast, MOB-typer was able to type 76% of the plasmids present in COMPASS.
Overall, few discrepancies were observed between plasmid assignments of PlasmidFinder and MOBtyper at the nucleotide level (e. g. , IncH replicons). However, several plasmid replicons were identified by MOB-typer while they were not detected by  PlasmidFinder (e. g. , IncFIIA, and IncP). The fact that MOB-typer database contains 2021 replicon sequences more than PlasmidFinder and that only 147 sequences are shared between the two databases could explain the observed differences. For example, MOB-typer database contains 34 different replicons associated with IncP while PlasmidFinder possesses only four. In addition, it must be emphasized that 56% of the IncP plasmids undetected by PlasmidFinder are larger than 100,000 bp. IncP plasmids have been reported to be small plasmids  (Popowska and Krawczyk-Balska, 2013).
However, our analysis showed that the size of IncP plasmid ranges from 3269 and 1,499,175 bp suggesting that some alleles of IncP replicon could be present in larger plasmids than previously reported. These results highlight the need to fill gaps in plasmid classification, but also the importance of the completeness of plasmid database to have a global view of plasmid properties. With the continuous accumulation of sequencing data, it would be useful to set up a real-time, curated feeding system to maintain comprehensive typing databases. A clear limitation of the current plasmid classification scheme revealed by the present analysis of COMPASS is the frequent occurrence of multiple replicons, complicating the classification.